UNIVERSIDAD COMPLUTENSE DE MADRID FACULTAD DE CIENCIAS QUÍMICAS TESIS DOCTORAL Liver X receptors command the transcriptional and functional polarization of humnan macrophages Control de la polarización transcripcional y funcional de macrófagos humanos por los receptores nucleares LXR MEMORIA PARA OPTAR AL GRADO DE DOCTOR PRESENTADA POR Arturo González de la Aleja Molina Directores Ángel Luis Corbí López Antonio Castrillo Viguera Madrid © Arturo González de la Aleja Molina, 2022 UNIVERSIDAD COMPLUTENSE DE MADRID FACULTAD DE CIENCIAS QUÍMICAS LIVER X RECEPTORS COMMAND THE TRANSCRIPTIONAL AND FUNCTIONAL POLARIZATION OF HUMAN MACROPHAGES Control de la polarización transcripcional y funcional de macrófagos humanos por los receptores nucleares LXR Arturo González de la Aleja Molina Doctoral thesis performed in CIB-CSIC under the direction of: Ángel Luis Corbí López Antonio Castrillo Viguera Madrid, 2022 Come down. From heaven now. In Another Universe, Haelos In my heart you’re still here, it’s the bond that we share. I can feel you’re around everywhere. In All Conscience, Epica I'm waiting for your last goodbye, ‘cause I'm not over it, not over it. I'm waiting for the light of your supernova, your last goodbye. Supernova, Within Temptation ACKNOWLEDGEMENTS En primer lugar, quería agradecer enormemente a mis directores de tesis Ángel y Antonio por darme la oportunidad de desarrollar mi trabajo y mi proyecto. A Ángel por acogerme en su laboratorio, aconsejarme sabiamente durante todos estos años y estar pendiente de mí. A Antonio también por los consejos, el poder siempre contar contigo y por ayudarme a que hiciera la estancia en un sitio adecuado. Los ratos de debate entre todos han sido siempre muy ilustrativos. En este sentido, quería dar las gracias a Noelia por acogerme en su laboratorio en Alemania y estar siempre a dispuesta a escucharme. Después quería agradecer a mis compis de laboratorio, Bárbara y con los que he compartido toda la tesis, Cristina y Miriam, que no habría sido lo mismo sin los ratos de salseo, cotilleo y risas. A Concha, a Ángeles, a Miguel, a María por ayudarme en muchos aspectos del laboratorio. A mis compañeras de universidad, Raquel, y las dos Anas, que, aunque tenemos menos contacto cuando hablamos o nos vemos es como si no hubiera pasado el tiempo. Sensate =). También a mis compis de piso, los actuales y los que estuvieron, que han tenido que soportar lo duro que es un doctorado. Mención a Sergio, Pablo, Mariano y Edurne que han estado en las muy buenas y en las muy malas. Dar las gracias también a mis amigos del pueblo que, aunque mi vida ya no esté allí, siempre podré contar con ellos, los dos Rubenes, MJ, Tamara, Víctor, Mari Sierra, Antonio. Además, a Aurora que siempre ha estado cerca apoyándome y a Dani, que aunque ninguno de los tres pilote el alemán conquistamos Hamburgo. Al resto de aquí, Bea, Nacho, Álvaro, que sin vosotros la vida en Madrid no sería igual y no se acaban nuestras aventuras. A Alfredo que estoy deseando volver a irme de conciertos y que siempre podemos contar el uno con el otro. A mi Marta, que siempre estará ahí para poder echarnos unas risas. A Andrea por nuestras conversaciones, nuestros tirones de orejas y por sumar muchos más momentos juntos. A Jorge, Tarek, Álvaro por esas videollamadas que me amenizaron la cuarentena y las noches alemanas. Gracias a todos. A mis padres y mi hermano porque sin ellos yo probablemente no estaría aquí. También a Ana que ya es como parte de la familia. En especial a papá, que estés donde estés, esto es gracias a ti y espero estés orgulloso. Y para terminar quería agradecer a Rubén, mi compañero de vida. Porque apareciste en el momento ideal y no has dejado de sorprenderme, ayudarme y apoyarme. A todos muchas gracias por formar parte de esto. No hubiera sido lo mismo. INDEX ABBREVIATIONS ................................................................................................................. 8 RESUMEN ...........................................................................................................................12 ABSTRACT ..........................................................................................................................15 INTRODUCTION ..................................................................................................................18 Immune system ................................................................................................................19 Macrophages ....................................................................................................................20 Macrophages present an intricate ontogeny ..................................................................20 Phagocytosis governs macrophage actions...................................................................24 Macrophages display an extraordinary plasticity ...........................................................25 Human macrophages manifest unique myeloid features ...............................................31 Nuclear receptors .............................................................................................................34 Liver X Receptors (LXR) ...................................................................................................35 LXR control cholesterol levels in the organism ..............................................................36 LXR guide macrophage inflammatory and immune functions ........................................38 LXR intertwine with SREBPs to control lipid metabolism ...............................................40 Aryl Hydrocarbon Receptor (AhR) interacts with LXR-dependent signaling ...................44 Macrophages constitute perfect targets for treatment of inflammatory disorders ...............47 Cancer ..........................................................................................................................48 Rheumatoid Arthritis ......................................................................................................51 HYPOTHESIS AND OBJECTIVES .......................................................................................57 EXPERIMENTAL PROCEDURES ........................................................................................59 Generation of human monocyte-derived macrophages in vitro and treatments .................60 RNA extraction and Quantitative real-time RT-PCR (qRT-PCR) .......................................61 Enzyme-Linked ImmunoSorbent Assay (ELISA) ...............................................................61 Lactate production ............................................................................................................61 Luminiscence assays ........................................................................................................61 Western blot .....................................................................................................................61 Cell proliferation assay ......................................................................................................62 Small Interfering Ribonucleic Acid (siRNA) Transfection ...................................................62 Mixed Leukocyte Reaction (MLR) .....................................................................................62 RNA-sequencing and data analysis ..................................................................................62 Statistical analysis ............................................................................................................63 RESULTS.............................................................................................................................67 LXR control macrophage transcriptional and functional polarization .....................................68 LXR are expressed in human pro and antiinflammatory macrophages in basal and activating conditions .........................................................................................................69 LXR have a minor effect on the maintenance of the transcriptome of terminally differentiated macrophages...............................................................................................74 Modulation of LXR modifies the monocyte-to-macrophage differentiation in response to M- CSF or GM-CSF ...............................................................................................................77 Gene ontology of differentially expressed genes in GW3965- and GKS2033-treated macrophages exposes novel roles of LXR receptors in human macrophages ...............90 Clustering analysis of differentially expressed genes in GW3965-treated and GKS2033- treated macrophages .................................................................................................. 101 Analysis of DEGs in GW3965- and GSK2033-treated macrophages uncovers new potential LXR target genes .......................................................................................... 106 LXR instruct several transcription factors in macrophage differentiation ......................... 109 LXR modulation alters responses of basal and activated macrophages .......................... 113 LXR modulation controls macrophages cytokine production ........................................ 113 LXR activity regulates antitumoral activity and T lymphocyte activation ....................... 119 LXR activity affects the Methotrexate response of macrophages ................................. 122 LXR direct the polarization effect of pathological fluids over human monocytes .............. 124 LXR contribute to the AhR-dependent antiinflammatory polarization of human macrophages ........................................................................................................................................... 129 Sustained AhR inhibition impairs the acquisition of the transcriptional signature of M-MØ and their functional differentiation ................................................................................... 130 LXR transcription factors regulate transcriptional changes in M-MØ differentiated in AhR- inhibited conditions ......................................................................................................... 134 DISCUSSION ..................................................................................................................... 138 LXR control macrophage transcriptional and functional polarization. ........................... 139 LXR contributes to the AhR-dependent antiinflammatory polarization of human macrophages. ............................................................................................................. 145 CONCLUSIONS ................................................................................................................. 147 REFERENCES ................................................................................................................... 149 ILLUSTRATION INDEX Figure 1. The immune system exerts its complex endeavor through multiple cellular and molecular mechanisms .........................................................................................................20 Figure 2. Macrophage ontogeny varies among the different tissues of the organism ............22 Figure 3. Numerous transcription factors determine tissue-resident macrophage identity .....23 Figure 4. Phases of bacterial macrophage phagocytosis ......................................................25 Figure 5. Phagocytosis of bacteria or apoptotic cells (efferocytosis) shows certain particularities ........................................................................................................................26 Figure 6. Macrophages display a full spectrum of phenotypes or "polarization states"..........27 Figure 7. Macrophages develop trained immunity ................................................................28 Figure 8. Polarization of macrophages determines the acquisition of opposite metabolic pathways. .............................................................................................................................30 Figure 9. Macrophage Colony-Stimulating Factor (M-CSF) and Granulocyte Macrophage Colony-Stimulating Factor (GM-CSF) exert their functions through different receptors .........32 Figure 10. Human proinflammatory (GM-MØ) and anti-inflammatory macrophages (M-MØ) exhibit M1 and M2 macrophages characteristics ..................................................................32 Figure 11. Human monocyte-derived proinflammatory GM-MØ and antiinflammatory M-MØ acquire particular features through expression and regulation of distinct molecular cues .....34 Figure 12. The structure of nuclear receptors is conserved ..................................................35 Figure 13. LXR-dependent transactivation of DNA is regulated by corepressors and coactivators. .........................................................................................................................36 Figure 14. LXR control all phases of cholesterol homeostasis ..............................................38 Figure 15. LXR wield antiinflammatory and proinflammatory effects in macrophages ...........40 Figure 16. Scheme of the SREBP-regulated metabolic pathways. .......................................41 Figure 17. SREBPs are activated by sequential proteolytic cleavages that liberate the active N-terminal domain ................................................................................................................42 Figure 18. Intracellular cholesterol levels regulate LXR/SREBP crosstalk ............................43 Figure 19. The Aryl Hydrocarbon Receptor (AhR) belongs to a large family of bHLH PAS transcription factors ..............................................................................................................45 Figure 20. Aryl Hydrocarbon Receptor (AhR) structure and its activation/inactivation ...........46 Figure 21. Tumor Associated Macrophages (TAMs) exert several functions that promote tumor growth, extravasation and metastasis. ........................................................................49 Figure 22. Macrophages constitute perfect targets to treat cancer .......................................51 Figure 23. Macrophages populate the synovial membrane ...................................................52 Figure 24. Macrophages concentrate RA pathogenesis .......................................................53 Figure 25. Drugs that target macrophages encompass crucial treatments for RA.................55 Figure 26. Proinflammatory GM-MØ and anti-inflammatory M-MØ express LXR proteins and LXRα splicing isoforms. ........................................................................................................70 Figure 27. Proinflammatory GM-MØ and anti-inflammatory M-MØ exhibit distinct LXR target gene expression ...................................................................................................................71 Figure 28. Effect of LXR modulation by synthetic agonists on the expression of polarization- specific genes. .....................................................................................................................75 Figure 29. Effect of LXR silencing on the expression of polarization-specific genes. ............76 Figure 30. Transcriptional effect of modulation of LXR activity along M-MØ differentiation. ..78 Figure 31. Transcriptional effect of modulation of LXR activity along GM-MØ differentiation 79 Figure 32. Analysis of the transcriptome of LXR-modified M-MØ ..........................................82 Figure 33. Analysis of the transcriptome of LXR-modified GM-MØ. ......................................83 Figure 34. Effect of modulation of LXR activity on the expression of genes regulated along monocyte-to-macrophage differentiation ..............................................................................84 Figure 35. Gene ontology analysis of LXR-modulated macrophages revealed new functions related to LXR activity ..........................................................................................................93 Figure 36. Clustering analysis of LXR-dependent differentially expressed genes in M-MØ . 103 Figure 37. Clustering analysis of LXR-dependent differentially expressed genes in GM-MØ ........................................................................................................................................... 105 Figure 38. Analysis of LXR-dependent DEGs in M-MØ generated in the presence of either GW3965 or GSK2033 ........................................................................................................ 107 Figure 39. Analysis of LXR-dependent DEGs in GM-MØ generated in the presence of either GW3965 or GSK2033 ........................................................................................................ 108 Figure 40. Several transcription factors are influenced by LXR in macrophage differentiation. ........................................................................................................................................... 110 Figure 41. Molecular mechanisms underlying the macrophage polarizing effect of LXR activation ........................................................................................................................... 112 Figure 42. LXR modulation alters cytokine production by M-MØ in basal and LPS-activating conditions ........................................................................................................................... 116 Figure 43. LXR modulation alters cytokine production by GM-MØ in basal and LPS-activating conditions. .......................................................................................................................... 118 Figure 44. LXR-altered human macrophages supernatants exert powerful antitumoral activities ............................................................................................................................. 120 Figure 45. LXR activity modulation alters the T-cell stimulatory ability of macrophages ...... 121 Figure 46. LXR activity modulation on human macrophages influences responsiveness to Methotrexate ...................................................................................................................... 123 Figure 47. Effect of LXR activation on the transcriptional profile of macrophages generated in the presence of tumor-derived ascitic fluid .......................................................................... 126 Figure 48. Effect of LXR inactivation on the transcriptional profile of macrophages generated in the presence of rheumatoid arthritis synovial fluid .......................................................... 127 Figure 49. LXR activation guides monocytes to acquire a more proinflammatory phenotype while LXR inactivation instructs monocytes to differentiate into a more antiinflammatory polarization state…………………………………………………………………………………...128 Figure 50. AhR inhibition impairs the acquisition of the transcriptional signature of M-MØ and their functional differentiation……………………………………………………………………..131 Figure 51. Chronic inhibition of AhR during M-MØ differentiation results in altered bioenergetic profile ............................................................................................................. 133 Figure 52. Sustained AhR inhibition along M-MØ differentiation modifies the expression of the transcription factors LXRα and SREBP ........................................................................ 135 Figure 53. LXR mediate the transcriptional changes secondary to chronic AhR inhibition during M-MØ differentiation ................................................................................................ 136 Figure 54. LXR and AhR cooperation controls human antiinflammatory macrophage polarization. ........................................................................................................................ 137 TABLE INDEX Table 1. Primers used in the present study ...........................................................................64 Table 2. Previously reported LXR target genes ....................................................................72 Table 3. M-MØ differentially expressed genes upon LXR modulation ...................................85 Table 4. GM-MØ differentially expressed genes upon LXR modulation ................................88 Table 5. Upregulated GW-M-MØ predicted functions ...........................................................94 Table 6. Downregulated GW-M-MØ predicted functions .......................................................95 Table 7. Upregulated GSK-M-MØ predicted functions ..........................................................96 Table 8. Downregulated GSK-M-MØ predicted functions .....................................................96 Table 9. Upregulated GW-GM-MØ predicted functions .........................................................97 Table 10. Downregulated GW-GM-MØ predicted functions ..................................................98 Table 11. Upregulated GSK-GM-MØ predicted functions .....................................................98 Table 12. Downregulated GSK-GM-MØ predicted functions .................................................99 Table 13. Upregulated GW/GSK-GM-MØ predicted functions ........................................... 100 Table 14. Downregulated GW/GSK-GM-MØ predicted functions ........................................ 100 Table 15. Cytokine production in M-MØ and GM-MØ differentiated in the presence of LXR modulators ......................................................................................................................... 114 ABBREVIATIONS 8 Abbreviations 5-AZA: 5-Azacytidine 5-HT: 5- hydroxytryptamine or Serotonin AASS: Aspartate–Arginosuccinate Shunt Pathway ABCA: ATP-Binding Cassette subfamily A ABCG: ATP-Binding Cassette subfamily G ACC/ACAC: Acetyl-CoA Carboxylase ACLY: ATP-Citrate Lyase ACPA: Anti-Citrullinated Protein Antibody and (RF), ACSL: Acyl-CoA Synthetase Long chain family AdipoR: Adiponectin Receptor AhR: Aryl hydrocarbon Receptor AHRR: Aryl Hydrocarbon Receptor Repressor AIM/CD5L: Apoptosis Inhibitor of Macrophage AIP: AHR-interacting protein AP1: Activator Protein 1 Apo: Apoprotein Arg1: ARGinase 1 ARL4C/ARL7: ADP ribosylation factor like GTPase 4C ARNT: AhR Nuclear Translocator ASC2: Activating Signal Co-integrator 2 ATP: Adenosine TriPhosphate BLIMP1: B Lymphocyte-Induced Maturation Protein 1 C/EBPβ: CCAAT/Enhancer-Binding Protein β CAR-T: Chimeric Antigen Receptor T CETP: Cholesterol Ester Transfer Protein ChREBP/MLXIPL: Carbohydrate Response Element Binding Protein CIDEA: Cell Death-Inducing DNA fragmentation factor-α-like Effector A CIITA: Class II Major Histocompatibility Complex Transactivator COX2: CycloOXygenase 2 CPT: Carnitine Palmitoyl Transferase CRISPR-Cas: Clustered Regularly Interspaced Short Palindromic Repeats CYP: Cytochrome P450 Protein DBA: Dimethyl Bisphenol A DBD: DNA Binding Domain DC: Dendritic Cell DFO/DFX: Deferoxamine DHCR7/24:7-/24-DeHydroCholesterol Reductase DMFO: α-Difluoromethylornithine DMHCA: N, N-DiMethyl-3β-Hydroxy- CholenAmide DMSO: DiMethyl SulfOxide DNA: Deoxyribonucleic Acid DRE: Dioxin Response Elements ECAR: Extracellular Acidification Rate EEPD1: Endonuclease/Exonuclease/Phosphatase family Domain containing 1 EMT: Epithelial-Mesenchymal Transition FABP: Fatty Acid Binding Protein FASN: Fatty Acid Synthase FBS: Fetal Bovine Serum FDPS: Farnesyl DiPhosphate Synthase FICZ: 6-FormylIndolo[3,2-b]CarbaZole FIZZ1: Found in Inflammatory Zone protein FRβ: Folate Receptor β 9 Abbreviations FXR: Farnesoid X Receptor GAPDH: Glyceraldehyde-3-Phosphate Dehydrogenase GH: Growth Hormone GSK3: Glycogen Synthase Kinase 3 GM-CSF: Granulocyte Macrophage Colony-Stimulating Factor GPAT3: Glycerol-3-Phosphate AcylTransferase GPR120: G Protein-Coupled Receptor 120 GSEA: Gene Set Enrichment Analysis GSH: Glutathione HDAC: Histone Deacetylase HDL: High Density Lipoprotein HIF: Hypoxia Inducible Factor HLA: Human Leukocyte Antigen HMGCR: 3-Hydroxy-3-Methyl-Glutaryl- Coenzyme A Reductase HMGCS: 3-Hydroxy-3-Methyl-Glutaryl- Coenzyme A Synthase IDOL/MYLIP: Increased Degradation of LDL Receptor Protein IFN: Interferon IGF1: Insulin-like Growth Factor 1 IL: InterLeukin iNOS: inducible Nitric Oxide Synthase INSIG: INSulin-Induced Genes IRF: Interferon Regulatory Factor IVIG: Intravenous Immunoglobulins JAK: Janus Kinase JNK: c-Jun N-terminal Kinase KO: Knock-Out LBD: Ligand-Binding Domain LBP: Lipopolysaccharide Binding Protein LDHA: Lactate Dehydrogenase A LDL: Low Density Lipoprotein LDLR: Low Density Lipoprotein Receptor LPCAT3: LysoPhospholipid AcylTransferase 5 LPL: LipoProtein Lipase LPS: LipoPolySaccharide LXR: Liver X Receptor LXRE: Liver X Receptor Element MAF: MusculoAponeurotic Fibrosarcoma oncogene MAPK: Mitogen-Activated Protein Kinase M-CSF: Macrophage Colony-Stimulating Factor MDSC: Myeloid Derived Suppressor Cell MERTK: MER Tyrosine-protein Kinase MGL: Macrophage Galactose-type Lectin MHC: Major Histocompatibility Complex MLR: Mixed Leukocyte Reaction MMP: Matrix Metalloprotease mTOR: mammalian Target of Rapamycin mTORC1: mTOR complex 1 MTT: 3-(4,5-diMethylThiazol-2-yl)-2,5- ciphenylTetrazolium bromide MTX: Methotrexate MVK: MeValonate Kinase NAD: Nicotinamide Adenine Dinucleotide NADPH: Nicotinamide Adenine Dinucleotide Phosphate NCOA1: Nuclear Receptor Co-Activator 1 NCoR1: Nuclear Receptor Corepressor 1 NFkB: Nuclear Factor kappa-light-chain- enhancer of activated B cells NO: Nitric Oxide NPC: Niemann-Pick C 10 Abbreviations NPC1L1: Niemann-Pick C1-Like 1 NR0B2: Nuclear Receptor subfamily 0 group B member 2 NR1D1: Nuclear Receptor Rev-ErbA- alpha NTD: N-Terminal Domain OCR: Oxygen Consumption Rate OXPHOS: Oxidative Phosphorylation Panther: Protein ANalysis THrough Evolutionary Relationships PCB: PolyChlorinated Biphenyl PD1: Programmed Cell Death Protein 1 PDGF: Platelet Derived Growth Factor PDL1: Programmed Cell Death Protein Ligand 1 PER: Period Circadian Protein PGE2: Prostaglandin E2 PI3K: PhosphatidylInositol 3-Kinase PLTP: Phospholipid Transfer Protein PMA: Phorbol 12-Myristate 13-Acetate PPAR: Peroxisome Proliferator-Activated Receptor PPP: Pentose Phosphate Pathway PTX3: Pentraxin 3 RA: Rheumatoid Arthritis RANKL: Receptor Activator of Nuclear factor Kappa-Β Ligand RAR: Retinoid Acid Receptor RARA: Retinoid Acid Receptor Alpha RASF: Rheumatoid Arthritis Synovial Fluid RF: Rheumatoid Factor RNA: Ribonucleic Acid ROS: Reactive Oxygen Species RPMI: Roswell Park Memorial Institute RXR: Retinoid X Receptor S1P: Site-1 Protease S2P: Site-2 Protease SCAP: SREBP Cleavage-Activating Protein SCARB1/SR-BI: Scavenger Receptor Class B Member 1 SCD: Stearoyl-CoA Desaturase SHP: Small Heterodimer Partner SiRNA: Small Interfering RNA SIM: Single-Minded Protein SLC: Solute Carrier Family SMPDL3A: sphingomyelin phosphodiesterase acid-like 3A SMRT: Silencing Mediator of Retinoic acid and Thyroid hormone receptor SOCS: Suppressor of Cytokine Signaling SQLE: SQuaLene Synthase SREBP: Sterol Regulatory Element Binding Protein STAT: Signal Transducer and Activator of Transcription TAF: Tumor Ascitic Fluid TAM: Tumor Associated Macrophage TAT: TAT-cyclo-CLLFVY TCDD: 2,3,7,8-TetrachloroDibenzo-p- Dioxin TEACOP: Trace-Extended Aromatic Condensation Product TGF: Transforming Growth Factor THRSP: Thyroid hormone-inducible hepatic protein TYMS: Thymidylate Synthase TLR: Toll-Like Receptor TMEM135: Transmembrane Protein 135 TNF: Tumor Necrosis Factor 11 Abbreviations UGT1A3: UDP GlucuronosylTransferase family 1 member A3 VEGF: Vascular Endothelial Growth Factor XRE: Xenobiotic Response Element RESUMEN Resumen 13 Control de la polarización transcripcional de macrófagos humanos por los receptores nucleares LXR Los macrófagos pueblan todos los tejidos del organismo y son imprescindibles para su homeostasis. Los macrófagos muestran un espectro de fenotipos o estados de polarización que vienen determinados por numerosas moléculas y sustancias. Por lo tanto, los macrófagos son células extremadamente plásticas capaces de detectar su entorno y cambiar y responder en consecuencia. Durante la inflamación, los macrófagos ejercen funciones efectoras proinflamatorias y antiinflamatorias/resolutivas necesarias para el retorno a la homeostasis, y cuyo desequilibrio promueve o colabora en la etiología de enfermedades inflamatorias crónicas. Para simplificar el estudio de la polarización de los macrófagos el presente estudio se ha centrado en dos fenotipos opuestos: macrófagos proinflamatorios y antiinflamatorios. In vitro, podemos diferenciar monocitos de donantes de sangre a macrófagos utilizando GM- CSF y M-CSF, respectivamente. La citoquina M-CSF induce la generación de macrófagos con perfil antiinflamatorio (IL10+++) e inmunosupresor (protumoral). Por contra, GM-CSF dispone a los macrófagos para la presentación de antígenos, la estimulación de linfocitos T (antitumoral) y una potente actividad proinflamatoria (TNF+++IL6+++). Por lo tanto, los macrófagos proinflamatorios (GM-MØ) y los macrófagos antiinflamatorios (M-MØ) equiparan el fenotipo in vivo de macrófagos sinoviales de pacientes con artritis reumatoide y de macrófagos asociados a tumores en pacientes con cáncer. En consecuencia, estos subtipos de macrófagos generados in vitro constituyen un modelo idóneo para estudiar el comportamiento de los macrófagos en diferentes escenarios. Además, a medida que la reprogramación de macrófagos se está estableciendo como una estrategia terapéutica, el conocimiento de las bases moleculares de la diferenciación de macrófagos y su (re)polarización se hace completamente necesario. Numerosas investigaciones han demostrado que GM-MØ y M-MØ muestran un transcriptoma completamente único y específico que determina su fenotipo, y que la modificación de este perfil se ve reflejada en su comportamiento funcional. Por lo tanto, el análisis del transcriptoma de macrófagos se puede utilizar para abordar el efecto de diferentes moléculas y receptores en su polarización. Los Receptores X Hepáticos (en inglés Liver X Receptors, LXR) son determinantes para la función de los macrófagos ya que controlan el eflujo del colesterol y el metabolismo de los lípidos, pero también la fagocitosis de células apoptóticas, la migración de células dendríticas y la diferenciación de macrófagos del bazo. Además, los LXR ejercen acciones antiinflamatorias y potencian la secreción de citoquinas, y presentan una mayor expresión en los macrófagos sinoviales y en los macrófagos asociados a tumores en condiciones patológicas. Las dos proteínas de la familia LXR, LXRα (gen NR1H3) y LXRβ (gen NR1H2), son factores de transcripción dependientes de ligando que regulan la expresión génica por lo que su estado de activación se puede manipular in vitro, lo que permite estudiar su papel fisiopatológico, analizar su contribución a la polarización y función de macrófagos humanos y evaluar su potencial terapéutico en enfermedades con un alto componente inflamatorio, como la artritis o el cáncer. En primer lugar, hemos analizado la expresión de LXR y sus genes diana, así como su nivel basal de activación, en GM-MØ y M-MØ. Dada su elevada expresión en ambos tipos de macrófagos, determinamos el perfil génico de los macrófagos generados tras la exposición de monocitos a una dosis de un potente agonista de LXR, GW3965, o del Resumen 14 potente agonista inverso GSK2033. De esta forma hemos determinado que los factores LXR son esenciales para la adquisición del perfil génico de GM-MØ y M-MØ, que la activación de LXR promueve la diferenciación proinflamatoria y que la inactivación de los LXR impulsa la diferenciación antiinflamatoria. De esta manera comprobamos también que la activación de LXR favorece una mayor ratio de secreción de citoquinas pro/antiinflamatorias, en un escenario que asemeja al “training” de macrófagos, y hemos puesto de manifiesto que los factores LXR modulan la presentación de antígenos a linfocitos T, la respuesta a metotrexato y la capacidad antitumoral de M-MØ y GM-MØ. De forma adicional hemos comprobado que los factores LXR regulan la expresión de MAF y MAFB, determinantes en la polarización antiinflamatoria y de los factores IRF4 y PPARγ, que favorecen actividades proinflamatorias. Los resultados posteriores sugieren que el factor MAFB podría contribuir a los efectos proinflamatorios de la activación de los LXR en M-MØ. Para recapitular estos hallazgos en escenarios fisiopatológicos y determinar si la modulación de los LXR podría plantearse como tratamiento terapéutico, hemos analizado el efecto de los factores LXR en la polarización proinflamatoria promovida por el líquido sinovial de pacientes con artritis reumatoide y en la polarización antiinflamatoria inducida por líquidos ascíticos tumorales. Nuestros resultados han revelado que la modulación de la actividad de LXR también es capaz de alterar la polarización inducida por ambos fluidos patológicos. Finalmente, hemos demostrado que los efectos proinflamatorios derivados de la inhibición crónica del Receptor de Aril-Hidrocarburos (en inglés, Aryl Hydrocarbon Receptor, AhR) son parcialmente dependientes de los factores LXR. El bloqueo de los receptores LXR impide la adquisición de algunos genes de la firma génica proinflamatoria promovida por la inhibición de AhR e inhibe el efecto que la inhibición de AhR tiene sobre los genes dependientes de los factores SREBP. Todos los resultados obtenidos nos permiten concluir que: 1) los receptores nucleares LXR son esenciales para la diferenciación de monocitos humanos a macrófagos in vitro y cumplen un rol minoritario en macrófagos ya diferenciados; 2) la activación de LXR promueve una polarización pro-inflamatoria, mientras que su inactivación favorece la adquisición de un estado de polarización anti-inflamatorio, y que ambos efectos se corroboran en presencia de fluidos biológios patológicos; 3) la actividad de LXR es determinante para el comportamiento funcional de macrófagos humanos; 4) los efectos de LXR en macrófagos implican la participación de otros factores de transcripción como MAFB, IRF4 y PPARγ; y 5) LXR participa de la capacidad del factor AhR de promover la polarización antiinflamatoria de macrófagos humanos. ABSTRACT Abstract 16 Liver X Receptors command the transcriptional and functional polarization of human macrophages Macrophages populate every tissue in the body, where are determinant to their homeostasis. To develop this crucial task, macrophages display a quasi-infinite spectrum of phenotypes or "polarization states", and these states are determined by tissue molecules and substances present in their immediate surroundings. Thus, macrophages are extremely plastic cells capable of sensing and adapting to their environment. During inflammation, macrophages exert pro-inflammatory and anti-inflammatory/resolving effector functions, which are crucial for tissue injury removal and return to homeostasis, and whose unbalance promotes chronic inflammatory diseases. To simplify the study of macrophage polarization, we analyzed two extreme polarization states: proinflammatory and antiinflammatory macrophages. We differentiated monocytes in vitro from healthy blood donors to macrophages using GM-CSF and M-CSF, respectively. M-CSF primes macrophages for acquisition of an anti-inflammatory (IL10high) and immunosuppressive (protumoral) profile. GM-CSF is produced at sites of inflammation and primes macrophages for robust antigen-presenting, T cell-stimulatory (antitumoral) and pro-inflammatory activity (TNFhigh IL6high). Therefore, human proinflammatory macrophages (GM-MØ from now on) and human antiinflammatory macrophages (M-MØ from now on) resemble in vivo arthritis-related synovial macrophages and tumor associated macrophages, respectively. These in vitro macrophages constitute a powerful model to study the behavior of macrophages in different scenarios. Besides, as macrophage re-programming is being actively assessed as a therapeutic strategy for numerous inflammatory disorders, the knowledge of the molecular basis regulating macrophage differentiation and (re)polarization is absolutely required. Previous investigations have shown that GM-MØ and M-MØ display a unique and specific gene set signature that determines their phenotype, and that the modification of this gene profile reflects the functional performance of these macrophages. Consequently, analysis of macrophage transcriptome can be used to address the role of distinct molecular cues in macrophage polarization. The Liver X Receptors (LXR) are nuclear receptors that control macrophage function, mainly cholesterol efflux and lipid metabolism, but also phagocytosis of apoptotic cells, dendritic cell migration and splenic macrophage differentiation. Besides, LXR have recently been linked to inflammation as LXR exert anti-inflammatory actions and potentiate cytokine secretion and are also upregulated in synovial macrophages and in tumor associated macrophages in pathological conditions. The two proteins of the LXR family, LXRα (NR1H3 gene) and LXRβ (NR1H2 gene), are ligand-activated transcription factors that regulate gene expression whose state of activation can be effectively manipulated in vitro to study their contribution to distinct processes. Given these antecedents, LXR nuclear receptors constitute potential therapeutic targets in diseases with a high inflammatory component like arthritis or cancer. First, we analyzed the expression of LXR and their targets, as well as their basal level of activation, in both GM-MØ and M-MØ. Considering that LXR are expressed at high levels in both macrophages, we modulated LXR activity during monocyte to macrophage transition and analyzed the gene profile of fully differentiated macrophages. To that end, we treated monocytes with one dose of a potent agonist of LXR, GW3965, or a potent inverse agonist, GSK2033. In this manner, we determined that LXR nuclear receptors are essential for acquisition of the GM-MØ and M-MØ gene profile, and found that LXR activation promotes Abstract 17 proinflammatory differentiation whereas LXR inactivation does the opposite. LXR activation also promoted higher pro- and antiinflammatory cytokine secretion but with a greater ratio of pro- vs antiinflammatory cytokines in a macrophage training-like scenario, where macrophages are primed for a second response upon TLR stimulation. On the other hand, LXR inactivation impeded an optimal production of pro- and antiinflammatory cytokines. We also analyzed antigen presentation to T Lymphocytes, methotrexate response and direct antitumoral capacity of macrophages as characteristic function that define the M-MØ or GM- MØ phenotypes, and the overall results corroborated the transcriptomic analyses. Additionally, we found that LXR regulate MAFB expression, an important regulator of antiinflammatory polarization and also IRF4 and PPARγ expression, two factors that favors proinflammatory differentiation and activities. Besides, preliminary results suggest that MAFB could modulate the proinflammatory effects of LXR activation in M-MØ. To recapitulate these transcriptomic findings in a physiopathological scenario and determine if LXR modulation could constitute a therapeutic treatment, we studied the contribution of LXR to the proinflammatory effect of rheumatoid arthritis synovial fluids and the antiinflammatory effect of tumor-derived ascitic fluids. Results revealed that activation of LXR impaired the acquisition of antiinflammatory markers induced by ascitic fluid, and that LXR inactivation impeded the upregulation of proinflammatory genes in monocytes exposed to RA synovial fluids. Finally, we demonstrated that the proinflammatory effects that AhR inhibition exerted on human M-MØ were partially dependent on LXR, and that blocking of LXR impeded the acquisition of certain proinflammatory genes in M-MØ exposed to AhR inhibitors and abrogated AhR-influenced SREBP signaling. Considering all the results generated upon this thesis work, we can conclude that: 1) LXR nuclear receptors are essential for the in vitro differentiation of human monocyte-derived macrophages and exert a minor role in fully differentiated human macrophages, 2) LXR activation promotes a proinflammatory polarization in macrophages, and their inactivation promotes an antiinflammatory polarization state, 3) LXR activity determines the functional performance of human macrophages, 4) LXR control of macrophage differentiation and polarization might involve the participation of MAFB, IRF4 and PPARγ transcription factors and 5) LXR partially mediates the influence of AhR on the antiinflammatory polarization of human macrophages. INTRODUCTION Introduction 19 Immune system he immune system defends and protects us against external threats and internal traumas through a variety of molecular mechanisms and cellular components. The immune system has evolved over time to specialize and develop multiple ways to fight any harm that can break tissue homeostasis (figure 1). In response to external threats, like bacteria or virus, the immune system exerts its action in a sequential manner: the first barrier of defense is constituted by skin and mucus membranes, and inner defense mechanisms initiate when those protections are overcome. These secondary mechanisms include the innate immune system and the adaptive immune system. The principal actors of innate immune system are granulocytes, macrophages and dendritic cells (DCs). These cells are capable of rapidly sensing their surroundings and control the damage, so tissues can return to their homeostasis. Besides, neutrophils and monocytes can travel from the peripheral blood to damaged tissues to help containing pathogens or injury. To fight pathogens, macrophages and granulocytes use common strategies for pathogen detection, and later respond accordingly by mechanisms like phagocytosis or formation of neutrophil extracellular traps. If damage is sustained, neutrophils start to die and macrophages need to be assisted by the adaptive immune system, mainly comprised by T and B lymphocytes. Macrophages and DCs capture pathogens and digest their protein contents for subsequent presentation and activation of antigen-specific T lymphocytes, a task preferentially exerted by DCs after migration into local lymph nodes. Once the adaptive immune response is initiated, antigen-specific T lymphocytes fight the pathogens through several mechanisms, whereas plasma cells start secreting antibodies that reach the injured tissue and help destroy pathogens. Once the damage is resolved, macrophages contribute to returning damaged tissues back to homeostasis and a subset of T lymphocytes and plasma cells travel to the bone marrow and remain there as memory cells1–4. Other cells that assist in all these processes are natural killer cells and mast cells. Altogether, macrophages are pivotal cells for the immune system to respond to pathogens and injury, to communicate with the rest of immune cells and other cell types, and to repair the aftermath of the damage. Indeed, macrophages are not only indispensable in fighting infection or harming conditions but also play essential functions in the maintenance of tissue homeostasis in the steady state. T Introduction 20 Figure 1. The immune system exerts its complex endeavor through multiple cellular and molecular mechanisms. Physical barriers constitute the first line of defense, whereas innate immunity and adaptive immunity act in second place. In fact, physical barriers are sometimes considered as a component of the innate immunity. Macrophages represent an indispensable hub that integrates all of these responses. Tissue- resident macrophages phagocytose microorganisms or cell debris to eliminate them and secrete factors that recruit monocytes and granulocytes into the damaged tissue. Macrophages and DCs also present foreign molecules to lymphocytes to initiate adaptive immunity. Once the damage is controlled, macrophages participate in tissue regeneration and return to homeostasis. Adapted from 5 . Macrophages acrophages populate all tissues of the body, where they are crucial for proper tissue function in homeostasis. Tissue-resident macrophages group a very diverse set of macrophages whose differentiation, phenotype and functions are tissue-specific6,7. This is so because macrophages adapt to their environment, integrating molecular cues from their immediate surroundings and from the outside, what allows them to acquire tissue- specific functionalities8. Tissue-resident macrophage ontogeny is quite diverse. In the past, the dogma on the origin of the mononuclear phagocyte system (monocytes and macrophages) was that bone marrow-derived peripheral blood monocytes migrated into the different tissues, where they M Introduction 21 differentiated into tissue-resident macrophages. Nowadays, data generated through genetic studies and fate-mapping experiments have proven this dogma to be inaccurate and have demonstrated that tissue-resident macrophages have distinct origins. Macrophages originate from different precursors during primitive and transient hematopoiesis, coming from the yolk sac and fetal liver, or definitive hematopoiesis, coming from the bone marrow9–18 (figure 2). Yolk sac macrophages infiltrate all tissues (including spleen, brain, lung, liver, kidney, skin, gut, lymph nodes, heart, pancreas, stomach and peritoneum) in early stages of development. Except for brain and large peritoneal macrophages, yolk sac-derived macrophages are later superseded by fetal liver-derived macrophages. At later stages of development, bone marrow-derived peripheral blood monocytes replace fetal liver monocytes/macrophages in the gut, spleen, heart, skin, kidney and the pancreas, while fetal liver-derived macrophages remain in other tissues. In some tissues [gut, skin (dermis), lymph nodes and peritoneum (small peritoneal macrophages)], macrophages are continuously replenished by new monocytes that come from adult bone marrow19–25. Arterial macrophages represent a unique subset of macrophages, as they derive from yolk sac progenitors and their number declines with aging, but are not replaced by bone marrow-derived cells26,27. Adipose tissue macrophages ontogeny is unknown, although some studies in obese mice suggest a possible adult monocyte-derived origin28,29. All these populations of tissue-resident macrophages, except for those derived from the bone marrow, can self-maintain. In fact, the determination of the factors promoting and controlling proliferation of tissue-resident macrophages is a very active area of research. Upon tissue damage, tissue-resident macrophages proliferate and, together with monocyte- derived macrophages, replaced damaged/dying macrophages and help replenishing the normal content of tissue-resident macrophages24,30–33. In fact, monocyte recruitment and local macrophage proliferation are likely to be interrelated processes34. Moreover, tissue-resident macrophages, independently of their ontogeny, depend on different transcription factors and molecular cues for their maintenance and tissue-specific differentiation (figure 3). For example, Liver X Receptor α (LXRα)35 or SpiC36,37 are essential for splenic macrophages, Peroxisome Proliferator Activated Receptor γ (PPARγ) is required for generation of alveolar macrophages in the lung38,39, Transforming Growth Factor β (TGFβ) and IL-34 are needed for generation of microglia40–42, and GATA6, Retinoic Acid and CCAAT/Enhancer-Binding Protein β (C/EBPβ) promote the differentiation of peritoneal macrophages24,43–45. It is important to mention that only a few studies have addressed the relevance of ontogeny in the case of human tissue-resident macrophages. However, experiments using transplants suggested that alveolar macrophages are maintained by local self-renewal46–48. In skin transplants, the majority of dermal macrophages were not replaced after 1 year of transplant, also suggesting these macrophages self-maintain independently of circulating monocytes49. Surprisingly, human gliomas experiments revealed that some tumor associated macrophages were recruited from blood, suggesting a possible implication of blood monocytes in human microglia establishment50. However, these experiments have not unraveled their developmental origin. Fortunately, very recent studies of single cell sequencing of human embryonic tissues suggest that early embryonic microglial development in humans resembles their murine counterparts, and have established a transcriptomic data basis for future researchers to address the ontogeny of different human tissue-resident macrophage populations51. Introduction 22 Figure 2. Macrophage ontogeny varies among the different tissues of the organism. Brain macrophages and large peritoneal macrophages are originated from yolk sac and self-maintain during adult life. In epidermis, most yolk sac macrophages are replenished by fetal liver macrophages but both populations coexist during life. In lung and liver, yolk sac macrophages are completely replaced by fetal liver macrophages. In these four tissues, macrophages are maintained by local proliferation with no participation from bone marrow-derived monocytes. For heart, pancreas, gut and dermis (and spleen, pancreas, lymph nodes and small peritoneal macrophages, not shown), all macrophages are eventually replaced by bone marrow-derived monocytes. In heart and pancreas, the turnover of these macrophages is slow, with low but effective proliferation. However, gut, dermis, lymph node and small peritoneal tissue-resident macrophages are continuously replaced by bone marrow-derived monocytes, depending exclusively of this source of cells. Adapted from 52 . Introduction 23 Figure 3. Numerous transcription factors determine tissue-resident macrophage identity. Macrophage populations are regulated by two sets of molecular and transcriptional cues. First, PU.1, MYB, c- MAF, MAFB and ZEB2 regulate the acquisition of an intermediate pre-macrophage phenotype that is completed upon interaction with tissue-dependent signals in a second phase, allowing macrophages to acquire their final state. Adapted from 53 . Shockingly, studies on severe Coronavirus Disease (COVID19) patients have shown that pathogenic monocyte-derived macrophages that enter the lungs share a common phenotype with other populations of pathological monocyte-derived macrophages, like those found in arthritis, lupus and ulcerative colitis. These findings suggest that, in response to infection, all tissues behave in a common manner, shaping macrophages for similar responses, thus surpassing the tissue or cellular signals that determine macrophage identity in the steady state54. Introduction 24 Thus, although tissue-resident macrophages are mostly shaped by their surroundings, their different origin and epigenetic state may condition them to acquire tissue- specific functions, raising the question as to what extent development (nature) is more important than the environment (nurture). Although many cells in the organism can phagocytose (fibroblast, epithelial cells, endothelial cells), cells of the innate immune system like macrophages, neutrophils and DCs are considered as professional phagocytes55. Macrophages phagocytose invading microorganisms, mainly bacteria and fungi. Although phagocytosis can also determine subsequent lymphocyte responses, the most paradigmatic function of macrophages in homeostatic conditions is phagocytosis of apoptotic or senescent cells (efferocytosis). Macrophages eliminate cellular debris and apoptotic cells, and the relevance of this process is illustrated by the fact that millions of apoptotic cells are eliminated every day in the organism to avoid autoimmune responses and chronic inflammatory conditions55,56. The vast majority of these cells are senescent neutrophils and monocytes that continuously patrol the tissues, as well as cells that undergo apoptosis as part of safe mechanisms of the cell cycle. Numerous target molecules and phagocytic receptors (in foreign microorganisms or apoptotic cells and in macrophages, respectively) are implicated in the phagocytosis process, and the intracellular mechanisms triggered by phagocytosis are well understood (figure 4). First, “find me” signals released by apoptotic cells, or by the invaded tissue, lure macrophages57–60. Later, macrophages recognize these cells through discrete receptors and “eat me” signals that mark the target cell61–66. Once bound, phagocytic receptors initiate signaling pathways and remodeling of the cytoskeleton and lipids in the membrane. The membrane extends and covers the cell/particle, which then gets internalized in a closed structure called phagosome. The phagosome ends up fusing with intracellular lysosomes (phagolysosome), where engulfed material is destroyed trough the action of hydrolytic enzymes, an acidic environment and the production of reactive oxygen species (ROS) and nitric oxide (NO)67,68. Once the cargo is degraded, its constituent components serve as cellular fuel for generation of macromolecules or bind to Major Histocompatibility Complex (MHC or Human Leukocyte Antigen (HLA) in humans), that travels to the membrane to initiate antigen-specific adaptive immune responses69. Depending of the eliminated cargo, phagocytosis can trigger different mediators (figure 5). Phagocytosis of apoptotic cells induces macrophage to secrete antiinflammatory and resolving mediators, mainly Interleukin 10 (IL-10) and TGFβ, and alters the response of macrophages to T lymphocytes70. As a consequence, apoptotic cells have been addressed as a therapeutic target71. In phagocytosis of bacteria, macrophages release proinflammatory mediators that recruit blood cells to the tissue in order to contain and eliminate the damage, i.e., Tumor Necrosis Factor α (TNFα) and Interleukin 1 and 8 (IL-6 and IL-8). Importantly, macrophages can even distinguish between dead and live bacteria72, what determines the type of mediators that they secrete. Indeed, phagocytosis of apoptotic cells infected with bacteria triggers a mixed and complex response73. Phagocytosis constitutes not just a safeguard against accumulation of deficient cells in the tissues but also modifies the phenotype of the macrophages, imprinting heterogeneity to tissue-resident macrophages50 and influencing their metabolism74. It is also an important process in preserving the correct Introduction 25 development and activity of the organism, as it controls the synaptic pruning of neurons during brain development75 and the maintenance of the proper levels of iron in the organism76. Phagocytosis certainly illustrates and justifies one of the most important characteristics of macrophages: their heterogeneity. However, the physiological relevance of macrophages is also evidenced by a second important feature, their plasticity. Figure 4. Phases of bacterial macrophage phagocytosis. Macrophages recognize foreign bacteria through different mechanisms that ultimately reorganize their cytoskeleton and allow bacterial capture and internalization. The fusion of the endosome with lysosomes creates the phagolysosome, where bacteria are destroyed by the action of different molecules and enzymes. Molecules produced upon bacterial degradation serve as cellular fuel or bind to MHC receptors to initiate antigen presentation and adaptive immune responses. Adapted from 77 . As indicated above, one of the main characteristic of macrophages is their phenotypic and functional plasticity, as they differentially respond to distinct stimuli by rapidly changing their functional profile in a process called “polarization”78. Macrophages display a quasi- infinite spectrum of phenotypes, more appropriately called “polarization states”. These states allow macrophages to perform different tasks along the infection process or in chronic pathological conditions. To simplify the study of macrophage polarization, it is usual to focus on two polarization states at the extremes of this spectrum, namely proinflammatory and antiinflammatory macrophages, or M1 and M2 macrophages, respectively. Historically, the M1/M2 nomenclature refers to the fact that M1 macrophages predominate during T Lymphocyte Helper 1 (Th1) responses, whereas M2 macrophages prompt Th2 activity79. M1 macrophages are also known as “classically activated macrophages” whereas M2 macrophages are commonly denominated “alternatively activated macrophages”. Introduction 26 Figure 5. Phagocytosis of bacteria or apoptotic cells (efferocytosis) shows certain particularities. Among the different proteins and organelles involved in the process, the most important feature of bacteria phagocytosis is the release of proinflammatory mediators (TNFα, IL-1, IL-6), unlike phagocytosis of apoptotic cells that yield an antiinflammatory response (secretion of IL-10 and TGFβ and activation of LXR and PPAR transcription factors). Adapted from 80 . In vivo, tissue-resident macrophages can acquire a complete range of phenotypes and are continuously “flowing” between them depending on the signals that they receive81 (figure 6). M1 macrophages are similar to monocyte-derived macrophages that are recruited into the tissue under inflammatory conditions, whereas M2 macrophages mostly resemble resting tissue-resident macrophages. The shifts between M1 and M2 polarization states have been primarily investigated in vitro and this knowledge has been later applied to different in vivo situations. Since macrophages display a high heterogeneity, tissue-resident macrophages have to adapt to their unique environment and acquire specialized phenotypes. Thus, tissue macrophages can show characteristics of a mixed M1/M2 polarization, but may need to adopt an inactivated or “deactivated” state under certain conditions to prevent some undesirable actions of the specialized M1/M2 activation. Inflammatory stimuli such as Lipopolysaccharide (LPS), Toll-like Receptors (TLR) ligands and Interferon-γ (IFN-γ) induce "M1" phenotypes82,83. On the other hand, cytokines like Interleukin-4 (IL-4) or Interleukin 13 (IL-13) induced "M2" phenotypes84. These stimuli exert an ulterior activation of macrophages and so, nowadays, tissue-derived cytokines like Granulocyte Macrophage Colony-Stimulating Factor (GM-CSF) and Macrophage Colony- Stimulating Factor (M-CSF) are being used to generate resting proinflammatory (M1) and antiinflammatory (M2) macrophages, respectively85,86. Indeed, some authors propose that the macrophage nomenclature should address the triggers that determine the macrophage phenotype. For example M(IL4), M(IFNγ) for macrophages generated with IL-4 and IFNγ; or M-MØ or GM-MØ for macrophages generated with M-CSF or GM-CSF87. In vitro monocyte- Introduction 27 derived macrophages differentiate in vitro in response to M-CSF (M-MØ) or GM-CSF (GM- MØ), and this nomenclature will be used for human macrophages throughout the rest of this text. Figure 6. Macrophages display a full spectrum of phenotypes or "polarization states". Although the classic representation of this spectrum is represented above, a wider and more appropriate representation is featured below. Macrophages can adopt a plethora of polarization states that regulate inflammation and healing, thus determining tissue homeostasis. Adapted from 81 . Importantly, and related to the high plasticity of macrophages, macrophages exhibit a remarkable ability to retain memory, somewhat similar to the lymphocyte capacity in adaptive immunity. Upon a second stimulus, activated macrophages react with a more robust response in a process called trained immunity88 (figure 7). As this phenomenon is relatively new, their terminology is still quite vague, so we will use here the terminology that various authors have suggested and that covers all the possible outcomes89. Trained innate immunity is formally defined as “an initial immune response that modifies the immune response to a future exposure of an unrelated pathogen”. Within this process, the initial response of macrophages can either position them for a subsequent elevated (trained potentiation) or suppressed response (trained tolerance). In essence, trained cells do not return to their basal state after the first stimulus, but maintain the epigenetic, metabolic or transcriptional changes induced by the first stimulus, so exhibiting an increased (potentiation) or reduced (tolerance) response towards the second stimulus. The processes of differentiation and polarization could be also included in this group, as the signals that drive differentiation also condition later macrophage responses90. Many stimuli can induce trained immunity, including Bacillus Calmette-Guerin (BCG), β-glucan, oxidized low-density lipoproteins (ox-LDL), lipopolysaccharide (LPS) or hormones. Moreover, the intracellular mechanisms involved in this complex response include glucose, fatty acids and cholesterol metabolism, as well as epigenetic modifications and transcriptional changes91-104. Interestingly, other cells that don’t belong to immune system can also develop trained immunity, including endothelial cells, muscle cells or adipocytes105– 108. Introduction 28 Therefore, trained immunity represents an additional feature of macrophages that allows them to regulate tissue and cellular homeostasis, and perfectly illustrates their functional versatility. Figure 7. Macrophages develop trained immunity. Trained immunity refers to an altered response after a secondary stimulation, that can result in increased responses (trained potentiation) or decreased responses (trained tolerance). Normally, cells return to their basal state after the first stimulus, but maintain the epigenetic modifications or metabolic reprogramming triggered by the first stimulus, what conditions the macrophage response to the second challenge. Adapted from 88 . Pro- and antiinflammatory macrophages skill up in distinct functions Proinflammatory macrophages are specialized in killing pathogens and presenting antigens to T cells to initiate adaptive immune responses. They secrete proinflammatory cytokines such as TNFα, interleukin 1β (IL-1β), Interleukin 6, 12 and 23 (IL-6, IL-12, and IL- 23). Besides, proinflammatory macrophages express high levels of inducible Nitric Oxide Synthase (iNOS) that synthesize NO, which can ultimately form ROS. Proinflammatory macrophages also have a potent antitumoral activity and a deficient phagocytic activity. Conversely, antiinflammatory macrophages act mainly to resolve inflammation and in tissue maintenance and remodeling through the secretion of Insulin-like Growth Factor 1 (IGF1), TGF-β and Vascular Endothelial Growth Factor (VEGF), and express Arginase 1 (ARG1) to produce polyamines used for tissue repair. Antiinflammatory macrophages also display a high protumoral activity and exhibit a high expression of scavenger receptors and potent phagocytic activity81,109. Metabolism of nutrients differs between pro- and antiinflammatory macrophages Proinflammatory and antiinflammatory macrophages stand out for their different metabolism. Most studies on the metabolic heterogeneity of macrophages have addressed the IFNγ/LPS model of proinflammatory (M1) macrophages and the IL-4/IL-13 model of antiinflammatory (M2) macrophages, with less studies using the model of resting GM-CSF and M-CSF-differentiated macrophages (figure 8). M1 macrophage metabolism is characterized by enhanced aerobic glycolysis, converting glucose into lactate, and a truncated Krebs cycle that leads to the accumulation of succinate and citrate metabolites110. Citrate excess converts to itaconic acid, a metabolite Introduction 29 characteristic of M1 polarization111, and the accumulation of succinate leads to Hypoxia Inducible Factor 1α (HIF1α) stabilization, thus increasing glycolytic pathway through upregulation of several enzymes and IL-1β secretion112. Since Krebs cycle is truncated in M1 macrophages, the increment of lactate production and efflux regenerate the majority of the Nicotinamide Adenine Dinucleotide (NAD) needed to sustain glycolysis. Intriguingly, iron accumulation participates in this response113. Besides its role in glucose metabolism, lactate can modify DNA histones in a process called lactylation, unraveling a powerful mechanism that control macrophage gene expression and might limit excessive inflammatory responses114,115. M2 macrophages mainly produce Adenosine Triphosphate (ATP) through Krebs cycle coupled to oxidative phosphorylation (OXPHOS), that rely on fatty acid beta oxidation and produces Acetyl CoA and glutamine metabolism by anaplerotic generation of α- ketoglutarate116. The most important source of fatty acids are lipoproteins, that enter the macrophage via CD36 receptor, an important marker for M2 macrophages, and enter the mitochondria through Carnitine Palmitoyl Transferase (CPT). Glycolysis and production of lactate is much lower in M2 than in M1 macrophages. Indeed, CD36 deficient mice lack proper M2 activation116 whereas overexpression of CPT dampens inflammation117 but does not completely alters M2 polarization118. Besides, M1 macrophages have an increased flux through the pentose phosphate pathway (PPP), generating Nicotinamide Adenine Dinucleotide Phosphate (NADPH), used for the generation of the anti-oxidant glutathione (GSH) and the inflammatory mediators NO and ROS119, thus upregulating iNOS, a paradigmatic characteristic of M1 macrophages. NO inhibits mitochondrial respiration and OXPHOS112, and ROS can stabilize HIF1α and enhance glycolysis120,121. Interestingly, induced NO production and OXPHOS inhibition can prevent M1 to M2 polarization after IL-4 stimulation122 and become crucial for M1 polarization123. In the case of M2 macrophages, L-arginine is catalyzed to urea and L-ornithine through induction of the Arginase 1-encoding gene Arg1124. L-ornithine serves as precursor for L-proline production, which is used for collagen synthesis and contributes to wound repair, a key function of M2 macrophages125. Importantly, Arginine metabolism distinguish macrophage phenotypes more efficiently than glucose metabolism126. Because M2 macrophages cannot produce NO, the latter cannot block the mitochondrial proteins, thus enabling OXPHOS122. Moreover, M2 macrophages show a decreased PPP. Redox balance is crucial for M1 macrophage polarization. Accumulation of citrate can be exported by a mitochondrial carrier to the cytosol where it is cleaved back to acetyl-CoA and oxaloacetate by the enzyme ATP-Citrate Lyase (ACLY). Within the cytosol, oxaloacetate can be reduced to malate, which is converted to pyruvate by malic enzyme with production of NADPH119. NO production and citrate replenishment are maintained by the Aspartate– Arginosuccinate Shunt Pathway (AASS)127, a pathway that is upregulated in M1 macrophages. M1 polarization ensures preservation of high citrate levels, as this metabolite acts as an intermediate to many metabolites that shape the proinflammatory phenotype. Noteworthy, fatty acids synthesis is considered a characteristic property of M1 macrophages and fatty acid oxidation is considered a hallmark of M2 macrophages, but the relationship between lipid oxidation and synthesis with macrophage polarization is more complex and will be addressed later. Introduction 30 Figure 8. Polarization of macrophages determines the acquisition of opposite metabolic pathways. M1 macrophage metabolism is characterized by enhanced aerobic glycolysis, converting glucose into lactate and a truncated Krebs cycle that leads to the accumulation of succinate and citrate metabolites that ends with the conversion of arginine to citrulline and the production of NO, ROS and IL-1β. M2 metabolism is characterized by an enhanced production of ATP through an oxidative TCA cycle coupled to OXPHOS, which relies on fatty acid beta oxidation and glutamine metabolism for regeneration of mitochondrial metabolites, leading to the conversion of arginine into proline and polyamines. Adapted from 128 . Regarding M-MØ and GM-MØ, previous studies have shown that these macrophage subtypes behave similarly to those generated with IL-4/IL-13 or IFNγ/LPS, as cytoplasmic glycolytic metabolism outperforms the mitochondrial metabolism in GM-MØ while M-MØ rely mainly on mitochondrial-dependent metabolism129–131. In this sense, HIF-dependent hypoxia and prolyl hydroxylases activate glycolytic pathways that can switch M2 to M1 macrophages, in line with studies on macrophages stimulated with IFNγ/LPS129,132. The importance of arginine metabolism in M-CSF- and GM-CSF-differentiated human macrophages remain almost elusive, although it seems that the iNOS/ARG1 duality is more complex in M-MØ and GM-MØ133–135. In fact, arginine metabolic pathway in macrophages is required to ensure continual efferocytosis and inflammation resolution136. Discrete transcriptional cues control pro- and antiinflammatory polarization. Transcriptionally, traditional M1/proinflammatory polarization is characterized by activation of Signal Transducer and Activator of Transcription 1 and 2 (STAT1 and STAT2) and subsequent activation of Interferon Regulatory Factor 5 and 9 (IRF5 and IRF9)137–141. M2/antiinflammatory polarization mainly depends on STAT6/PPAR and IRF4142–147. STAT3148,149 and Nuclear factor Kappa-light-chain-enhancer of activated B cells (NFB)150,151 participate in the acquisition of both phenotypes. Moreover, HIF-1α and HIF-2α act antagonistically in terms of M1/M2 polarization152. As both phenotypes share common mediators, the interconversion between both phenotypes might be promoted by subtle changes. For example, proinflammatory cytokines like IL-6 or IL-33 also enhance the polarization of M2 macrophages153,154. M1/M2 differentiation and their interconversion is, therefore, controlled by distinct stimuli and intracellular pathways whose regulation is of utmost importance to secure their appropriate balance in physiological conditions. Notably, the whole spectrum of transcriptional molecules that control GM-MØ and M-MØ polarization are yet to be defined (Figure 10), but unlike IL-4/IL-13 macrophages, IRF4 controls GM-MØ polarization155,156. Besides, STAT5 has a role in cells stimulated with GM-CSF157 whereas Introduction 31 STAT3 rules the response of M-CSF stimulated cells158,159. Altogether, these results illustrate that M-CSF and GM-CSF can polarize macrophages by regulating a different set of factors. Phenotypically, M1 macrophages express high levels of MHCII and Class II Major Histocompatibility Complex Transactivator (CIITA) along with CD80 and CD88, CD86, cyclooxygenase 2 (COX-2), and iNOS. On the other hand, M2 macrophages express low levels of MHC-II, high levels of mannose receptor (CD206), the decoy receptor IL-1R as well as the IL-1R antagonist, CD163, CD36, Found in Inflammatory Zone (FIZZ1) protein, Macrophage Galactose-type Lectin 1 and 2 (MGL-1, MGL-2), Ym1, Matrix Metalloproteases (MMPs) and ARG1160–164. M-MØ and GM-MØ share most of these characteristics, but some markers are absent, like ARG1 or Ym1 for M2 macrophages or iNOS for M1 macrophages165–167. Of note, polarized human macrophages express unique markers that are not seen in mouse macrophages, a feature that will be commented below. The equilibrium between proinflammatory and antiinflammatory macrophages is crucial for an adequate return to homeostasis, and their misbalance contributes or collaborates to the onset and maintenance of inflammatory disorders168,169. When the damaging stimuli cannot be destroyed or phagocytosed, prolonged or excessive harm leads to tissue damage and chronic inflammation because of an exacerbated activity of proinflammatory macrophages. As an example, proinflammatory macrophages destroy the synovial membranes of the joints in Rheumatoid Arthritis (RA) causing pain and muscular injuries170,171. Conversely, and in the case of cancer, antiinflammatory macrophages promote tumoral cell growth and suppress cytotoxic response from T lymphocytes172,173. Consequently, studying the molecular and cellular mechanisms that control the differentiation and interrelation between macrophage polarization states is crucial. In fact, macrophage re- programming is being currently assessed as a possible therapeutic treatment for disorders with high inflammatory component. For example, Intravenous Immunoglobulins (IVIG) have shown their efficacy through reprogramming of macrophages174–176. Nowadays, macrophage repolarization is being assessed even as a possible strategy for COVID19177. First discovered as growth factors that control myeloid cell number from bone marrow precursors, Colony Stimulating Factors have emerged as pleotropic cytokines that control numerous macrophage functions. M-CSF (or CSF-1) is ubiquitously produced and controls macrophage numbers in many tissues, while GM-CSF (or CSF-2) has low basal circulating levels and its production requires stimulation by immune/inflammatory factors. Many cell types produce these both factors including fibroblasts, endothelial cells, stromal cells, macrophages, smooth muscle cells and osteoblasts178. M-CSF and GM-CSF receptors differ structurally and are differentially distributed on myeloid cell populations179 (figure 9). M-CSFR (CSF1R) is a homodimer with a tyrosine kinase domain whereas GM-CSFR is a heterodimer composed of a specific ligand-binding subunit (CSF2Rα) and a common signal-transduction subunit (CSF2Rβ). According with their different structure, the downstream intracellular signaling pathways from M-CSFR and GM- CSFR are different. Engagement of GM-CSFR leads to activation of Janus Kinases and STAT5 (JAK-STAT), Mitogen-Activated Protein Kinase (MAPK) and Phosphoinositide 3- Kinase (PI3K) pathways, while binding of M-CSF to M-CSFR activates PI3K and c-Jun N- terminal kinase (JNK), Protein Kinase C (PKC) and MAPK, and also activates STAT3157,159 Thus, M-CSF and GM-CSF fulfill a much wider role than mere growth factors179–181 as they Introduction 32 determinate the distinct functional features of tissue-resident macrophages. In fact, targeting GM-CSF and M-CSF has become a therapeutic treatment for inflammatory disorders and cancer182–185. Figure 9. Macrophage Colony-Stimulating Factor (M-CSF) and Granulocyte Macrophage Colony- Stimulating Factor (GM-CSF) exert their functions through different receptors. M-CSF and GM-CSF are expressed in several cells of the myeloid lineage and exert different functions, beyond acting as growth factors. The receptors for both factors show structural differences and differ in signaling capability, explaining their distinct effects on macrophages. Adapted from 186 . Figure 10. Human proinflammatory (GM-MØ) and anti-inflammatory macrophages (M-MØ) exhibit M1 and M2 macrophages characteristics. GM-CSF activates JAK-STAT and MAPK/PI3K routes to upregulate STAT5 and IRF4 and primes macrophages to acquire a proinflammatory and immunostimulatory phenotype. M- CSF regulates PI3K/JNK and PKC/MAPK pathways and skews macrophages towards an antiinflammatory and immunomodulatory state through stimulation of STAT3 and secretion of antiinflammatory and resolving mediators. GM-MØ show a more active metabolism than M-MØ, thus resembling M1 and M2 macrophages generated with traditional molecular cues. The role of other STAT factors and HIF in M-MØ and GM-MØ is yet to be defined. Introduction 33 As commented before, human monocytes differentiated into macrophages with M- CSF (M-MØ) and GM-CSF (GM-MØ) resemble M2 and M1 macrophages86,187 (figure 10) These macrophages express a unique and specific set of genes that constitute the “antiinflammatory gene set” (M-MØ) and the “proinflammatory gene set” (GM-MØ), respectively. These gene sets group the genes with the highest differential expression, |log2fold|>8, between GM-MØ and M-MØ. (figure 11). The modification of these gene sets by several stimuli reflects a change in the phenotype and functions of both macrophage subtypes, and can therefore be used to identify new pathways and molecular cues that regulate macrophage plasticity188. Interestingly, only around 20% of the genes differentially expressed between M-MØ and GM-MØ are conserved in their murine counterparts189. It is noteworthy that, in spite of their huge transcriptional differences, M-MØ and GM-MØ share most of the functional characteristics of M-CSF- and GM-CSF-dependent bone marrow- derived mouse macrophages86,189,190. On the other hand, and although M-CSF and GM-CSF trigger the acquisition of M2-like and M1-like polarization states, respectively, neither of them stimulates macrophages as potently as “traditional” macrophage-activating stimuli (IFNγ, LPS, IL-4, IL-10). Indeed, M-CSF and GM-CSF trigger the acquisition of a differentiation/polarization state in which macrophages are “primed” for a later activation, thus resembling resting tissue-resident macrophages86,187,191. Of note, while M-CSF is essential for the generation of tissue-resident macrophages in most tissues192,193, GM-CSF is absolutely required for the generation of lung alveolar macrophages194. As representative genes that define the “antiinflammatory gene set” (M-MØ) and “proinflammatory gene set” (GM-MØ), it is worth mentioning the genes encoding the serotonin (5-HT) receptors 5-HT2B (HTR2B) and 5-HT7 (HTR7) for M-MØ, and the genes encoding the lipid-presenting proteins CD1B (CD1B) and CD1A (CD1A) for GM-MØ188. Several transcription factors and molecules have been identified in recent years as regulators of human macrophage differentiation and polarization in response to M-CSF or GM-CSF. Thus, the Musculo Aponeurotic Fibrosarcoma oncogene homolog B (MAFB) has emerged as the key factor controlling the generation of antiinflammatory M-MØ and the expression of IL-10195. In fact, IL-10 dominates the gene signature of LPS-treated M-MØ196. Other member of the large MAF family, MAF (also known as c-MAF) is also decisive in M- CSF-dependent polarization197,198. In this sense, Growth Hormone (GH) production improves remission in a colitis model by a MAFB-dependent macrophage re-programming effect199. Besides, MAFB and MAF transcription factors are controlled by GSK3β activity200–203, whose activity has been also proven to be decisive for human macrophage polarization (unpublished data). Conversely, Activin A has arisen as a crucial regulator of the GM-CSF- driven proinflammatory macrophage polarization through regulation of the SMAD2/3 pathway188,204 and controls Rheumatoid Arthritis Synovial Fluid (RASF)-dependent polarization205. In fact, the expression of the transcription factor PPARγ, critical for the differentiation of alveolar macrophages, depends on both GM-CSF and Activin A39 and limits human antiinflammatory polarization206. Other factors that have been demonstrated to promote the interconversion between M-MØ and GM-MØ include palmitate207, the cytokine C-C Motif Chemokine Ligand 2 (CCL2)208, serotonin (5-HT)209–211 and Intravenous Immunoglobulins174–176. The specific transcriptomic signature of human macrophages determines their functional performance. As we stated previously, the bioenergetics profile of M-MØ differs from that of GM-MØ, as they exhibit a lower oxygen consumption rate and a weaker aerobic glycolysis129. Indeed, the antigen-presentation and antitumoral capabilities of GM-MØ are Introduction 34 stronger than their M-MØ siblings159,175. In basal conditions, GM-MØ stand out for secretion of IFN-β and Activin A, whereas M-MØ mostly produce CCL2 and CCL8. Importantly, LPS- activated GM-MØ produce high levels of proinflammatory cytokines, like TNF-α, IL-6, IL1β or IL-23, whereas LPS-activated M-MØ produce high levels of IL-10188,204. In this sense, LPS-M- MØ, but not LPS-treated GM-MØ, secretes the chemokine CCL19196. Therefore, TNFα and IL-10 are usually considered as the gold standard cytokines for GM-MØ and M-MØ, respectively. Figure 11. Human monocyte-derived proinflammatory GM-MØ and antiinflammatory M-MØ acquire particular features through expression and regulation of distinct molecular cues. GM-CSF promotes the generation of monocyte-derived proinflammatory GM-MØ, which are defined by the expression of the “proinflammatory gene set” including genes like INHBA, EGLN3, MMP12, CCR2, PPARG, CCL17 or CLEC5A. On the other hand, M-CSF induces monocyte-derived antiinflammatory M-MØ, characterized by the expression of the “anti-inflammatory gene set”, represented by genes like MAFB, MAF, IGF1, FOLR2, CD209 or HTR2B. Activin A and PPARγ regulate the response of GM-CSF-treated monocytes whereas MAFB and MAF control monocyte response to M-CSF. Serotonin and CCL2, as well intravenous immunoglobulins, can trigger the interconversion between GM-MØ and M-MØ. *The involvement of LXR and AhR in the generation of both macrophage subtypes is described in the present work. All the functional differences between macrophage polarization states illustrate the importance of dissecting human macrophage polarization as a means to assess their contribution to the diverse range of diseases where macrophages display a pathogenic role (autoimmune diseases, neurodegenerative disorders, cancer, atherosclerosis). Nuclear receptors uclear receptors constitute a large family of transcription factors that regulate cell metabolism, differentiation, activation and death212. The smorgasbord of factors of this family belongs to different classes depending on their mode of action and their monomeric or dimeric state but all of them share a common structural component (figure 12). Some specificities aside, all nuclear receptor family members contain a variable N- Terminal Domain (NTD), a DNA Binding Domain (DBD), a hinge region, a conserved Ligand- Binding Domain (LBD), and a variable C-terminal domain213. In the present work, we will N Introduction 35 focus on the part of the family that forms heterodimers with Retinoid X Receptors and in particular, Liver X Receptors or LXR. Figure 12. The structure of nuclear receptors is conserved. Nuclear receptors share a common structure: a variable N-terminal domain (NTD), a DNA binding domain (DBD), a hinge region, a conserved ligand- binding domain (LBD), and a variable C-terminal domain. A plethora of physiological molecules, as bile acids or oxysterols, or synthetic ligands, can bind to the LBD and activate nuclear receptors. Adapted from 214 . Liver X Receptors (LXR) he Liver X Receptors, or LXR, first discovered in hepatic cells, are nuclear transcription factors crucial for the proper performance of the organism. The LXR family is composed of two members: LXRα (NR1H3 gene) and LXRβ (NR1H2 gene), coded by two different genes located in different chromosomes but that share a high sequence similarity (around 75%). LXRα predominates in high metabolic tissues like liver, adipose tissue, intestine or macrophages. By contrast, LXRβ is ubiquitously expressed215–217. In mouse macrophages, LXRα is mainly expressed in liver, splenic and bone marrow macrophages while LXRβ is expressed in all mouse macrophages75. In human macrophages, LXRα exists in at least five alternatively spliced isoforms whose expression varies among tissues218,219, albeit some of them are marginal (LXRα4 and LXRα5). Whether any of the alternatively spliced isoforms fulfill a specific role remains to be elucidated. Elegant studies have discovered that LXRα and LXRβ show many genomic and metabolic differences, uncovering possible mechanisms that may allow pharmacological distinction of both proteins220. In this sense, the identification of LXR protein-specific functions has been previously approached221–224 but they appear to reflect the preferential expression of either LXR protein in certain tissues. Furthermore, LXR activity is increased in macrophages from various pathological conditions, like rheumatoid arthritris225 or cancer226. Synovial macrophages from Rheumatoid Arthritis show a high LXR activity and LXR arise as the most upregulated pathway in these macrophages compared to monocytes225. Moreover, the LXR pathway has been identified as the most enriched pathway in colorectal liver metastasis “large tumor-associated macrophages” (large TAM)226. On top of that, LXRα is upregulated along the monocyte-to-macrophage transition in human macrophages differentiated with GM- CSF or M-CSF227. LXR are ligand-activated transcription factors that respond to a variety of ligands, either endogenous or synthetic. Their canonical ligands are oxysterols, oxidized forms of cholesterol, that include 20(S)-, 22(R)-, 24(S)-, 25- and 27-hydroxy cholesterol, 24(S), 25- epoxycholesterol and 24-dehydrocholesterol (desmosterol)228–230. Several synthetic agonists have been developed (GW3965231 and T0901317232) that differ in their specificity, as high concentrations of T0901317 also activate Farnesoid X Receptors (FXR) while GW3965 does not233,234. Endogenous antagonists for LXR, like Arachidonic acid, also exist, and they block subsequent agonist activity235. Synthetic inverse agonists like GSK2033236 and SR9238237 have been developed and they are capable of reducing LXR transcription on their own. T Introduction 36 Intriguingly, GSK2033 has been shown to display specific functions in macrophages but not on hepatocytes238. As we previously noted, LXR form obligated heterodimers with Retinoid X Receptor (RXR), a feature shared by other nuclear receptors of the family like FXR or the Retinoid Acid Receptor (RAR)239 (figure 13). LXR bind to DNA constitutively through recognition of LXRE elements composed of a consensus sequence separated by any four nucleotides (DR4), AGGTCAnnnnAGGTCA, and whose sequence vary depending on the gene240. In the basal state, corepressors are bound to LXR-RXR heterodimers, hindering LXR-dependent transcription. LXR known corepressors include Nuclear Receptor Corepressor 1 (NCoR1) and Silencing Mediator of Retinoic acid and Thyroid hormone receptor (SMRT)241. When agonists reach the heterodimer, a conformational change allows the recruitment of coactivators and subsequent LXR-dependent transcription. LXR can also associate with many coactivators like Nuclear Receptor Co-Activator 1 (NCOA1), Activating Signal Co- integrator 2 (ASC2), Small Heterodimer Partner (SHP) or Cell Death-Inducing DNA fragmentation factor-α-like Effector A (CIDEA), depending of the cell type242–245. Interestingly, either LXR agonist or RXR agonist (9-cis-retinoic acid) can activate transcription, and this activation is synergic when both ligands are present215,217. Figure 13. LXR-dependent transactivation of DNA is regulated by corepressors and coactivators. Corepressors impede LXR-mediated transcription in basal conditions, while the presence of an LXR ligand, either physiological (oxysterols) or synthetic (GW3965), induces a conformational change of the heterodimer that allows coactivators to be recruited and LXR target genes to be expressed. Adapted from 214 . Numerous mechanisms regulate LXR activation and transcription and these differ between mouse and humans. In human macrophages, LXRα is autoregulated, as its gene promoter contains LXR elements that allow a strong response to LXR agonists246. In mouse hepatic cells, LXR can be recruited de novo to certain elements in response to agonists247. LXR activity can also be regulated by the presence of several non-coding RNA and microRNA248–251. Activation of LXR is also regulated by posttranslational modifications, including phosphorylation252–255, acetylation256, SUMOylation257–259 or ubiquitination260 and, in a particular case, even OGlcNacylation261. LXR nuclear receptors govern cholesterol metabolism through the regulation of different genes that control cholesterol absorption, transport and efflux in adipose tissue, intestine, liver and macrophages262,263 (figure 14). When intracellular cholesterol rises, in a phagocytosis scenario or in feeding conditions, the enzymes that metabolize cholesterol are activated and oxysterols are generated. Oxysterols activate LXR-RXR heterodimers to compensate for the high levels of cholesterol and to avoid autoimmune responses. The principal LXR target genes under these conditions encode for proteins of the ATP-Binding Cassettes (ABC subfamily A and ABC subfamily G) family, namely ABCA1, ubiquitously expressed, and ABCG1, preferentially Introduction 37 expressed in macrophages and hepatic cells. Both ABCA1 and ABCG1 limit cholesterol accumulation by outflowing it out of the cell 264–267. Once released, cholesterol is rapidly captured by blood lipoproteins and converted into cholesterol esters that travel to different tissues to feed them or to the liver, where it will be converted into bile acids to eliminate its excess. LXR contribute to all these processes, as they regulate the transcription of genes encoding: 1) apolipoproteins (ApoC1, C2, C3, C4, ApoD, ApoE268–271) that are present on the surface of lipoproteins; 2) the enzymes Niemann– Pick C1 and C2 (NPC1 and NPC2)272 that mediate esterification of cholesterol; 3) the hepatic enzymes of the Cytochrome P450 (CYP) family (CYP7A1273,274) that regulate bile acid generation; 4) the Lipoprotein Lipase (LPL275), present in blood vessels and the membrane of the cells to capture cholesterol from lipoproteins into the tissues; 5) the Increased Degradation of LDL Receptor (IDOL or MYLIP) enzyme276 that contributes to Low Density Lipoprotein Receptor (LDLR) elimination, thus limiting capture of cholesterol from the tissues; and 6) Phospholipid Transfer Protein (PLTP)277,278 and Cholesteryl Ester Transfer Protein (CETP)279,280 that exchange cholesterol from different lipoproteins. Besides, in intestine, LXR control the expression of carrier Niemann-Pick C1-Like 1 (NPC1L1)281 and heterodimeric ABCG5/ABCG8282 that limit cholesterol absorption from the diet. Therefore, LXR regulate cholesterol transport, metabolism and excretion. However, LXR have also great importance in the control of lipid metabolism, and in particular in lipid synthesis. Experiments in mice have revealed that LXR control the expression of the Sterol Regulatory Element Binding Protein-1c (SREBP1c)283 and Carbohydrate Response-Element Binding Protein (ChREBP)284 that are the major regulators of lipid synthesis in hepatic cells. In this regard, LXR also regulate expression of Fatty Acid Synthase (FASN)285, the multicomplex enzyme that synthesize fatty acids, and other proteins like the Sterol CoAcyl Desaturase (SCD)286,287, the Acetyl CoA carboxylase (ACC or ACACA in humans)288 and even the Lysophospholipid Acyltransferase 3 (LPCAT3)289, that administers intracellular lipid metabolism and reduces endoplasmic reticulum stress. A complete panel of previously reported LXR target genes in mouse and human cells is listed in Table 2. For all these reasons, LXR activity has been related to multiple pathologies like atherosclerosis or non-alcoholic fatty liver290,291. Experiments with Wild type (WT) and Lxr KO mice models have revealed that LXR have both anti/pro-atherosclerotic effects, and that LXR also contribute to macrophage immune behavior292. These anti/proinflammatory effects led to the search for LXR agonists that limit lipid biosynthesis while promoting cholesterol efflux and to dissect the role of LXR in immune functions. Introduction 38 Figure 14. LXR control all phases of cholesterol homeostasis. LXR factors regulate a smorgasbord of proteins that control cholesterol transport, metabolism and excretion, exerting an intimate communication between liver, intestine, gall bladder, adipose tissue and macrophages. LXR control absorption of dietary cholesterol in the intestine, regulating transport from the intestine lumen (NP1CL1) or excretion of the excess back to the lumen (ABC). This cholesterol binds to apoproteins and nascent lipoproteins to form mature high- density lipoproteins (HDL). LXR control efflux of cholesterol from macrophages to lipoproteins through ABC transporters, regulating reverse cholesterol transport. These lipoproteins reach the hepatic tissue and transform into bile acids that enter the gall bladder through ABCG transporters and other LXR-regulated enzymes like CYP7A1. In the liver, LXR also regulate synthesis of fatty acids through their targets SREBP1c and ChREBP. Moreover, LXR regulation of ABC transporters starts over the reverse cholesterol transport. IDOL protein, whose expression depends on LXR, dampens uptake of cholesterol from lipoproteins to the tissues. Adapted from 263 . LXR also control immune performance of macrophages and novel functions regarding the involvement of LXR in immune homeostasis are continuously emerging. The vast majority of studies performed on macrophages have evidenced an anti-inflammatory action of LXR (figure 15 A, B). Activation of LXR impedes transcription of numerous proinflammatory mediators (IL-1β, IL-6, iNOS or COX2) in activated macrophages and also limits Metaloproteinase-9 (MMP9) secretion by inhibiting NFkB293,294, thus revealing the existence of an indirect LXR-dependent mechanism to control gene transcription. Several mechanism have been reported that could explain these effects, including SUMOylation of LXR receptors and blocking of corepressors from proinflammatory genes258. A recent study evidenced that LXR can also limit inflammation through cholesterol efflux and through Activator Protein 1 (AP1)-independent suppression of inflammatory genes295. LXR can also exert antiinflammatory actions by changes in lipid metabolism that affect TLR/Myd88 signaling296 or impeding maturation of proinflammatory cytokines like IL18 Introduction 39 or IL1β297 and secretion of TNFα and IL-1α298. Accordingly, LXR agonists suppress tissue factor (TF) and induced TNFα expression299,300. In human monocytes, LXR preactivation suppresses the secretion of many inflammatory mediators in response to LPS challenge301. In this sense, TNFα treatment of human macrophages increases LXR expression, possibly in a loop of autoregulation to dampen inflammation associated with high levels of TNFα225. Also, TLR activation by bacterial antigens blocks LXR expression and affects cholesterol efflux from mouse macrophages302. Moreover, LXR exert antiinflammatory actions through regulation of apoptotic cell phagocytosis by induction of Mer Tyrosine Kinase (MERTK) receptor303 (figure 15C). Phagocytosis of apoptotic cells induces a macrophage antiinflammatory phenotype characterized by expression of TGFβ and IL-10. This mechanism is of utmost importance, as LXR agonists reduce inflammation and improve prognosis in murine models of lupus303. The LXR-dependent regulation of IL17 and T Lymphocyte 17 (Th17) polarization also helps limiting autoimmunity in Multiple Sclerosis mice models304 and in controlling macrophage- related lung inflammation305. LXR antiinflammatory action is also notable upon infection of Listeria monocytogenes since their absence leads to accelerated macrophage apoptosis and defective bacterial clearance through direct regulation of Apoptosis Inhibitor of Macrophage (AIM, also known as CD5L) that is crucial for macrophage survival306. In fact, this is detrimental in atherosclerosis, as LXR promote survival of foam cells in a MAFB-dependent manner307. Besides, LXR limit Salmonella infection of macrophages controlling CD38 and NAD abundance, what impairs cellular cytoskeleton assembly308. Conversely, a role for LXR in proinflammatory pathways has started to be considered, especially in human cells (figure 15 D, E). Thus, LXR potentiate cytokine production after TLR activation in human macrophages and increase the expression of TLR4, an LXR gene target only in human cells225,309. ROS production and expression of NADPH oxidase can be also augmented by LXR agonist treatment. In DCs, LXR preactivation also increases proinflammatory cytokine secretion after TLR stimulation and induces macrophage-derived T lymphocyte proliferation310. In collaboration with HIF1α, LXR activation impulses IL1β secretion in human macrophages, without an increase in TNFα secretion311. Moreover, LXR activation enhances the glycolytic pathway only in human macrophages. Regarding this effect, LXR also boost cytokine secretion in human monocytes by a mechanism resembling "training potentiation" that might explain all these previous findings312. In fact, all LXR- mediated proinflammatory effects are observed after a long exposure to LXR agonists (>48 hours). Additionally, the LXR-HIF1α axis contributes to the generation of foam cells and atherosclerosis in hypoxic conditions313 and LXR also favor DCs chemotaxis314. Regarding macrophages, the involvement of LXR in macrophage polarization is still poorly understood, as only a few studies in mice have related the LXR pathway to the macrophage phenotype315,316. Introduction 40 Figure 15. LXR wield antiinflammatory and proinflammatory effects in macrophages. A. A short pretreatment with LXR agonist dampens inflammation caused by inflammatory stimuli. In the monomeric state, LXR block transcription of NFkB and therefore proinflammatory gene expression. Several processes govern these effects but SUMOylation of LXR and a change of conformation that allows them to inhibit transcription without RXR dimer is the most feasible mechanism. B. Bacterial infection of macrophages activates LXR and promotes transcription of AIM and other antiapoptotic genes while diminishes transcription of proapoptotic genes, thus leading to greater survival of macrophages and rapid elimination of bacteria. LXR depletion promotes macrophage death by increasing bacterial number and tissue damage. C. Phagocytosis of apoptotic cells activates LXR by unknown mechanisms and primes macrophages to acquire a more antiinflammatory state, characteristic of a greater production of TGFβ and IL-10 and a lower production of TNFα and IL-1β. LXR contribute to this switch by increasing MerTK expression that impulses phagocytosis of apoptotic cells. D. Long pretreatment (>48h) with LXR agonist boosts TLR response of macrophages and increase secretion of ROS and a variety of proinflammatory cytokines. LXR activation also increases TLR4 expression. These proinflammatory effects might be explained by a LXR-mediated trained potentiation on macrophages. E. Long pretreatment (>48h) with LXR agonist augments secretion of IL1β and intracellular glycolysis through a HIF1α-dependent mechanism that involves ROS and NFkB. Interestingly, the proinflammatory effects are only seen in human macrophages. LXR activity is thoroughly regulated by intracellular cholesterol levels and their interplay with Sterol Regulatory Element Binding Proteins (SREBPs). SREBPs present three Introduction 41 major isoforms, SREBP1a, SREBP1c and SREBP2, coded by two genes, SREBF1 and SREBF2317,318. SREBP1a expression is ubiquitous while SREBP1c and SREBP2 are expressed primarily in adipose tissue, liver and macrophages319. Besides, SREBP1a expression is higher in macrophages than SREBP1c320. The three members of the family share a similar structure, composed of an amino-terminal transcription factor domain, a middle hydrophobic region containing two hydrophobic transmembrane segments and a carboxy-terminal regulatory domain317,318. Differences in the amino terminal section of three isoforms makes SREBP1c a weaker transcriptional activator than SREBP1a or SREBP2321, although SREBP1c and SREBP2 are inducible and their abundance increases upon different stimulus while SREBP1a is normally present at low levels319. Although there is some crosstalk between both isoforms, SREBP1c primarily targets genes that synthetize fatty acids and SREBP2 primarily upregulates genes that code for the enzymes involved in cholesterol biosynthesis (figure 16). SREBP1a can drive both pathways in all tissues. SREBP1 target genes include ACC, FASN, ACLY, SCD and the gene encoding glycerol-3-phosphate acyltransferase (GPAT3). SREBP2 regulates the genes that code for Hydroxymethylglutaryl-CoA synthase (HMGCS) and Hydroxymethylglutaryl-CoA reductase (HMGCR), farnesyl diphosphate synthase (FDPS), squalene synthase (SQLE), mevalonate kinase (MVK), 24-Dehydrocholesterol reductase (DHCR24) and 7-dehydrocholesterol reductase (DHCR7), as well as LDLR322–325. Figure 16. Scheme of the SREBP-regulated metabolic pathways. SREBP2 controls several enzymes that convert Acetyl CoA in cholesterol, which has inhibitory effects on SREBP2. SREBP1 regulates enzymes that lead to generation of Acetyl CoA-derived fatty acids, which exert a positive loop on SREBP1. The control of the opposite route by either SREBP1 or SREBP2 is less effective. In order to be fully functional, SREBPs must be cleaved to release their active form, which subsequently enters the nucleus and activates transcription in a highly regulated process326,327 (figure 17). SREBPs remain in the Endoplasmic Reticulum (ER) forming a complex with Insulin-Induced Genes (INSIG1 and INSIG2) and SREBP Cleavage-Activating Protein (SCAP). When the levels of cellular cholesterol are high, INSIGs become stable and allow the SCAP-SREBP complex to remain in the ER. However, when the levels of sterols decrease, INSIGs are ubiquitinated and rapidly degraded, triggering the transport of SCAP- SREBP complex from the ER to Golgi Apparatus, where SREBPs are consecutively cleaved by the membrane proteases Site-1 Protease (S1P) and Site-2 Protease (S2P). Then, cleaved SREBPs release the transcriptionally active NH2-terminal domains that enter into the nucleus and induce target gene expression328. Additional studies suggest that SREBP1 may be regulated in additional manners, and that regulation of SREBP1, unlike that of SREBP2, Introduction 42 is more dependent of unsaturated fatty acids content than cholesterol329. Indeed, SREBPs are regulated by intracellular and extracellular metabolites as well as by different hormones that control feeding and starvation330–334. This regulation is so intricate that even in absence of these lipid master regulators, the organism can maintain reasonable levels of these essential molecules335,336. Figure 17. SREBPs are activated by sequential proteolytic cleavages that liberate the active N- terminal domain. SREBPs remain in the endoplasmic reticulum bound to INSIG and SCAP proteins. When the intracellular levels of cholesterol increase, the INSIG-SCAP complex separates releasing the SCAP-SREBP complex that travels to the Golgi apparatus. There, SP1 and SP2 proteases cleave SREBP proteins releasing their N-terminal domain that travels to the nucleus binding to SRE and starting transcription of their target genes. INSIG proteins are not represented in the image to simplify the cleavage mechanisms. Adapted from 337 . The expression of SREBP and LXR is also inter-related. In this regard, the cholesterol-dependent regulation of SREBPs is very relevant because the cholesterol levels also regulate LXR activity and function (figure 18). In fact, it is noticeable that both transcription factors share some common target genes. Under conditions of low cholesterol, SREBPs are processed and bind to sterol-response elements in genes encoding enzymes required for the synthesis and uptake of cholesterol. Under cholesterol excess, SREBP precursors are sequestered in the endoplasmic reticulum and active LXR-RXR heterodimers recruit coactivators and upregulate proteins that mediate cholesterol efflux and degradation of LDLR, decreasing intracellular concentrations of cholesterol338. Moreover, it has been recently discovered that LXRα negatively regulates the genes that encode squalene synthase (FDFT1) and lanosterol 14α-demethylase (CYP51A1), key enzymes in the cholesterol biosynthesis pathway339. Therefore, the interplay between LXR and SREBP is intimate, considering that SREBF1 (SREBP1c) is also a LXR target gene283. This is of special importance as LXR agonists, and in particular the widely used synthetic agonists GW3965 and T0901317, activate LXR and SREBP1c, what results in a marked increase in fatty-acid biosynthesis232,340. Moreover, LXR activation in SREBP1c deficient animals does not impede upregulation of fatty acid synthesis341, illustrating that there are ulterior mechanisms that regulate this process independently of SREBP. The crosstalk between both transcription Introduction 43 factors is also implicated in Poly-Unsaturated Fatty Acids (PUFAs) and Arachidonic Acid342. In summary, activation of LXR leads to efflux of cholesterol and fatty acid generation through SREBP1, while diminished cholesterol levels promote intracellular cholesterol biosynthesis via SREBP2 activation. Considering these antecedents, the existence of ligands that activates LXR while inhibiting SREBP has been addressed. Studies in cholesterol loading cells and foam cells have shown that natural ligands of LXR activate their targets while blocking SREBP1c signaling, and that the most abundant ligand upon cholesterol loading was desmosterol. Desmosterol, and synthetic analogous like N, N-dimethyl-3β-hydroxy-cholenamide (DMHCA), showed bright expectations in hepatic pathologic conditions and also in the study of the role of LXR under basal conditions343–348. Accordingly, D. Muse et al. defined gene sets including the genes that are upregulated and downregulated by desmosterol, respectively, and that correspond to LXR-dependent and SREBP-dependent gene sets. Consequently, desmosterol has become one of the most promising LXR ligands for therapeutics. However, its weaker LXR activation potency, compared to GW3965 or T0901317, has been a drawback for its therapeutic use. Recently, encapsulation of a synthetic agonist like T0901317 limited atherosclerosis without hepatic affectation349. Interestingly, during later stages of the TLR response, LXR are necessary for an increase in sterol synthesis and this implication intersects with the control of lipogenesis by the mammalian target of rapamycin (mTOR)350. Figure 18. Intracellular cholesterol levels regulate LXR/SREBP crosstalk. In low-cholesterol situations, the absence of oxysterols keeps LXR repressed while favors SREBP transcription. In this setup, cholesterol levels rise and transform to oxysterols that activate LXR and repress SREBP transcription, rapidly flowing out the cell the excess of cholesterol. Adapted from 351 . The interrelation between lipids, cholesterol and inflammation is very sophisticated. Fatty acids govern the inflammatory responses in obesity and liver disease, and most studies have addressed their role in these diseases as a whole, integrating adipose tissue, liver and pancreas signals352–354. In general, they are precursors of a diverse range of molecules and metabolites, specially prostaglandins, leukotrienes and thromboxanes355,356 that mediate Introduction 44 inflammation. Saturated fatty acids trigger a pro-inflammatory response through TLR4 receptor, and polyunsaturated fatty acids employ G protein-coupled receptor 120 (GPR120) to induce an antiinflammatory signaling cascade357. In terms of macrophage response and polarization, their implication is quite vague. According to previous experiments, saturated fatty acids induce M1 proinflammatory polarization while polyunsaturated fatty acids favor M2 antiinflammatory phenotype, with participation of the transcription factor PPARγ358. A few studies have shown that fatty acids can upregulate TLRs in macrophages in vitro and in Kupffer cells, where captured lipoproteins polarize them into proinflammatory macrophages and induce secretion of inflammatory mediators (TNFα, CCL2, IL-1β)359,360. In fact, the levels of two targets of SREBP signaling that belong to fatty acid cascade, ACLY and FASN, are important for M1 macrophage activation. Increased ACLY expression was found in activated M1 macrophages, and the silencing of ACLY was sufficient to reduce the expression of inflammatory mediators361 while FASN deletion prevented macrophage recruitment and inflammatory response in diabetic mice362. Accordingly, M2 macrophages rely on fatty acid oxidation, and blockade of this pathway impedes M2 polarization116,363. However, there is some controversy since M-CSF-driven differentiation of antiinflammatory M-MØ upregulates SREBP1 that increases lipid synthesis364, while previous studies associating fatty acids synthesis with proinflammatory polarization were performed in LPS-activated macrophages365. Consequently, further studies are needed to completely clarify their role in macrophage polarization. The SREBPs implication in inflammation and immune response has started to be addressed in the recent years, especially because SREBPs can control inflammation without fatty acids or cholesterol involvement. SREBP1 is necessary for response to LPS366 and inflammasome formation320,367,368, both linked to M1 polarization, as well as for upregulation of antiapoptotic factors upon bacterial challenge369, which resembles the LXR-dependent activation of AIM in foam cell formation. Nevertheless, recent studies revealed SREBP1 is necessary for macrophage resolving capacities during later stages of TLR activation370 and, as we said before, for the M-CSF-dependent differentiation of human monocytes364. Interestingly, most of these effects are mediated by SREP1a, not regulated by LXR, and its capability to activate both SREBP1c and SREBP2 target genes. The most recent studies link SREBP2 signaling to augmented TNF-induced macrophage activation and impaired wound repair. Interestingly, these effects are independent of cholesterol biosynthesis, a process strictly regulated by SREBP2371. Besides, the SCAP-SREBP2 complex is also capable of regulating inflammasome activation372, demonstrating that SREBP1 and SREBP2 also regulate inflammation through this mechanism. The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor that regulates the xenobiotic detoxifying response and other cellular processes through its ability to initiate ligand-, cell-type- and context-specific transcriptional programs in response to exogenous and endogenous ligands373,374. AhR is a member of the large basic-Helix-Loop-Helix (bHLH) PAS family (figure 19). AhR includes a bHLH domain, implicated in DNA binding and protein dimerization, a Q-rich domain, responsible for transcriptional activation and two PER–ARNT–SIM (PAS) domains, that are named after three proteins of the same family, period circadian protein (PER), AhR nuclear translocator (ARNT), and single-minded protein (SIM), originally described in Introduction 45 Drosophila375,376. These domains can sense endogenous (such as oxygen tension or redox potential) and exogenous factors (such as polyaromatic hydrocarbons and environmental toxins). Figure 19. The Aryl Hydrocarbon Receptor (AhR) belongs to a large family of bHLH PAS transcription factors. AhR presents two PAS domains that are important for dimerization and interaction with Hsp90 chaperones, a Q-rich domain implicated in transactivation and a bHLH domain that binds to DNA. Adapted from 373 . AhR is normally present in the cytoplasm forming a complex with the Heat shock protein (Hsp90), the cochaperone p23, the AhR-interacting protein (AIP; also named as XAP2) and the protein kinase SRC (figure 20). The interaction of AhR with these proteins allows AhR to be in a conformation of maximal affinity for ligands and minimal affinity for DNA, stabilizes the receptor in the cytoplasm, prevents its nuclear translocation and avoids proteasomal degradation of the receptor377,378,387,379–386. After ligand binding to the PAS domains, AIP is released from the complex, which then travels to and enters the nucleus via importins388. There, conformational changes result in AhR release and its heterodimerization with AhR nuclear translocator (ARNT) and later binding to AhR response elements (XRE, from Xenobiotic Response Elements or DRE, Dioxin Response Elements) that contain a DNA consensus motif (5ʹ-TNGCGTG-3ʹ)389,390. AhR activates transcription of numerous genes including proteins of the p450 cytochrome family (CYP), CYP1B1, CYP1A1, CYP1A2 and other genes like AhRR, IL-17 or TIPARP. AhR-dependent transcription is controlled at several levels, including nuclear translocation of the receptor388,391, ubiquitination and proteasomal degradation via the cytoplasmic proteasome392,393, competition with AHR repressor (AHRR)394, availability and degradation of the ligands by CYP1 proteins395, and even ADP-ribosilation396. HIF1α has also been shown to compete with AHR for its interaction with ARNT. In addition, non-transcriptional activities of AhR397 or even ligand-independent actions398 have also been described over the years. AhR ligands comprise a large family of molecules with high-affinity for AhR399,400. The most studied ligands for AhR are dioxins, polychlorinated biphenyls (PCBs) and other environmental contaminants, with 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) being the most representative member of this family. Besides, AhR has additional canonical and endogenous ligands, most of them derived from Tryptophan metabolism or microbiota- derived, including kynurenines and 6-formylindolo[3,2-b]carbazole (FICZ), which has a similar affinity for AhR as TCDD. Arachidonic acid and other prostaglandins are also potent endogenous ligands for AhR401. The most important difference between prototypical FICZ and TCDD agonists is their susceptibility to degradation by CYP proteins, which are capable of degrading FICZ but not TCDD. Consequently, AhR is considered as highly promiscuous. Interestingly, some authors considered that certain proposed agonists are really CYP enzymes inhibitors which increase the half-life of endogenous agonists402. Of note, very Introduction 46 recent studies have shown that Vitamin B12 and folic acid are endogenous inhibitors of AhR function403. Figure 20. Aryl Hydrocarbon Receptor (AhR) structure and its activation/inactivation. In ligand-absence conditions, AhR forms an inactive complex with HSP90, p23, AIP and SRC proteins in the cytoplasm. When a ligand enters the cell, binding to this complex cause a conformational change that results in the translocation of the complex to the nucleus. Once there, AhR is dissociated from the complex and heterodimerizes with ARNT and binds to AhR response elements (XRE), provoking gene transcription. The abundance of active AhR is controlled by its repressor, AHRR, which competes with ARNT for heterodimerization with AhR. Besides, ligands are rapidly metabolized and AhR can be degraded in the proteasome by a ubiquitination-dependent mechanism. Adapted from 374 . Experiments performed in mice lacking AhR or carrying AhR defective proteins have revealed multiple functions of AhR in immune cells and in inflammatory conditions and disorders. Moreover, the commercially available cornucopia of agonists and antagonists for AhR permit a feasible modulation of their activity in multiple models or cell lines, especially through the use of ligands that avoid AhR-dependent elimination. Given the large variety of exogenous and endogenous ligands, most studies on AhR have focused on the use of inhibitors. AhR is considered the master regulator of Th17 differentiation. AhR is upregulated in Th17 cells, boosts IL-17 and IL-22 production404,405 and impulses human Th17 differentiation406. AhR also promotes T regulatory (Treg) lymphocytes differentiation in humans407. Surprisingly, an AhR- and RORγt-positive T cell subset that produces IL-22, but not IL-17 or IFN-γ, has been identified in humans408. AhR also controls DCs and macrophages behavior where most results have linked antiinflammatory consequences with AhR activation and proinflammatory actions with AhR inactivation. AhR signaling in differentiated DCs decreases proinflammatory T cell polarization while favoring antiinflammatory T reg cells409,410. However, proinflammatory actions derived from AhR activation by TCDD in naive DCs have also been described411 Introduction 47 whereas AhR inactivation induces differentiation of CD34 cells to conventional and plasmacytoid DCs, that promote proinflammatory T cells412. In other studies, AhR inactivation impedes monocyte differentiation to Langerhans dendritic cells413 and AhR activation has been shown to control monocyte to DCs differentiation through IRF4 and B lymphocyte- induced maturation protein 1 (BLIMP1)414. Besides, AhR can interact with the promoters of many transcription factors that are related to macrophage cytokine production415. Importantly, AhR participates in the negative regulation of proinflammatory gene expression of tumor- associated macrophages416,417 and tissue-resident macrophages418,419. AhR promotes IL-10 production in AhR-overexpressing cell lines and limits IL-6 expression and production in LPS-activated macrophages420–422. AhR hinder activation of human macrophages423 but cooperates with other factors in TNFα and IL-33 production424,425. Curiously, AhR activation by benzopyrene alters inflammatory state of bone marrow-derived macrophages426,427. AhR also regulates murine macrophage polarization in a mixed way, as its absence affects characteristics of pro- and antiinflammatory macrophages, whereas AhR has a not yet clear role in human macrophage polarization428,429. Up to date, no clear relation has been established between AhR and LXR. However, AhR activation has been related to liver fibrosis and inflammation in different directions430–434 that were associated with lipids accumulation in the liver. AhR activation increase cholesterol uptake and diminish cholesterol-related lipoproteins in mice435,436 and increase HMGCR expression437,438 in livers of AhR KO mice. Curiously, in a AhR-depleted human cell line, LXR activation decreases cholesterol secretion but not cholesterol biosynthetic genes437. In experiments with human intestinal cells, AhR represses NP1CL1 and other cholesterol biosynthetic genes by induction of SREBP2 proteolytic degradation in a calcium-dependent manner439. On the other hand, LXR regulate CYP1A1 and CYP1A2, paradigmatic AhR target genes, in human hepatocytes435 and controls Th17 and Treg differentiation in mouse and humans304,440. In this regard, LXR agonism ameliorates EAE by inhibiting Th17-related genes and specifically IL-17 through a mechanism of upregulation of SREBP1, that physically interacts with AhR to impede its binding to IL-17 promoter. Importantly, there is no described direct relation between AhR and LXR in macrophages. Macrophages constitute perfect targets for treatment of inflammatory disorders s principal effectors of the innate immune response, macrophages orchestrate or contribute to disorders with immunological components, including metabolically- dependent diseases (diabetes, atherosclerosis), autoimmune diseases, neurodegenerative and bone disorders, chronic inflammatory diseases (arthritis), and cancer6,441–445. Besides, macrophage polarization, and thus its implication in the above mentioned diseases, is influenced by sex differences, as several studies have already suggested that females present higher macrophage-related antiinflammatory responses445– 447. In this regard, elegant studies identified estrogens as the underlying factors for sex- dependent macrophage responses because macrophage antiinflammatory M2 polarization is enhanced upon activation of estrogen signaling448–451. This could be of special interest since the incidence of some diseases is biased between sexes452–454. Here, we summarize the role of macrophages in cancer and rheumatoid arthritis, the diseases most directly related to the work described in this study. A Introduction 48 Cancer comprises a huge variety of diseases characterized by exacerbated cell proliferation. The tumor microenvironment creates a hermetic niche that is perfectly suited for cancer cells to grow under hypoxic conditions and to evade anti-tumor immune responses. The tumor microenvironment includes cancer cells, fibroblasts, endothelial cells and immune cells, mainly lymphocytes and macrophages, commonly known as tumor associated macrophages (TAM)456,457. Some TAMs originate from monocytes recruited from peripheral blood by chemokines secreted by tumor cells and other leukocytes458–461 but TAMs can also derive from proliferation of tissue-resident macrophages462–465. In general, TAMs exert a potent protumoral activity, although certain TAM subsets might exert antitumoral activity172,466 (figure 21). TAMs promote angiogenesis and vascularization and also participate in remodeling the extracellular matrix, thus facilitating tumor cell motility and extravasation. Moreover, TAMs dampen T lymphocyte antitumoral cytotoxicity and support tumor growth and cell recruitment. TAMs primarily secrete VEGF, IGF1, Platelet Derived Growth Factor (PDGF) and MMPs, all of which contribute to vascularization and matrix remodeling to ensure arrival of nutrients from the blood stream. TAM immunosuppressive activities derived from their reduced IL-12 production and increased release of IL-10, TGFβ and prostaglandin E2 (PGE2), all of which activate Treg lymphocytes and impede cytotoxic T cell responses. TAMs also recruit Treg through production of chemokines like CCL20 and CCL22, promote apoptosis of T cells and suppress T cell function by ARG1 expression and NO production. Besides, TAMs enhance tumor proliferation by activation of NFkB and STAT3 secondary to secretion of pro- inflammatory cytokines like IL-6 or TNFα. Alteration of Programmed Cell Death Protein 1 and their ligand (PD1-PDL1 axis) and expression of MHC and co-immunostimulatory molecules also play a role in the ability of TAM to suppress anti-tumor T lymphocyte actions. Finally, TAMs are involved in the creation of a metastatic niche in a CCL2-dependent manner. All these actions are maintained by the low-oxygen environment and the intimate communication between TAMs and tumor cells, that even involves exosome interchange467,468. Tumor-derived signals like lactic acid469 or immunosuppressive cytokines470–472, and the anoxic environment473,474, prime TAMs to acquire an M2-like polarization state. So, TAMs exhibit mostly anti-inflammatory M2 features (production of IL-10), although they also produce NO and some pro-inflammatory and chemotactic cytokines. M1-like TAMs play a role in the initiation of a tumor, but signals derived from tumor cells and the microenvironment, produced along the transition to more advanced states of cancer, end up polarizing TAMs towards the acquisition of an M2-like phenotype. Therefore, some authors claim that, rather than M1 or M2, TAMs should be addressed as immunostimulatory or immunomodulatory macrophages, considering the different activities of these-resident macrophages and the fact that both populations can be found in a tumor. Actually, some macrophages that do not display M1 or M2 features have been found475. Recently, some descriptive studies have shown that, in the liver metastatic tumor microenvironment, two macrophage populations exist that can be distinguished by their morphology, size and functions: Large TAMs and Small TAMs. These two populations can be distinguished also by their characteristic transcriptomic signature, and their abundance mark cancer prognosis226. Of note, comparison of the “proinflammatory gene set” and “Antiinflammatory gene set” that define monocyte-derived GM-MØ and M-MØ macrophages with the transcriptome of Large Introduction 49 and Small TAMs reveal a clear overlap, with Large TAMs resembling antiinflammatory M-MØ and Small TAMs mimicking proinflammatory GM-MØ. In this scenario, the LXR pathway is upregulated in Large TAMs in comparison with Small TAMs, illustrating the importance of LXR in cancer and the possibility of modifying LXR activity to alter polarization of TAMs. Besides, M-CSF and GM-CSF, that control in vitro polarization of human monocyte-derived macrophages, regulate different aspects of TAMs and also contribute to their phenotype476. As the number of TAMs in human tumors correlates with a higher tumor grade and shorter survival477–483, and since TAMs limit antitumoral responses, macrophages have emerged as promising therapeutic targets in cancer (figure 22), and different strategies have arisen to target tumor-promoting macrophages. CCR2/CCL2 blockers or anti-chemotactic drugs limit macrophage number in the tumor yielding better patients’ outcomes484,485, although cancer cells can adapt and surpass CCL2 blocking486. Moreover, treatment with an agonist of CD40, a co-stimulatory molecule characteristic of M1 macrophages, increases antigen presentation by macrophages and induces tumor regression487,488. In this sense, targeting CD47, a “don’t eat me” signal that prevent phagocytosis of cancer cells, has also shown promising results489,490. Finally, cancer immunotherapy targeting “checkpoint inhibitors” has become a current anti-cancer therapy, and also influences macrophage activity. In this regard, targeting the PD1/PDL1 axis enhances phagocytosis activity of macrophages and increases tumor cell elimination491. Figure 21. Tumor Associated Macrophages (TAMs) exert several functions that promote tumor growth, extravasation and metastasis. TAMs secrete VEGF that promotes angiogenesis and increases nutrients availability to the tumor, and, in combination with PDGF and other factors, benefits tumor growth. Macrophages produce metalloproteinases (MMP2, MMP9) and M-CSF to secure tissue remodeling, epithelial- mesenchymal transition (EMT), invasion, extravasation and metastasis. Prostaglandins and arginase, along with antiinflammatory cytokines (IL-10, TGFβ), alter T lymphocyte function and contribute to tumor growth and resistance. Adapted from 492 . Introduction 50 Nevertheless, repolarization of TAMs towards an M1-like immunostimulatory phenotype has gained insight in recent years. Blocking or inhibiting the M-CSF receptor with antibodies or antagonistic molecules reverses macrophage polarization to an M1 state and decreases tumor burden in animal and human patients, standing out as one of the most important strategies under evaluation493,494. Unfortunately, blocking M-CSF receptor has shown limited efficacy, as other cells in the tumor microenvironment exert compensatory mechanisms495 and inflammation is maintained496. Another class of antibodies like IgE497 and low-dose radiotherapy498 can also reprogram macrophages towards an M1-like phenotype that recruit T lymphocytes and contribute to destroy the tumor. Recently, a combination of α- Difluoromethylornithine (DMFO) and 5-Azacytidine (5-AZA) has been shown to increase antitumoral macrophages while decreasing protumoral macrophages499, thus contributing to tumor destruction. Besides, self-assembled nanoparticles that contain two inhibitors (DNTs) can target M2 macrophages and repolarize them into active M1 macrophages500. As a novelty, the transfection of particles that mimic exosomes is being investigated as a possible therapeutic strategy501, in particular to target and/or repolarize macrophages502–504. Besides, the use of Chimeric Antigen Receptor (CAR)-T cells that has been used to treat cancer505–507 is being explored as a powerful technique to target tumor macrophages508. Indeed, CAR-T cell-mediated selective elimination of murine TAMs through targeting of Folate Receptor β (FRβ), a marker of anti-inflammatory macrophages, results in delayed tumor progression and prolonged survival508. Overall, macrophage repolarization has become as a highly powerful tool to treat cancer, and alternative strategies that target macrophage must be taken in great consideration. Overall, targeting the factors/receptors that determine macrophage phenotype, proliferation or recruitment constitute potential therapies to treat cancer. In this regard, LXR modulation has also been addressed as an alternative, as they regulate major aspects of macrophage behavior and control lymphocyte functions223. LXR activation, alone or in combination with other treatments, targets macrophages and inhibits tumor growth in several cancers (lung, colon, prostate, breast and pancreatic) through a plethora of mechanisms that includes limited T regulatory cell recruitment, increased cancer cell apoptosis or altered signaling pathways necessary for tumor growth, development or metabolism509–515. Alteration of cholesterol synthesis and efflux by LXR modulation has proven crucial in prostate and breast cancer that depend on the generation of steroid hormones516–518. Besides, LXR activation limits the function of “Myeloid Derived Suppressor Cells” (MDSCs) in the tumor microenvironment 224. Interestingly, LXR inhibition also potentiates tumor destruction in triple- negative breast cancer519, proving that understanding macrophage heterogeneity is crucial in the search for new cancer treatments. However, whether LXR alteration changes TAM polarization and improves cancer prognosis, and the potential mechanisms underlying this action, requires further studies. Introduction 51 Figure 22. Macrophages constitute perfect targets to treat cancer. Different strategies have been developed to tackle cancer through macrophage performance: blockade of PD1-PDL1 or CCR5/CCL5 axes, stimulation of CD40, inhibition of Angiopoietin-1 Receptor (Tie2) and M-CSF receptor (CSF-1R) have been shown to diminish the number of macrophages in the tumor and lead to a better prognosis. Other strategies targeting Phosphatidylinositol 3-kinase (PI3K), the endoribonuclease DICER or Histone Deacetylases (HDAC) have focused on re-educating (re-programming) macrophages within the tumor, converting them from protumoral to antitumoral. Adapted from 520 . Rheumatoid Arthritis (RA) is one of the most common autoimmune and chronic inflammatory disorders in humans. RA affects 1-2% of the world population and is characterized by chronic inflammation of the joints that results in damage, pain and loss of functions of muscles and bones521,522. Besides, RA is associated with premature death secondary to earlier development of cardiovascular and lung diseases523. The triggering cause of RA remains unknown and many genetic, epigenetic and environmental factors have been associated, including smoking524, inner microbiota525 or the presence of particular HLA- DR alleles526,527 and microRNAs528. The intrinsic complexity of the synovial membrane determines a differential distribution between macrophages of the synovial lining and macrophages at the cartilage junction529 (figure 23). The synovial membrane is composed of scattered macrophages within a fibroblast stromal tissue and scarce blood vessels. In RA, the synovial membrane becomes hypertrophic due to the large infiltration of immune cells, fibroblast expansion and osteoclast activation. This inflammation causes bone and cartilage destruction and leads to extreme pain and loss of function of the tissue530,531. Infiltration and accumulation of cells in the synovium membrane forms the so-called rheumatoid pannus. Depending on the dominant cellular population, RA can be categorized as myeloid or fibroid, a distinction that is of importance for subsequent therapy to tackle the disease532. Introduction 52 Figure 23. Macrophages populate the synovial membrane. The synovial membrane is composed of a sublining layer, where interstitial macrophages reside, and a lining layer, constitute mainly by macrophages and fibroblast and the synovial fluid. During RA, and in response to different signals, monocyte-derived macrophages penetrate the tissue from the blood vessels and into the sublining layer. Adapted from 533 . Monocytes and macrophages lie at the center of RA pathogenesis and their origin resembles those of cancer, with both tissue-resident and newly recruited monocyte-derived macrophages responding to the pro-arthritic milieu and adopting a harming proinflammatory phenotype534,535 (figure 24). Although many cytokines that contribute to RA have been found in the synovial fluid of RA patients (TNFα, IL-1β, IL-1, IL-6, IL-10, IL-12, IL18, IL-15, IL-10, GM-CSF, M-CSF and TGFβ), macrophages are the main producers of TNFα and IL-1 in this setting536–539. TNFα is the most important cytokine involved in RA pathology, as it exerts proinflammatory and bone-resorbing effects537,540, while IL-1 induces MMPs, iNOS and Receptor Activator of Nuclear factor Kappa-Β Ligand (RANKL) that also lead to joint inflammation541,542. TNFα also activates fibroblasts leading to RANKL and M-CSF production543–545, what ultimately activates osteoclasts, and induces MMPs, leukotrienes and prostaglandins secretion546,547. IL-6 production has been linked to fibroblasts and can also activate osteoclasts and produce bone resorption548,549. Many other cytokines like IL-15, IL- 17, IL-18, IL-22, IL-26 or IL-29 have been linked to macrophage-lymphocyte interactions in RA, and cause further damage550–556. In fact, a crosstalk exists between all these proinflammatory mediators and cells in the synovial tissue557,558. Macrophages are also producers of several chemokines in synovial fluids, including CXCL1, CXCL5, CXCL8, CXCL9, CXCL10 and CCL2. All these chemokines contribute to monocyte and cellular recruitment and subsequent inflammation559. Moreover, high levels of TNFα contribute to macrophage survival, elevating the positive feedback loop between TNFα secretion and inflammation in RA560. Introduction 53 Figure 24. Macrophages concentrate RA pathogenesis. The first triggering event of RA is currently unknown but the hyperplasia of the synovial membrane, caused by activation of fibroblast and macrophages, is the best candidate. Macrophages are crucial for the onset of RA as they exert numerous functions that boost RA pathology. Macrophages secrete pro-inflammatory cytokines (TNFα, IL-6, IL-1β, IL-17 and many others) that activate osteoclast, stimulating bone resorption and fibroblast proliferation, enhancing remodeling of the tissue and its destruction. Macrophages also lure blood cells into the synovial tissue and increase the inflammation and tissue damage. This whole proinflammatory environment polarizes monocyte-derived macrophages and non- active resident macrophages to acquire an M1-like phenotype, creating a loop of inflammation and tissue destruction. Adapted from 561 . Lastly, macrophages interact with T lymphocytes to promote RA pathology. Macrophages attract T lymphocytes into the synovium and promote damage. Macrophages present antigens derived from joint damage to naïve T cells in the lymphoid organs, and these mature T lymphocytes promote proinflammatory responses when reaching the synovium562,563. T lymphocytes can also stimulate resting macrophages to produce the chemokines and cytokines mentioned above, also including IL-10564,565. Curiously, when T cells are stimulated in an antigen-independent manner with just cytokines (e.g. IL-15 or IL-2, IL-6 and TNFα) they induce macrophages to secrete TNFα but not the antiinflammatory cytokine IL-10566. In addition, direct contact between macrophages and lymphocytes have been shown to induce proinflammatory cytokine production and arthritis pathology567. This proinflammatory scenario is crucial for resident macrophages and newly recruited monocytes to differentiate into M1-like proinflammatory macrophages that are the major pathogenic cell population in RA. Like in cancer and other inflammatory diseases, both M1 and M2-like macrophage coexist in RA inflamed tissue, although the strong pro- inflammatory millieu in RA polarizes these macrophages towards the M1-like phenotype. Soler et al. and Vandoreen et al.205,568 have shown that synovial macrophages resemble in vitro proinflammatory GM-MØ at the transcriptional and phenotypic levels, and that M1-like macrophages predominate in synovial tissue of patients with RA. Indeed, synovial fluids skew in vitro human monocytes to acquire a M1 phenotype. However, Ambarus and colleagues569 found that macrophages expressing M2 markers predominate in the synovial Introduction 54 lining of patients with RA, and that peripheral blood monocytes of RA patients concomitantly displayed an M1 phenotype. Joint-derived antigens can promote M1 features570 and the higher M1/M2 macrophage ratio in rheumatoid arthritis promotes osteoclastogenesis571. Furthermore, hypoxia plays a part in this inflammatory scenario and contributes to macrophage polarization towards a glycolytic M1 phenotype572,573 and to extravasation of immune cells574. Curiously, hypoxia may have a dual role in macrophage polarization, as the tumor microenvironment is also characterized by hypoxia and TAMs primarily exhibit an M2-like phenotype. Probably, activation of HIF and the variety of HIF-dependent functions might explain this apparent discrepancy. In this regard, some authors postulate that the tumor environment is most presumably anoxic instead of hypoxic, and this difference might explain the apparent dual effect of hypoxia in pathogenic macrophage polarization. In any event, as the number of macrophages correlates with RA disease activity575, macrophages serve as biomarkers for RA576 and the decrease in macrophage number is also an indicator of RA regression (referenced below). Therefore, targeting macrophages and/or their polarization state could have therapeutic benefits in RA. Connecting with the importance of macrophage polarization in RA and the findings of Soler et al.205, GM-CSF produced by activated fibroblasts promotes M1 differentiation577–579. In this way, GM-CSF-mediated induction of M1 polarization and M-CSF-dependent promotion of osteoclast activation critically contribute to RA pathology. In RA, the chronology of the pathologic events is still under investigation. However, some researchers found that months before the onset of RA, increased levels of GM-CSF and IL-6 could be observed580. It is possible that a primary triggering event increases one of these cytokines, thus creating a loop in which macrophages are crucial, as proinflammatory cytokines secreted by them can further promote M1 polarization, tissue damage, cellular activation and inflammation, with the whole process failing to resolve even in response to therapy. Of note, distinct subsets of synovial macrophages regulate remission and response to therapy in RA581. Therefore, understanding the implication of macrophages and their diversity in RA is crucial for the development of effective therapies. Consistent with these findings, blocking M-CSF or GM- CSF action impedes development of arthritis582,583. The primary treatment for RA is Methotrexate (MTX), with 40% of the patients subjected to MTX therapy showing reduced inflammation and pain. MTX exert its therapeutic effects by several mechanisms584–587 but clearly impacts on macrophage polarization. In fact, MTX effects are dependent on the macrophage polarization state as MTX triggers a state of tolerance exclusively on GM-CSF-dependent GM-MØ-like macrophages by a Thymidylate Synthase (TYMS)-dependent manner588,589. As proinflammatory cytokines produced in the synovium are the principal actors that promote M1 polarization, targeting them has already shown beneficial effects in RA (figure 25). TNF and IL-6 are the cytokines with highest levels in RA, and blocking TNF and IL-6 has led to decreased levels of proinflammatory cytokines in the synovium of RA patients590–595 and even a reduction in the pain associated with the disease596, probably because of re- programming of macrophages597,598. Nowadays, several anti-TNF and anti-IL-6 agents have been approved for RA treatment, and tackling other cytokines like IL-12, IL-15, IL-18, GM- CSF or M-CSF has also shown promising results599–603. Numerous additional and innovative strategies to treat RA have appeared in recent years, and novel ways to target drugs specifically to macrophages, like nanoparticles, have been proposed604. For example, Introduction 55 administration of alginate nanoparticles loaded with IL-10 repolarize M1 to M2 macrophages in a model of RA in rats605 and administration of human umbilical blood stem cells in a model of RA in mice also repolarizes macrophages towards an M2 state606. Finally, researchers are investigating the use of tyrosine kinase inhibitors to hinder macrophage-dependent cytokine production and to ameliorate RA607–610. As a whole, modulating different aspects of macrophage biology can be very beneficial for RA patients. Surprisingly, the LXR pathway has been described as the most upregulated pathway in synovial macrophages compared to blood monocytes, and their activation potentiates cytokine secretion by synovial macrophages225. Accordingly, LXR agonism boost inflammation in a arthritis mouse model611. However, other studies have suggested the opposite, and report that LXR activation prevents arthritis appearance612. The methodology used for induction of arthritis in the mice or the dosage of the LXR agonists could explain these contradictory results. Curiously, in line with this last study, LXR activation prevents synoviocyte invasiveness and production of cytokines in vitro613 and attenuates arthritis-affecting lymphocytes614. All of these investigations, and the fact that LXR also mitigates osteoarthritis615,616, convey the importance of inspecting LXR as a potential spot for treatment of RA. Figure 25. Drugs that target macrophages encompass crucial treatments for RA. Inhibition of TNF and IL-6 inhibits proinflammatory polarization of macrophages and subsequent osteoclast differentiation and lymphocytes activation, showing promising effects in the treatment of rheumatoid arthritis. Modulation of macrophages has arisen as the most propitious target for disease therapy. Adapted from 617 . In conclusion, macrophages play a central role in tissue homeostasis and are indispensable for combating pathogens and internal threats, but they also contribute to pathology of important disorders like cancer or rheumatoid arthritis, where they have become major targets for therapy. Within macrophage biology, LXR are master regulators of macrophage behavior in tissue homeostasis and in pathologic conditions, controlling their Introduction 56 performance during development and in response to harming scenarios. However, the role of LXR in human macrophages, and specifically in their polarization, has been poorly addressed and is urgently required, as LXR are important targets for therapy in disorders where macrophages are relevant. Therefore, the objectives of this doctoral thesis are to unravel the role of LXR in human macrophage polarization and to explore their modulation as a potential strategy to treat inflammatory conditions. HYPOTHESIS AND OBJECTIVES Hypothesis and objectives 58 Having described the importance of searching for new factors that control macrophage (re)polarization (re-programming) and the relevance of LXR in macrophage function and behavior, we have hypothesized that LXR are essential for human macrophage polarization and function. In particular, we propose that LXR will be principal actors for antiinflammatory macrophage polarization, may have a role in the protumoral activity of tumor-associated macrophages, and may also control trained immunity/tolerance of human macrophages in response to different stimulus. Accordingly, the objectives of this doctoral thesis are: 1. Assessment of LXR proteins and LXR target gene expression in human GM-CSF- primed (GM-MØ) and M-CSF-primed (M-MØ) monocyte-derived macrophages. 2. Determination of the LXR-dependent transcriptome of human GM-CSF-primed (GM- MØ) and M-CSF-primed (M-MØ) monocyte-derived macrophages through the use of LXR agonists and inverse agonists. 3. Identification of novel LXR-dependent genes and functions in human macrophages. 4. Analysis of the role of LXR in the acquisition of the macrophage polarization state promoted by pathological fluids from rheumatoid arthritis or cancer. 5. Analysis of the involvement of MAFB, PPARγ and IRF4 in the changes in macrophage polarization triggered by modulation of LXR activity. 6. Determination of the role of LXR in the AhR-mediated polarization of human macrophages. EXPERIMENTAL PROCEDURES Experimental procedures 60 Generation of human monocyte-derived macrophages in vitro and treatments Human Peripheral Blood Mononuclear Cells (PBMCs) were isolated from buffy coats from anonymous healthy (HIV-, Hepatitis C-) donors over a Lymphoprep (Nycomed Pharma) gradient according to standard procedures (provided by the Transfusions Center of Comunidad de Madrid). The demographic characteristics of the donors were unknown. Monocytes were purified from PBMC by magnetic cell sorting using anti-CD14 microbeads (Miltenyi Biotec). Monocytes (>95% CD14+ cells) were cultured at 0.5 x 106 cells/ml in Roswell Park Memorial Institute (RPMI 1640, Gibco) medium supplemented with 10% fetal bovine serum (FBS, Biowest, Gibco) for 7 days in the presence of 1000 U/ml GM-CSF or 10 ng/ml M-CSF (ImmunoTools) to generate GM-CSF-polarized macrophages (GM-MØ) or M- CSF-polarized macrophages (M-MØ), respectively. Cytokines were added every two days and cells were maintained at 37°C in a humidified atmosphere with 5% CO2 and 21% O2. Each buffy coat corresponds to a different blood donor. Where indicated, macrophages were treated at different time points with one dose of the LXR agonist GW3965231 (1 μM, Tocris) (to generate GW3965-M-MØ or GW3965-GM- MØ), the LXR inverse agonist GSK2033236 (1 μM, Tocris) (to generate GSK2033-M-MØ or GSK2033-GM-MØ), or both (to generate GW/GSK2033-M-MØ or GW/GSK2033-GM-MØ), using dimethyl sulfoxide (DMSO) as vehicle. In the dual condition, the inverse agonist was added 1-hour prior to agonist treatment. Besides, when indicated, either Synovial Fluid from Rheumatoid Arthritis (RASF) patients or Tumor Ascitic Fluid from cancer patients (TAF) was added to monocytes (0,2:1 ratio in culture medium for RASF, 0,5:1 ratio in culture medium for TAF), and the cultures were maintained for 72 h. Considering the particular components of the fluids, previous experiments performed in Dr. Puig-Kröger laboratory (Hospital General Universitario Gregorio Marañón) showed these were the appropriate ratios to assess macrophage polarization without compromising cell viability. Each TAF was obtained from a different patient, and was collected anonymously. In the case of synovial fluids, these samples were obtained by therapeutic arthrocentesis from the knee joints of six patients with active Rheumatoid Arthritis. For ascitic fluids, these were kindly provided by Dr. Mª. Isabel Palomero (Oncology Department, Hospital General Universitario Gregorio Marañón) and correspond to four patients with different tumor pathologies: one from ovary cancer with peritoneal metastasis, one from renal carcinoma, and two from gastric carcinoma patients. Samples were centrifuged (4000xg, 15 min) to remove cells and particulate material, sterile- filtered, aliquoted, and stored at -20°C until use. In all cases, patients provided informed consent (Approval for this study was obtained from the ethics committee of Hospital General Universitario Gregorio Marañón, and the procedures used in this study adhere to the tenets of the Declaration of Helsinki). For activating macrophages or activate or inhibit several molecules, a buffet of small molecules was used: 1) for macrophage activation, cells were treated with 10 ng/ml E. coli 055:B5 lipopolysaccharide (Ultrapure LPS, Sigma-Aldrich). 2) To assess MTX (Sigma) response, macrophages were treated with MTX at 50 nM from the start of the differentiation process. 3) To activate LXR while prevent SREBP we used synthetic Desmosterol-mimic DMHCA344,346,347 (500 nM, Sigma) 4) To obstruct GSK3β, we used CHIR99021618 (2 μM, Sigma). HIF1α stabilizer DFO619 (100 µM) was a Gift. 5) To activate PPARγ we used synthetic agonist GW7895620 (a gift from Antonio Castrillo group, 2 µM). 6) To inhibit AhR, Experimental procedures 61 CH-223191621 (Sigma, 3 µM) along the monocyte-to-macrophage transition was used. 7) To activate AhR, FICZ622 (Enzo Life Sciences, 250 nM) was used. RNA extraction and Quantitative real-time RT-PCR (qRT-PCR) Total RNA was extracted using the total RNA and protein isolation kit (Macherey- Nagel). RNA samples were reverse-transcribed with High-Capacity cDNA Reverse Transcription reagents kit (Applied Biosystems) according to the manufacturer’s protocol. Real-time quantitative PCR was performed with LightCycler® 480 Probes Master (Roche Life Sciences) and Taqman probes on a standard plate in a Light Cycler® 480 instrument (Roche Diagnostics). Gene-specific oligonucleotides (Table 1) were designed using the Universal ProbeLibrary software (Roche Life Sciences). Results were normalized to the expression level of the endogenous references genes TBP, HPRT1 or GAPDH and quantified using the ΔΔCT (cycle threshold) method. Enzyme-Linked ImmunoSorbent Assay (ELISA) Human cytokine production was measured in supernatants collected from treated M- MØ and GM-MØ in non- and activating conditions using commercial ELISA [(TNF-α, CCL2 (BD Biosciences), IL-10, IL-6 (Biolegend), Activin A, CCL19, CCL17, IL-1β, IFN-α, IFNβ (R&D Systems) and according to the procedures supplied by the manufacturers. Lactate production Lactate levels were measured in treated M-MØ and GM-MØ supernatants following Lactate Colorimetric Assay Kit (K627, Biovision) instructions. Luminiscence assays Untreated or untreated M-MØ and GM-MØ were detached using Trypsin-EDTA (Gibco) at 37ºC and plated at a density of 6x104 cells/well in 24-well-flat bottom plates for 24 hours. Plasmidic DNA of LXRE-Luc, negative control and positive control (Cignal Reporter Assay Kits, Qiagen) were transfected using Viromer Red (Origene, Lipocalix) standard protocol. After 6 hours culture medium was replaced and cells were allowed to recover for 18 hours. Cells were lysed and Firefly and Renilla luminescence was measured in a Luminometer using Dual-Luciferase® Reporter Assay System (Promega) according with their instructions. We performed three independent transfection per cell type and plasmid DNA and analyzed only those experiments where transfection was successful (Renilla values of LXRE-Luc transfection were similar to those of positive control transfection). Western blot M-MØ and GM-MØ cell lysates were subjected to SDS-PAGE (from 20 μg to 50 μg of total protein) and transferred onto an Immobilon-P polyvinylidene difluoride membrane (PVDF; Millipore). After blocking the unoccupied sites with 5% non-fat milk diluted in Tris- Buffered Saline plus Tween 20 (TBS-T), protein detection was carried out with antibodies against AhR (sc-8087, Santa Cruz), ABCA1 (NB400-105, Novus Biologicals), ABCG1 (NB400-132, Novus Biologicals) (gifts from Antonio Castrillo), LXRα (PPZ0412; Biotechne), LXRβ (PPK8917; Biotechne), MAFB (HPA005653, Sigma Aldrich), MAF (sc-7866; Santa Cruz Biotechnology), IRF4 (4964S, Cell Signaling), phosphoGSK3β (activating pTyr279/216 Experimental procedures 62 (05-413, MERCK), or inhibitor Ser21/9 (9331, Cell Signaling)), HIF1α (54/HIF-1α, BD Biosciences) and SREBP1 (ab28481, Abcam). Protein loading was normalized using an antibody against GAPDH (sc-32233; Santa Cruz Biotechnology) or Vinculin (V9131; Sigma- Aldrich). Quimioluminiscence was detected in a Chemidoc Imaging system (BioRad) using SuperSignal™ West Femto (ThermoFisher Scientific). Cell proliferation assay The human BRO Lung Metastasis (BLM) melanoma cell line was maintained in Dulbecco's Modified Eagle Medium (DMEM, Gibco) supplemented with 10% FBS (Biowest) at 37°C in a humidified atmosphere with 5% CO2 and 21% O2. BLM cells were plated (10 × 103 cells/well) in 96-well flat bottom plates, allowed to adhere for 24 hours, and exposed to culture supernatants from treated human M-MØ and GM-MØ for 72 hours. Cell proliferation was evaluated using MTT (0.5 mg/mL, Sigma-Aldrich) for 2 hours and absorbance of formazan crystals were measured at 540 nM in a MultiSkan Spectrophotometer (ThermoScientific). RPMI complete medium was used as control to determine the basal BLM cell proliferation. Direct effect of LXR agonist and inverse agonist on BLM cells was also evaluated. Experiments were performed using 6 replicates in four independent donors. Small Interfering Ribonucleic Acid (siRNA) Transfection M-MØ or GM-MØ (1 × 106 cells) were transfected with human NR1H3-specific siRNA (siNR1H3, 50 nM) (s19568, Thermo-Fisher Scientific) and/or human NR1H2-specific siRNA (siNR1H2, 50nM) (s14684; Thermo-Fisher Scientific) using HiperFect (Qiagen). Silencer™ Select Negative Control No. 1 siRNA (siCtrl, 50 nM) (#4390843; Thermo-Fisher Scientific) was used as negative control siRNA. Six hours after transfection, cells were allowed to recover from transfection in complete medium (18 h) and then lysed. Knock-down of NR1H3/LXRα or NR1H2/LXRβ was confirmed by q-PCR and western blot. Mixed Leukocyte Reaction (MLR) Untreated or treated M-MØ and GM-MØ were detached using Trypsin-EDTA (Gibco) or PBS plus EDTA 100 mM at 37ºC, and re-plated in a 96-well U-bottom plates (104 cells/well) in RPMI with 5% human AB+ serum (Sigma) for 24 hours. Allogeneic T lymphocytes were isolated from PBMCs using CD3+ magnetic beads (Miltenyi Biotec), and co-cultured with macrophages (10:1 T lymphocyte:macrophage ratio) for 6 days in RPMI with 5% human AB+ serum. Then, 3H-Thymidine (1 μCi/well, Perkin Elmer) was added and, after 18 hours, radioactivity was transferred to a filter and thymidine counts were measured in a scintillation counter (Perkin Elmer). 3H-Thymidine was determined in eight replicates from every condition and donor. RNA-sequencing and data analysis RNA was isolated from GM-MØ or M-MØ generated from monocytes exposed to a single dose of DMSO, GW3965, GSK2033 or both at the beginning of the differentiation process, and subjected to sequencing on a BGISEQ-500 platform (https://www.bgitechsolutions.com). Each sample of GM-MØ or M-MØ comes from a different buffy coat and therefore, three or more independent samples were submitted to RNA https://www.bgitechsolutions.com/ Experimental procedures 63 sequencing. RNAseq data were deposited in the Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/) under accession GSE156783, GSE156696, GSE161776 and GSE181313. Gene sets that define the transcriptome of GM-MØ ("Proinflammatory gene set") or M-MØ ("Antiinflammatory gene set") have been previously reported (GSE68061). Antiinflammatory and proinflammatory gene set group the genes with the highest differential expression defined by|log2fold|>8 and padj<0.05 between GM-MØ and M-MØ. On average, 88.04 M reads per sample were generated and clean reads were mapped to the reference (UCSC Genome assembly hg38) using Bowtie2 (average mapping ratio to reference genome, 91.82%)623. Gene expression levels were calculated by using the RSEM software package624 or HTAseq, and differential gene expression was assessed by using the R-package DESeq2 algorithm; using the parameters Fold Change>2 (log2FC>1) and adjusted p value <0.05 (adj p<0.05). Plots were generated with the ggplot2 package, and heatmaps and k-means clustering were performed using the Genesis software (http://genome.tugraz.at/genesisclient/)625. Principal Component Analysis (PCA) were conducted using R software. For clustering read counts of differentially expressed genes (log2fold and adj p <0.05) were normalized between all the conditions using Z-score, where values were adjusted to a value of mean=0 and standard deviation=1 among all the experimental conditions. For PCA read counts of differentially expressed genes (log2fold and adj p <0.05) were used. Besides, differentially expressed genes were analyzed for annotated gene sets enrichment using ENRICHR (http://amp.pharm.mssm.edu/Enrichr/)626,627, and PANTHER (http://pantherdb.org/)628 and enrichment terms were considered significant with a Benjamini- Hochberg-adjusted p value <0.05. For gene set enrichment analysis (GSEA) (http://software.broadinstitute.org/gsea/index.jsp)629, gene sets available at the website, as well as gene sets generated from publicly available transcriptional studies (https://www.ncbi.nlm.nih.gov/gds), were used (GSE90615, GSE131353). Ranked comparisons between transcriptomes were performed using either log2FC or -log10(padj). For GSEA analysis NES and FDRq were used and only enriched terms with FDR<0.25 were considered significant. NES illustrate the magnitude of the positive or negative enrichment of a given gene set and FDRq indicates how statistically significant is this enrichment. Venn diagrams were conducted using the Venny platform (https://bioinfogp.cnb.csic.es/tools/venny). Statistical analysis For comparison of means, and unless otherwise indicated, statistical significance of the generated data was evaluated using the paired Student t test. In cases of more than two groups, t-student was used to avoid influence of treated groups between each other. In all cases, p<0.05 was considered as statistically significant. All analyses were performed using GraphPad Prism 8. http://www.ncbi.nlm.nih.gov/geo/ http://genome.tugraz.at/genesisclient/ http://amp.pharm.mssm.edu/Enrichr/ http://software.broadinstitute.org/gsea/index.jsp https://www.ncbi.nlm.nih.gov/gds https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE90615 https://bioinfogp.cnb.csic.es/tools/venny Experimental procedures 64 TABLE 1. PRIMERS USED IN THE PRESENT STUDY GENE PRIMER SEQUENCE ABCA1 Forward TGCTGCATAGTCTTGGGACTC Reverse ACCTCCTGTCGCATGTCACT ABCG1 Forward TCAGGGACCTTTCCTATTCG Reverse TTCCTTTCAGGAGGGTCTTGT ABCG4 Forward ATGAGGGAGCACCTCAACTACT Reverse GACCACCCGGACACACCAC ACACA Forward GGCTCAAACTGCAGGTATCC Reverse ATTTTCCTGCCAGTCCACAC ACACB Forward CAGACGCTACAGGTCCCAAC Reverse CTGTCCACTCCACTGTCAGG AHRR Forward GCAAAACCCAGAGCAGACAC Reverse ACAGACTGGTGGTGGCTTTTA APOE Forward CAGGCAGGAAGATGAAGGTT Reverse CTGTCTCCACCGCTTGCT AQP3 Forward GTCACTCTGGGCATCCTCAT Reverse AGCACATGGCAAAGGTCAC ARG2 Forward AGCAGAGCTGTGTCAGATGG Reverse GGCATGGCCACTAATGGTA ARL4C Forward CACCAATGTATCAATGGGTGATT Reverse CCTATGGGAAACCCATTCACT CA12 Forward GCTCTGAGCACACCGTCA Reverse GGATAAAGGTCTGAGTTATAATGGACA CCL2 Forward AGTCTCTGCCGCCCTTCT Reverse GTGACTGGGGCATTGATTG CCL20 Forward GCTGCTTTGATGTCAGTGCT Reverse GCAGTCAAAGTTGCTTGCTG CCL8 Forward CCCTCAGGGACTTGCTCAG Reverse CTCCAGCCTCTGGATAGGAA CCR2B Forward TGAGACAAGCCACAAGCTGA Reverse TTCTGATAAACCGAGAACGAGAT CD163 Forward GAAGATGCTGGCGTGACAT Reverse GCTGCCTCCACCTCTAAGTC CD163L1 Forward AGAACCCCTCCTTCTGGTTG Reverse AGCACTTATTTTATCCAGTATCTTTGG CD1B Forward CCCTCAGGGACTTGCTCAG Reverse CTCCAGCCTCTGGATAGGAA CD209 Forward TCGAGGATACAAGAGCTTAGCA Reverse AAGGAGCCCAGCCAAGAG CD36 Forward TGGAACAGAGGCTGACAACTT Reverse TTGATTTTGATAGATATGGGATGC CLEC5A Forward ACGGCTTCATTACCACAAGG Reverse CTTGCTTGATAAAATTCCCAGTC CXCL2 Forward CGCCCATGGTTAAGAAAATC Reverse AGGAACAGCCACCAATAAGC CYP1B1 Forward ACGTACCGGCCACTATCACT Reverse CTCGAGTCTGCACATCAGGA DHCR24 Forward CTACTACCACCGCCACACG Experimental procedures 65 Reverse GTTGTTGCCAAAGGGGATAA EGLN3 Forward ATCGACAGGCTGGTCCTCTA Reverse GATAGCAAGCCACCATTGC FABP4 Forward CCTTTAAAAATACTGAGATTTCCTTCA Reverse GGACACCCCCATCTAAGGTT FASN Forward CAGGCACACACGATGGAC Reverse CGGAGTGAATCTGGGTTGAT FCGBP Forward GGCACAGCTGACATGATCC Reverse GAAGGTGAGCAGTCCCAAGT FOLR2 Forward GAGAGAGGCCAACTCAGACAC Reverse CCAGACCATGTCTTTCTGTCC GAPDH Forward AGCCACATCGCTCAGACAC Reverse GCCAATACGACCAAATCC GDF15 Forward CCGGATACTCACGCCAGA Reverse AGAGATACGCAGGTGCAGGT HIF1A Forward TTTTTCAAGCAGTAGGAATTGGAA Reverse GTGATGTAGTAGCTGCATGATCG HMGCR Forward GTTCGGTGGCCTCTAGTGAG Reverse GCATTCGAAAAAGTCTTGACAAC HMGCS1 Forward TGTCCTTTCGTGGCTCACT Reverse CTGTCACTGTTTCCTCCTTCG HPRT1 Forward TGACCTTGATTTATTTTGCATACC Reverse CGAGCAAGACGTTCAGTCCT HTR2B Forward TGCTGGAGGCTCAGAATAAGT Reverse TTGCATGCCAGAGAGTTCC IGF1 Forward TGT GGA GAC AGG GGC TTT TA Reverse ATC CAC GAT GCC TGT CTG A IL10 Forward TCACTCATGGCTTTGTAGATGC Reverse GTGGAGCAGGTGAAGAATGC INHBA Forward CTCGGAGATCATCACGTTTG Reverse CCTTGGAAATCTCGAAGTGC IRF4 Forward CTGGCTAGCAGAGGTTCTACG Reverse GCCAAGATTCCAGGTGACTC LDHA Forward GCAGATTTGGCAGAGAGTATAATG Reverse GACATCATCCTTTATTCCGTAAAGA LGMN Forward GAACACCAATGATCTGGAGGA Reverse GGAGACGATCTTACGCACTGA LIF Forward TGCCAATGCCCTCTTTATTC Reverse GTCCAGGTTGTTGGGGAAC LPL Forward AGAACATCCCATTCACTCTGC Reverse CCATTTGAGCTTCAACATGAGTA MAFB Forward GCAGGTATAAACGCGTCC Reverse TGAATGAGCTGCGTCTTCTC MARCKS Forward GGTGCCCAGTTCTCCAAG Reverse TTTACCTTCACGTGGCCATT MERTK Forward ATTGGAGACAGGACCAAAGC Reverse GGGCAATATCCACCATGAAC MET Forward AAATGTGCATGAAGCAGGAA Reverse TCTCTGAATTAGAGCGATGTTGA MMP12 Forward TGTCACTACCGTGGGAAATAAG Reverse AACACTGGTCTTTGGTCTCTCAG MYLIP Forward CGAGGACTGCCTCAACCA Experimental procedures 66 Reverse TGCAGTCCAAAATAGTCAACTTCT NR1H2 Forward CCGAGCCTGTAGACCTATCG Reverse TCACCCCTTCTGGAAGACTC NR1H3 Forward CATCCTCTTCTCCCAGCAAG Reverse CATTACCAAGGCACTGTCCA PLTP Forward CCACCTACTTTGGGAGCATT Reverse CAGCTTCAATGGGGAGTCA PPARG Forward GACAGGAAAGACAACAGACAAATC Reverse GGGGTGATGTGTTTGAACTTG SCD Forward CCTAGAAGCTGAGAAACTGGTGA Reverse ACATCATCAGCAAGCAGGT SLC2A1 Forward GGTTGTGCCATACTCATGACC Reverse CAGATAGGACATCCAGGGTAGC SLC40A1 Forward CCAAAGGGATTGGATTGTTG Reverse CCTTCGTATTGTGGCATTCA SQLE Forward CCTGAATCAGAAAATAAGGAGCA Reverse GCTTGTTTCTGAAATATTGGTTCC SREBF1 Forward CGCTCCTCCATCAATGACA Reverse TGCGCAAGACAGCAGATTTA SREBF1c Forward GGCACTGAGGCAAAGCTG Reverse GACAGCAGTGCGCAGACTTA SREBF2 Forward ATCTGGATCTCGCCAGAGG Reverse CCAGGCAGGTTTGTAGGTTG STAB1 Forward TGTGGCTATTGACGAGTGTGA Reverse AAAGCCCAGCTTGCAGGT TBP Forward CGGCTGTTTAACTTCGCTTC Reverse CACACGCCAAGAAACAGTGA TNF Forward CAGCCTCTTCTCCTTCCT Reverse GCCAGAGGGCTGATTAGA TYMS Forward CCCAGTTTATGGCTTCCAGT Reverse GCAGTTGGTCAACTCCCTGT RESULTS LXR control macrophage transcriptional and functional polarization Results 69 LXR are expressed in human pro and antiinflammatory macrophages in basal and activating conditions As previous studies have not appropriately addressed the expression and function of LXR nuclear receptors in primary human macrophages, we characterized LXR expression and activity in in vitro human antiinflammatory M-MØ and proinflammatory GM-MØ macrophages (figure 26A). Results showed the expression of LXRα and LXRβ in both macrophages subtypes (figure 26B, C). The expression of LXRβ (NR1H2 gene) was higher in M-MØ, whereas higher levels of LXRα (NR1H3 gene) were found in GM-MØ. In terms of activity, we observed that, GM-MØ have greater LXR-dependent transcriptional activity than M-MØ in basal conditions (figure 26D), although the difference did not reach statistical significance. In any event, this result confirmed that LXR proteins are functional in both M- MØ and GM-MØ. Since human macrophages express splicing isoforms of LXRα218,219, we designed specific primers to amplify the three most abundant splicing isoforms of LXRα in M- MØ and GM-MØ (figure 26E). PCR demonstrated that both M-MØ and GM-MØ express the three previously described splicing isoforms of LXRα (figure 26F). Altogether, these results demonstrated that M-MØ and GM-MØ express functional LXR factors, implying that they constitute a valid experimental system to address the involvement of LXR in macrophage polarization. We next analyzed the expression of known LXR target genes in M-MØ and GM-MØ, using a curated list generated after an extensive search of the available literature (table 2), and found that M-MØ and GM-MØ exhibit a distinct profile of LXR-dependent genes. In fact, GSEA showed a bimodal distribution of LXR target genes in M-MØ and GM-MØ, which might reflect the distinct expression of LXRα/β in both macrophage subtypes. This was further confirmed by qPCR (figure 27B) and after analysis of the expression of LXR target genes along monocyte-to-macrophage differentiation towards M-MØ and GM-MØ (figure 27C). As a whole, these results demonstrated that LXR are functional in both monocytes and macrophages and that the profile of LXR target genes is dependent on the macrophage differentiation state and differs between M-MØ and GM-MØ. Once we had demonstrated LXR expression and activity in M-MØ and GM-MØ, we investigated if LXR activity could be effectively modulated in both macrophage subtypes. To that end, M-MØ and GM-MØ were exposed to a potent agonist of LXR (GW3965, 1μM), or to a potent LXR inverse agonist (GSK2033, 1μM) for 24 and 48 hours (figure 27D). GW3965 treatment increased expression of LXRα (and NR1H3) and LXRβ (and NR1H2) in both macrophages, while GSK2033 diminished NR1H3 expression and enhanced LXRα/β protein expression (figure 27E, F, G). As expected, ABCA1 expression was increased by GW3965 and inhibited by GSK2033 (figure 27E, 2F), and was used as a readout of LXR modulation by both agonists in further experiments. These results confirmed that macrophages are sensitive to both LXR agonists, which modulate LXR proteins and LXR target gene expression in M-MØ and GM-MØ. Results 70 Figure 26. Proinflammatory GM-MØ and antiinflammatory M-MØ express LXR proteins and LXRα splicing isoforms. A. Scheme of the in vitro generation of human antiinflammatory (M-MØ) and proinflammatory (GM-MØ) macrophages. B. Expression of NR1H3 and NR1H2 mRNA in human M-MØ and GM-MØ. C. Expression of LXRα and LXRβ proteins in human M-MØ and GM-MØ. A representative image of western blot protein expression is shown. D. LXR-dependent transcriptional activity in human M-MØ and GM-MØ transfected with LXRE-luciferase promoter. Experiments represent the ratio of Firefly/Renilla luciferase values obtained in nine independent experiments. E. Representation of the primers used to amplify the different splicing isoforms of LXRα in human macrophages. F. Representation of agarose gels of LXRα isoforms in human M-MØ and GM-MØ. In all cases, mean ± SEM of four independent donors is shown. Paired-t-test was used to compare between groups and a pvalue<0.05 was considered as statistically significant. *p<0.05, **p<0.01, *** p<0.001. Results 71 Figure 27. Proinflammatory GM-MØ and antiinflammatory M-MØ exhibit distinct LXR target gene expression. A. GSEA of the gene set including known LXR target genes in the ranked comparison of the M-MØ and GM-MØ transcriptomes. B. LXR target gene expression in M-MØ and GM-MØ. C. LXR target gene expression regulation along the monocyte to macrophage differentiation. D. Scheme of the in vitro treatment of human M-MØ and GM-MØ with LXR agonist GW3965 or LXR inverse agonist GSK2033 for 24 or 48 hours. E. Expression of LXRα and LXRβ proteins and their genes NR1H3 and NR1H2 in M-MØ treated for 24 and 48 hours with GW3965 and GSK2033. Quantification of four independent donors is shown. F. Expression of LXRα and LXRβ proteins and their genes NR1H3 and NR1H2 in GM-MØ treated for 24 and 48 hours with GW3965 and GSK2033. G. Representative western blot for LXRα and LXRβ expression in human M-MØ and GM-MØ treated for 24 and 48 hours with GW3965 and GSK2033. In all cases, mean + SEM of three to six independent donors is shown. Paired-t-test was used to compare between groups and a pvalue<0.05 was considered as statistically significant *p<0.05, **p<0.01, *** p<0.001, **** p<0.0001. Results 72 TABLE 2. PREVIOUSLY REPORTED LXR TARGET GENES Gene Name Other symbols Cellular type References ABCA1 ATP binding cassette subfamily A member 1 Human and murine Macrophages 264–266,630 ABCG1 ATP binding cassette subfamily G member 1 ABC8 Human and murine Macrophages 264,631 ABCG4 ATP binding cassette subfamily G member 4 Human macrophages 632 ABCG5 ATP binding cassette subfamily G member 5 Hepatocytes and Enterocytes 282,633 ABCG8 ATP binding cassette subfamily G member 8 ACACA Acetil CoA carboxylase Hepatocytes 288 ACACB ACSL3 acyl-CoA synthetase long chain family member 3 Human placental trophoblasts 634 AdipoR1 Adiponectin Receptor Human macrophages 635 AdipoR2 ANGPTL3 angiopoietin like 3 Hepatocytes 636 APOA4 apolipoprotein A4 Hepatocytes 637,638 APOC1 apolipoprotein C1 Human and murine macrophages 271 APOC2 apolipoprotein C2 APOC4 apolipoprotein C4 APOD apolipoprotein D Adipocytes 270 APOE apolipoprotein E Human macrophages, Astrocytes 268,269 ARG2 Argynase 2 Human and mouse macrophages 639,640 ARL4C ADP ribosylation factor like GTPase 4C ARL7 Human and mouse macrophages 641 CD36 CD36 molecule Hepatocytes 642 CD5L CD5 molecule like AIM Mouse macrophages, human foam cells 306,643 CETP cholesteryl ester transfer protein Mouse hepatocytes, mouse adypocytes 279,280,644 ChREBP Carbohydrate-responsive element-binding protein MLXIPL Human and mouse macrophages, hepatocytes 284 CYP7A1 cytochrome P450 family 7 subfamily A member 1 Mouse macrophages; not in human macrophages 230,273,274 EEPD1 endonuclease/exonuclease/ph osphatase family domain containing 1 Human and mouse macrophages 645 FABP6 fatty acid binding protein 6 I-BABP Enterocytes 646 FASN fatty acid synthase FAS Hepatocytes 285 IL-5 Interleukin-5 Mouse macrophages 647 IL-18 Interleukin-18 Mouse macrophages 297 LBP lipopolysaccharide binding protein Mouse macrophages 648 LPCAT3 lysophosphatidylcholine acyltransferase 3 Human and mouse macrophages; Human hepatocytes 289,649,650 Results 73 LPL lipoprotein lipase Mouse macrophages 275 MERTK MER tyrosine kinase Human and mouse macrophages 303,651 MYLIP myosin regulatory light chain interacting protein IDOL Hepatocytes, mouse macrophages 276 NPC1 Niemann Pick C intracellular cholesterol transporter 1 Human macrophages 272 NPC1L1 Niemann Pick C-like intracellular cholesterol transporter 1 Enterocytes 281 NPC2 Niemann Pick C intracellular cholesterol transporter 2 Enterocytes 272 NR0B2 nuclear receptor subfamily 0 group B member 2 SHP Human hepatocytes 652 NR1D1 Nuclear receptor Rev-ErbA- alpha Human macrophages 653 NR1H3 Liver X Receptor α Human macrophages and human adypocytes 246,654 PLTP phospholipid transfer protein Human macrophages, hepatocytes, adypocytes, enterocytes 277,278 PTX3 Pentraxin 3 Human fibroblast 655 RARA Retinoid acid receptor alpha Human macrophages 656 SCARB1 Scavenger Receptor Class B Member 1 SR-BI Human macrophages, hepatocytes 657,658 SCD stearoyl-CoA desaturase Hepatocyte, mouse and human macrophages, adipocytes 286,287,659,660 SLC2A4 solute 73 carrier family 2 member 4 GLUT4 Adypocytes 661,662 SMPDL3A sphingomyelin phosphodiesterase acid-like 3A Human macrophages 663,664 SREBF1 sterol regulatory element binding transcription factor 1 Human macrophages, hepatocytes 283,343 SULT2A1 hydroxysteroid sulfotransferase family 2A member 1 Human hepatocytes 665 THRSP Thyroid hormone-inducible hepatic protein SPOT14 Hepatocytes 666 TLR4 toll like receptor 4 Human macrophages 309 TMEM135 Transmembrane Protein 135 Human hepatocytes and human macrophages 667 TNF tumoral necrosis factor Human monocytes 668 UGT1A3 UDP glucuronosyltransferase family 1 member A3 Hepatocytes 669 VEGFA vascular endothelial growth factor A Human and mouse macrophages 670 Results 74 LXR have a minor effect on the maintenance of the transcriptome of terminally differentiated macrophages Considering that human macrophages expressed LXR proteins and were sensitive to LXR agonist and inverse agonist, we next addressed the role of LXR in macrophage polarization. Initial experiments evaluated the effect of either LXR ligands or specific siRNA on the expression of a selected list of genes within the previously described “Proinflammatory gene set” (INHBA, MMP12, EGLN3, CD1B, AQP3, CCR2, CLEC5A) and “Antiinflammatory gene set” (IGF1, HTR2B, MAFB, FOLR2, CD163L1, IL10, STAB1), whose expression depends on and influences macrophage polarization 39,129,132,159,175,177,188,195,199,204,205,207–211,589,671–673. Analysis of macrophages exposed to LXR agonist GW3965 or LXR inverse agonist GSK2033 (figure 28) showed that the LXR target gene ABCA1 was modified as expected. However, LXR modulators did not cause major changes in the expression of polarization genes, implying a minor role for LXR in the maintenance of the transcriptome or suggesting that alteration of LXR in fully differentiated macrophages has not major effects in the maintenance of the transcriptome of either M-MØ or GM-MØ. However, GW3965 diminished the expression of various genes of the “Antiinflammatory gene set” in M-MØ, what constitutes a first indication of the ability of LXR activation to limit the acquisition of the “Antiinflammatory gene set”. The analysis of M-MØ or GM-MØ after siRNA-mediated silencing of LXRα, LXRβ or both (figure 29) showed that LXR protein expression was reduced by almost 50%, albeit the simultaneous silencing of both proteins was not effective in depleting LXRβ expression (figure 29B). In any event, no obvious effects were seen on the expression of the “Pro- inflammatory gene set” and “Antiinflammatory gene set” (figure 29C), further suggesting that LXR factors are not relevant for maintenance of the human macrophage phenotype. Results 75 Figure 28. Effect of LXR modulation by synthetic agonists on the expression of polarization- specific genes. A. Schematic representation of the in vitro treatment of M-MØ and GM-MØ with LXR agonist GW3965 or LXR inverse agonist GSK2033 for 24 or 48 hours. B. Expression of M-MØ-specific genes in M-MØ treated for 24 and 48 hours with GW3965 (top) and GSK2033 (bottom). C. Expression of GM-MØ-specific genes in GM-MØ treated for 24 and 48 hours with GW3965 (top) and GSK2033 (bottom). ABCA1 serve as readout of LXR activity. In all cases, mean ± SEM of four independent donors is shown. Paired-t-test was used to compare between groups and a pvalue<0.05 was considered as statistically significant *p<0.05, **p<0.01, *** p<0.001, **** p<0.0001, ns: non-significant. Results 76 Figure 29. Effect of LXR silencing on the expression of polarization-specific genes. A. Schematic representation of the in vitro strategy to deplete LXR in M-MØ and GM-MØ. B. LXR protein expression in human M-MØ and GM-MØ transfected with siRNA specific for NR1H3 and NR1H2 or both for 24 hours. Representative images for western blot and quantification (bottom) are shown. C. Expression of M-MØ-specific genes in M-MØ (top), and GM-MØ-specific genes in GM-MØ (bottom) transfected with siRNA for NR1H3 and NR1H2 or both for 24 hours. For all cases, mean ± SEM of two to five independent donors is shown. Paired-t-test was used to compare between groups and a pvalue<0.05 was considered as statistically significant *p<0.05, **p<0.01, *** p<0.001. Results 77 Modulation of LXR modifies the monocyte-to-macrophage differentiation in response to M-CSF or GM-CSF Next, we treated monocytes at different times along the monocyte-to-macrophage differentiation process with a single dose of LXR agonist GW3965 and/or LXR inverse agonist GSK2033 (GSK2033 one hour prior to GW3965) (figures 30A and 31A). In this experimental system, LXR activity modulation had striking effects on the “Proinflammatory gene set” and “Antiinflammatory gene set” expression as activation of LXR promoted macrophages to acquire a more proinflammatory state while inactivation of LXR skewed macrophages towards a more antiinflammatory state. In M-MØ, GW3965 treatment decreased expression of all genes analyzed, while GSK2033 treatment increased expression of some genes of the “Antiinflammatory gene set” (figure 30B). In GM-MØ, LXR activation increased the expression of most of the “Proinflammatory gene set” genes while LXR inactivation diminished expression of some of them (figure 31B). Besides, we detected that timing of the treatment was important. Treatment with LXR agonists at day 0 showed the strongest effects, which progressively decreased at later times. Indeed, analysis of the expression of some genes of the “Proinflammatory gene set” in M-MØ (INHBA, MMP12, TNF and PPARG) and some genes of the “Antiinflammatory gene set” in GM-MØ (IGF1, CD163, CCL2 and IL10) further supported the above conclusion (figure 30C, figure 31C), with GW3965 having more potent effects in M-MØ and GSK2033 showing stronger effects in GM- MØ. Since ABCA1 expression reflected the specificity of both GW3965 and GSK2033 and GSK2033 impeded the GW3965 transcriptional effects, these results indicate that LXR activity controls the acquisition of the gene profile of monocyte-derived macrophages in response to either M-CSF (M-MØ) or GM-CSF (GM-MØ). Results 78 Figure 30. Transcriptional effect of modulation of LXR activity along M-MØ differentiation. A. Schematic representation of the in vitro generation of M-MØ in the presence of LXR agonist GW3965 (GW-M- MØ), LXR inverse agonist GSK2033 (GSK-M-MØ) or both (GW/GSK-M-MØ) at different time points along the differentiation process. B. Expression of M-MØ-specific genes in CNT-M-MØ, GW-M-MØ, GSK-M-MØ or GW/GSK-M-MØ, generated in the presence of GW3965 and GSK2033 for 2, 5 or 7 days. ABCA1 was used as readout of GW3965 and GSK2033 efficacy. C. Expression of GM-MØ-specific genes in CNT-M-MØ, GW-M-MØ, GSK-M-MØ or GW/GSK-M-MØ, generated in the presence of GW3965 and GSK2033 for 7 days during the differentiation process. In all cases, mean ± SEM of three independent donors is shown. Paired-t-test was used to compare between groups and a pvalue<0.05 was considered as statistically significant *p<0.05, **p<0.01, *** p<0.001. Legend box refers to panels B and C. Results 79 Figure 31. Transcriptional effect of modulation of LXR activity along GM-MØ differentiation. A. Schematic representation of the in vitro generation of GM-MØ in the presence of LXR agonist GW3965 (GW-GM- MØ), LXR inverse agonist GSK2033 (GSK-GM-MØ) or both (GW/GSK-GM-MØ) at different time points along the differentiation process. B. Expression of GM-MØ-specific genes in CNT-GM-MØ, GW-GM-MØ, GSK-GM-MØ or GW/GSK-GM-MØ, generated in the presence of GW3965 and GSK2033 for 2, 5 or 7 days. ABCA1 was used as readout of GW3965 and GSK2033 efficacy. C. Expression of M-MØ-specific genes in CNT-GM-MØ, GW-GM-MØ, GSK-GM-MØ or GW/GSK-GM-MØ, generated in the presence of GW3965 and GSK2033 for 7 days during the differentiation process. In all cases, mean ± SEM of three independent donors is shown. Paired-t-test was used to compare between groups and a pvalue<0.05 was considered as statistically significant *p<0.05, **p<0.01, *** p<0.001. Legend box refers to panels B and C. Results 80 Considering the above results, we performed RNA sequencing on macrophages differentiated in the presence of GW3965, GSK2033 or both since day 0 of the differentiation process (Figures 7 and 8) in order to get a full picture of the role of LXR in the acquisition of the M-MØ and GM-MØ transcriptomes. Using adjp<0.05 and |log2FC|>1 as threshold parameters to identify Differentially Expressed Genes (DEG), a large number of DEG were found among the different experimental conditions in M-MØ (Table 3) and GM-MØ (Table 4). In the case of M-MØ (figure 32A) we observed that 402 genes were upregulated and 313 genes were downregulated in GW-M-MØ, whereas 36 genes were upregulated and 87 genes were downregulated in GSK-M-MØ (figure 32B), and 2 genes were upregulated and 7 genes were downregulated in GW/GSK-M-MØ. Regarding GM-MØ (figure 33A), 229 genes were upregulated and 145 genes were downregulated in GW-GM-MØ, whereas 121 genes were upregulated and 232 genes were downregulated in GSK-GM-MØ (figure 33B), and 95 genes were upregulated and 98 genes were downregulated in GW/GSK-GM-MØ. These results confirmed that GW3965 has a greater transcriptional effect on M-MØ and that GSK2033 exhibits a more potent action on GM-MØ. Moreover, GW3965 and GSK2033 worked as expected on the expression of the LXR-dependent gene set extracted from344 (figure 32D and 33D). Then, we assessed the expression of the “Proinflammatory gene set” and “Antiinflammatory gene set” in the transcriptome of GW-M-MØ and GSK-M-MØ using GSEA, and also compared the “Proinflammatory gene set” and “Antiinflammatory gene set” with the DEG found in the comparison of GW-M-MØ or GSK-M-MØ with CNT-M-MØ. GSEA (figure 32D) showed that, compared to control M-MØ, GW-M-MØ have a higher expression of the “Proinflammatory gene set” while GSK-M-MØ exhibits a global lower expression of this gene set, and the opposite result was observed in the case of the “Antiinflammatory gene set”. Results of these GSEA analyses were additionally represented using the Normalized Enrichment Score (NES) and False Discovery Rate (FDR) (figure 32E) for an easier visualization of the data. This data is extended by the analysis of only the DEG (figure 32F, 32G). Comparison of the “Proinflammatory gene set” and “Antiinflammatory gene set” with the DEG found in GW-M-MØ and GSK-M-MØ revealed that the expression of 20% of the genes of the “Antiinflammatory gene set” were significantly diminished in GW-M-MØ, whereas GSK2033 exerted a weaker effect on the expression of genes of the “Proinflammatory gene set” and “Antiinflammatory gene set”. Analysis on the transcriptome of GW-GM-MØ and GSK-GM-MØ using the same procedure (figure 33D and 33E) indicated that GSK2033 strongly upregulated the majority of the genes of the “Antiinflammatory gene set” and downregulated the genes of the “Proinflammatory gene set”, whereas GW3965 treatment had more ambiguous effects. Comparison of gene sets yielded similar conclusions, as GSK2033 significantly upregulated 18 genes of the “Antiinflammatory gene set” and downregulated 26 genes of the “Proinflammatory gene set”, whereas GW3965 treatment significantly upregulated and downregulated a similar number of genes of both gene sets (figure 33F-G). Altogether, these results demonstrate that GW3965 has a greater effect on the M-MØ-specific transcriptome and that GSK2033 exhibits a more potent action on the GM-MØ-specific gene profile. This conclusion was further confirmed in a Principal Component Analysis comparing DEG of GW-M-MØ, GSK-M-MØ, GW/GSK/GM-MØ and their GM-MØ siblings (figure 34A). In addition, further analysis comparing the DEG in GW-M-MØ, GSK2033-M-MØ or GW-GM-MØ and GSK-GM-MØ with the genes specifically regulated along the M-CSF- Results 81 dependent and GM-CSF-dependent macrophage differentiation confirmed the relevance of LXR in the monocyte-to-M-MØ and monocyte-to-GM-MØ differentiation process (figure 34B). Results 82 Figure 32. Analysis of the transcriptome of LXR-modified M-MØ. A. Schematic representation of the in vitro generation of M-MØ in the presence of LXR agonist GW3965 (GW-M-MØ), LXR inverse agonist GSK2033 (GSK-M-MØ) or both (GW/GSK-M-MØ) for 7 days during the differentiation process. B. Number of differentially expressed genes (|log2fold|>1 and padj<0.05) in GW-M-MØ and GSK-M-MØ compared to vehicle-treated cells (CNT-M-MØ). C. Gene Set Enrichment Analysis (GSEA) of the LXR-dependent gene set 344 on the ranked comparison of the indicated transcriptomes. D. GSEA of the Proinflammatory gene set and Antiinflammatory gene set on the ranked comparison of the indicated transcriptomes. E. Representation of Normalized Enrichment Score (NES) and False Discovery Rate (FDR) of the GSEA analysis of GW-M-MØ, GSK-M-MØ and GW/GSK-M- MØ compared with M-MØ (bottom) and GM-MØ (top) specific gene set. F-G. Comparison of the genes included within the indicated gene sets. Results 83 Figure 33. Analysis of the transcriptome of LXR-modified GM-MØ. A. Schematic representation of the in vitro generation of GM-MØ in the presence of LXR agonist GW3965 (GW-GM-MØ), LXR inverse agonist GSK2033 (GSK-GM-MØ) or both (GW/GSK-GM-MØ) for 7 days during the differentiation process. B. Number of differentially expressed genes (|log2fold|>1 and padj<0.05) in GW-GM-MØ and GSK-GM-MØ compared to vehicle-treated cells (CNT-GM-MØ). C. Gene Set Enrichment Analysis (GSEA) of the LXR-dependent gene set 344 on the ranked comparison of the indicated transcriptomes. D. GSEA of the Proinflammatory gene set and Antiinflammatory gene set on the ranked comparison of the indicated transcriptomes. E. Representation of Normalized Enrichment Score (NES) and False Discovery Rate (FDR) of the GSEA analysis of GW-GM-MØ, GSK-GM-MØ and GW/GSK-GM-MØ compared with M-MØ (bottom) and GM-MØ (top) specific gene set. F-G. Comparison of the genes included within the indicated gene sets. Results 84 Figure 34. Effect of modulation of LXR activity on the expression of genes regulated along monocyte-to-macrophage differentiation. A. Principal Component Analysis (PCA) of Differentially Expressed Genes (DEG) of M-MØ and GM-MØ generated in the presence of LXR agonist GW3965 (GW-M-MØ; GW-GM- MØ), LXR inverse agonist GSK2033 (GSK-M-MØ; GSK-GM-MØ) or both (GW/GSK-M-MØ; GW/GSK-GM-MØ) for 7 days during the differentiation process. B. Left, number of genes downregulated or upregulated in GW-GM-MØ or GSK-GM-MØ in the total of genes downregulated or upregulated in the monocyte (Mo) to GM-MØ transition. For every group, the number of genes up or downregulated in GW-GM-MØ or GSK-GM-MØ is shown. Right, number of genes downregulated or upregulated in GW-M-MØ or GSK-M-MØ in the total of genes downregulated or upregulated in the monocyte (Mo) to M-MØ transition. For every group, the number of genes up or downregulated in GW-GM-MØ or GSK-GM-MØ is shown. Results 85 TABLE 3. M-MØ DIFFERENTIALLY EXPRESSED GENES UPON LXR MODULATION GW-M-MØ UP GW-M-MØ DOWN GSK-M-MØ UP GSK-M- MØ DOWN GW/GSK -M-MØ UP GW/GSK -M-MØ DOWN SMFSD6 C20orf197 FCGBP CD59 GTF2IP1 ABCG1 YWHAH GPR82 SOWAHD SLC45A3 SFRP4 LRP3 DAB2 OLMALINC IL18BP IL2RA TAGLN2 MERTK MAT1A WWP1 GLCCI1 ABCA1 SCIMP TNFRSF21 REV3L TPRG1-AS1 FBLN5 GPR155 CHIC1 TNC CD300A ENPP2 DOCK5 ZMYND15 EYA2 SELL IL18BP GPR82 PDK4 ARL4C LAPTM5 FAM43A LINC02073 TMEM119 STK32B DZIP1L ADAMTS10 CD320 DCHS1 PLEKHG5 DBP XYLB SDC3 JAK3 SLC25A35 MTMR11 KCTD4 ADORA3 ETV5 SMPDL3A EEPD1 HIPK2 ITPR3 THBS1 CCDC170 LGI2 TRIM54 PDCD1LG2 DST CHI3L2 ARNT2 RNF144A FAM174B APOE HLA-DQA1 PLSCR1 HAL LGI2 CAPN5 JPH4 SCD TKT KHDRBS3 WWC1 GAS6 RAB3IL1 APOC1 TSPAN14 RARA-AS1 FAM177B IL10 CHST15 PNPLA3 TM7SF3 IL1R1 SCAMP5 MYO10 MLC1 SREBF1 VOPP1 MFGE8 VCAM1 DAB2 CAMKK1 MMP2-AS1 PIM2 LPIN1 LINC00942 PRR5 PCBP1-AS1 SPON2 ZC3H12A CLDN23 LYVE1 STAT1 GNG12 FABP4 HSD17B8 IRAK2 TAFA4 FES PDK4 NES CD55 APOE TFAP2C SLCO2B1 LRRC4 MYLIP POLE4 NTSR1 FOLR2 DTNB DTX1 FADS2 PYGL OLMALINC ADGRL3 BDH1 THBS1 AKR1C3 OPN3 ATP8B1 PLCH1 SNX6 FSCN1 KCNMA1 ZDHHC9 TFPI MLC1 MGLL SUSD3 TNFRSF21 AK9 ACSL1 FCER2 RN7SL138P KLF2 SLC45A3 SINHCAF PPARG SPNS2 CREM LYNX1 CD226 BTG3 ECE1 CFH C2 EYA2 NR1H3 ITGAL HK2 F13A1 LXN ARHGAP20 SPATA25 SLITRK4 MYO9A CES3 KIAA0895L HS3ST2 FASN MMAB OAF ABCA8 C1orf127 CD28 KL UGCG ARRDC3 PKD1L3 AP2A2 ALS2CL SLC40A1 FCHO1 MIR210HG HMCN1 S1PR2 BMP2 TMEM135 LSS GUCY1B1 LRRC4 RPS6KA2 PGA5 ABCD1 SYT11 KCNE1 AKAP6 GLMP MLXIPL DHCR7 CD180 NAALADL1 SCN9A SLC18B1 PGA3 ARL4C NFIL3 HECW2 TRIM50 CYSLTR2 FGF13 KCNMB4 SLC27A3 PDK4 CD200R1 ARMC9 LYVE1 DLL1 CAMK2D B9D1 BMP2 IGSF22 MID1IP1 C1orf54 AK4 RPS6KL1 IFI44 LPCAT3 TTPAL SLC29A2 RASAL1 ECM1 S1PR1 LPCAT2 DHCR24 DIRC3 OAS3 CD82 AKNA CD1D AFF3 BLNK LDLR PIGH MAFF C3orf70 PCBP1-AS1 FADS1 RAPGEF2 UST PDGFB MAP2K6 MIR155HG GPCPD1 SLC25A15 DNMBP-AS1 IRF2BPL TIFAB ACP2 VEGFA ALK GIMAP2 CXXC5 MAP3K20 LHFPL6 CLEC4GP1 IFITM2 SYTL3 ARHGEF18 NEK10 TMEM236 LIMA1 DHCR24 FOXO1 FADS1 SEMA3A BAIAP2 GFRA2 BHLHE41 PCNX2 DTX1 ITM2C CD244 GPR65 LINC00937 F2R PLS1 CXCR4 RPARP-AS1 GPR82 ABCA9 IGFBP4 KCNK13 USP45 TMEM135 GSDMA TMEM173 DUSP5 ACVR1B BTBD11 SYT6 APOL1 CORO7 PTPN13 SDC3 TLR3 GATM CDCA7L NUAK2 SLC44A2 MAMDC2 ADAMTS10 EPN1 ACO1 TRAF3IP2 CCL13 MYO7A EEPD1 HPSE LINC02185 CLEC4G PRSS36 GBP5 PLTP ACSL3 HPGDS GNPDA1 C3 FMNL2 SLC29A1 RHPN2 LSR TNRC6C-AS1 DLEU7 PGM2L1 ALS2CL FAXDC2 CA11 PAQR8 CXCR4 OLFML3 RHOU HLA-DOA GPRIN3 LPCAT3 CMBL TMEM255B CLEC4E SEMA4B NR1H3 TMEM273 CIITA FLVCR2 SLC25A23 LONRF1 IL2RA AFAP1 RUNX2 TRAF1 CDCA7L ABCA6 ASRGL1 MMP25 LY75 CLEC4D LINC00173 ZC3H12D LILRB4 KCNJ2 CAPN11 CNGA1 C1orf112 ACSL3 ALDOC CCDC151 TNFRSF11A FCHSD2 MYCL CRIM1 SEL1L3 KLHL13 CYP4V2 ARG2 GTDC1 FADS2 PLXDC1 CAMK1 TKT NECTIN1 KLHDC8B FAM174B MS4A4E PTK2 Results 86 MID1IP1 ITGA1 PRLR SYT1 SPHK1 ATP11C LUCAT1 S100B OXCT1 GBP2 FARP1 CARD14 ADGRG6 ENTPD1 INSIG1 PAG1 TMCC3 IGF2BP3 SUSD1 KIF3C MPRIP DHCR7 GPBAR1 FSTL3 LONRF1 TSC22D3 C3 GIMAP5 PITHD1 SORL1 BLOC1S2 FXYD2 RAB3IL1 TXK CD320 TRIM16 FBLIM1 RN7SL187P AMDHD2 ADAMTS10 TNRC6C-AS1 PLIN2 KCNJ5 GARNL3 MAN1A1 SQLE GPC1 ABCG2 CCDC200 DPEP2 MARVELD1 ABCB4 SUSD3 TMEM86A JAML C3orf62 PITPNM2 MRVI1 ACRBP LYZ PRKAG2-AS1 DACT1 GPR141 HLA-DMB STARD4 CYTIP ABTB2 ROR2 HAGHL RAB20 XYLT1 MCEMP1 DMD TNFAIP2 ALDOC BZW2 TRPV4 ANTXR1 SLC2A8 QPRT RUNX2 TMEM63C CCL18 FAT2 WASF1 CLEC4E SOCS2 TNS3 ABCA3 ABCA1 LINC02798 CRYBB1 NIPSNAP3B C17orf67 S100A9 PLA2G7 SENP8 GPR35 HAMP DEXI FAM102B KRT36 PCDH12 NR1D1 DZIP1L SREBF1 NRG1 C5orf30 HMGCR PCSK5 KITLG PYROXD2 GALNS FNDC4 WNT5B HLA-DRB1 MSMO1 MCTP2 TLN2 MROH6 CCND3 ASAP2 COL18A1 RCBTB2 ZNF436 RGL3 PLEKHA7 CLEC4A KMO CACHD1 SIDT1 GIMAP4 SSBP3 IRS1 TNFSF18 CD4 GBP2 SLC46A2 ATP1B1 TRIM32 OSBPL8 SPOCK1 CSGALNACT1 DYRK4 RDH11 DAPK2 HGF ALOX5AP KLHL5 LYPD1 LILRB5 PPP1R21 ETV5 PMAIP1 HSF4 TNFSF13 KBTBD11 CD82 C1QA IQCE SMAD6 LILRA1 EPHB3 RFLNB MYCL P2RY13 LINC01480 GLCCI1 COQ2 MYO5B AATBC BLVRB GDF11 GPRC5C KLF2 PEAK1 HEG1 KIF3C STON2 CCL3 MMP2-AS1 ACSM4 GNB5 CDH5 TPBGL SLC4A7 DLL1 RSAD2 CPNE2 VLDLR S100A8 ELOVL5 SYT17 LINC00639 PRXL2A SLC2A1 HLA-DQB2 ABHD12B SPATA41 CDH13 TUBA1A NT5E SPTLC3 IQSEC1 EFNA1 STK32B SYTL3 ACVRL1 IL12RB2 FGFR1OP2 LINC01500 IL12RB1 SNTB1 FASN PDCD1LG2 PIWIL4 AIM2 CCDC136 DGKG A2MP1 PLAAT4 STOM EGLN3 RARRES1 STARD4 AFF2 CD72 LRP8 IL1B FN3K TMEM154 JAKMIP2 NME8 LMTK2 SMPDL3A IL18BP COLQ AOX1 WLS UCK2 ARHGEF16 C1QC ACTN1 CACNB1 CHST13 CATSPER1 SLCO4C1 BNC2 SORL1 P3H2 PDGFC BCL2L1 APOC1P1 LY86-AS1 MGAM CLDN1 LGMN PLCB1 OR7E140P KIF17 CREB5 PHKA1 SRGAP1 NLRC4 CXADR SFXN2 NIBAN1 CD300A HELLPAR SGMS2 TPD52 ITSN1 WHRN CASR ACE TNFRSF21 CD34 MS4A4A CCL3L1 CNTNAP1 CCDC152 CCL3L3 PKD2L1 RAB38 MIR155HG COL11A2 MAPK12 GLT1D1 C6orf223 SDSL FNDC3B EXT1 FOXRED2 PRKCH SYNPO GYPC Results 87 SPIRE2 SRPX2 PCED1B FAR2 AKR1C7P AMIGO2 FXYD6 PNPLA3 GALNT14 CDK5R1 ABCG1 DISP1 PSD3 PKIB IL7 SOX4 AKR1C3 LINC00677 ACSL4 CYP26B1 ZKSCAN4 KCNMA1 COL9A3 JPH4 NEDD4L CFP FRMD3 ACACA CD244 AASS CDC42EP3 PTPRN DIP2C ST6GALNAC3 TRNP1 SESN3 PPP1R3G FAM135B GIMAP7 PID1 CCL19 CTSC HMGB3 SAMD12 LGALS3BP GLIS3 SIGLECL1 PRELID3A SMIM35 TREM1 LOXL3 PTK2 SCD SULT1B1 CXCL16 ANKRD22 SLC45A4 LILRB1 LIPM MAF FCN1 HEY1 SAMD4A TMEM38A PCOLCE2 GIMAP6 FLVCR2 LINC02561 STAT4 KCNK13 KCNJ10 M1AP NEDD9 OR7E62P COLGALT2 MAP3K7CL DOK6 CD209 FYN PZP CADM1 CXXC5 CD226 GRIN3A UTRN SCDP1 OAZ3 JUN TRIM9 CISH ARL4C RPL22P2 ZMYND12 CLEC5A KIAA1217 ARHGAP23 BCL2 ADCY1 RNASE1 RARA ITLN1 PDE7B KREMEN1 ORM1 SLC16A7 NT5DC3 FOXP2 UNC80 MCU CYP4F22 CMAHP SLC2A6 PPFIA2 DNM1 C1RL AKR1C8P ESR1 SLC29A3 ACKR3 CES4A MRO FABP6 BATF2 PLAUR GCKR TDRKH MARCKSL1 ADAMTS17 GIMAP1 LDLR CXCR2P1 MCC AUTS2 SCAT8 KANK2 MYLIP AKR1C4 PLB1 EEPD1 GRAMD1C HSD17B14 SPRY2 TMEM156 GNG2 MIR646HG CETP RPP25 INSIG1 GAPLINC NDST3 LTC4S Results 88 TABLE 4. GM-MØ DIFFERENTIALLY EXPRESSED GENES UPON LXR MODULATION GW-GM-MØ UP GW-GM-MØ DOWN GSK-GM- MØ UP GSK-GM-MØ DOWN GW/GSK- GM-MØ UP GW/GSK- GM-MØ DOWN DSYNJ2 RASAL1 FN1 CYSLTR2 CYB561A3 ROBO4 RGS16 EPN1 SLC9A2 N4BP1 ARHGEF16 HP CDK18 SPIRE1 ABCG1 CYTL1 PIK3CD GPD1 SLC39A6 MMP25 CCL7 PRDX2 TFEB CXCR2P1 S100Z GBP4 GLDN AKNA TSPAN5 LINC01614 TBC1D10C NBEAL2 F13A1 HCAR2 TSPAN4 CX3CR1 COQ2 HR GJB6 SLC9A7P1 HERPUD1 TRGC2 HPGD FADS2 ADAM19 PLA2G15 ABCG1 LINC02073 ARHGEF10L SQSTM1 TNC TMTC2 SIPA1L2 HMGA2 SRGAP3 CD1A SIGLEC12 OSM MEI1 CX3CR1 TMEM38A ACACA PID1 TNFSF8 CD226 PLEKHG5 DDO CAMKK1 PID1 HSPG2 SLCO4C1 HR TCF4 CACHD1 CCL2 RAPGEF3 CARD14 ABCA1 TMEM173 PDE4B SEMA3G KMO LPCAT3 LINC00996 FBP1 LINC01857 NEFL ZNF395 JAKMIP2 CD207 ZNF609 IL1B GPD1 TLE3 DYRK4 ANKRD22 SREBF1 LINC00900 HP EPN1 EMBP1 PCARE MRC2 TLR5 ADAM19 APOE ATP13A2 AOC3 PRCP EGR3 GJB2 PFKM HMOX1 CLDN1 HILPDA SLC25A35 PTGER3 FADS1 CD207 S100A12 GIMAP1 RGL1 P3H2 IL21R PLEKHA5 CLEC4F JAKMIP2 GPR35 NEFL PCCA WIPF3 HP ABCA9 CTDSPL ALOX15 ABCD1 CXCL10 TPD52L1 FCGR1B MERTK PTGER3 LTB ACSL1 COL14A1 MAMLD1 WFDC21P CAMP SYNJ2 H2AFY2 RUFY4 SLC9A7P1 SLC25A15 NTSR1 KIAA1671 GAREM2 FCGR3A SAMD4A CDH5 CCL1 ARL4C MMP10 PTK2 SERPINF1 FAM157B TSPYL2 ERBB3 LINC02345 FADS1 TCN1 ICAM1 PMAIP1 LGI2 IL4I1 NT5E SCG5 ZNF609 KRT4 BRWD3 CD209 KLK13 SLA TRPC6 OR6N1 EEPD1 ABCG2 LPIN1 AUTS2 CYP19A1 TTLL4 LIPM GPBAR1 TSPAN15 CLDN1 TUBA1A JADE3 S100A8 MGLL PPP2R2B NOD2 ELOVL5 HCAR2 OPHN1 HOMER2 CXCL5 HYOU1 AFF3 TACSTD2 LIN7A GAL RGS1 CACNB1 MMP8 NAV2 RSPO3 CAPN11 ARHGEF18 RGS16 INSIG1 CYP4F22 CP HSPA13 CCR2 FAM3C2 P2RY13 KDR CPT1A RASAL1 GLB1L2 KRBOX4 CLEC10A CD200R1 MT-ATP8 RHO SLC25A35 ARHGEF16 AOC3 CD209 IGFL3 PLTP NRIP1 S100A16 CTDSPL MMP25 ANKRD66 PRXL2B HMGA2 NES PHKA1 LIPG PCSK5 TSPAN5 FCRLB NMRAL2P MYLIP FUT7 SIGLEC17P CTSV APOC1 HR DUSP13 FICD STEAP1 ALDH1A2 TMEM135 DKK2 CD82 ABCG1 VCAN FBXO10 CD226 PDE1B PGM2L1 HCAR3 IQSEC1 CD1A LINC02407 IER3 GLB1L2 MCTP2 PMP22 SNAI1 PLIN2 CD226 PPBP PMP22 C20orf197 CRABP2 ASB2 LGI2 NAGK CACHD1 APLN LY9 GPR82 FCGR2B KIF3C CPE FLVCR2 LPCAT3 CYGB BTBD19 TRGC1 HTRA1 RCSD1 TMEM45A CDH23 IL1B VAT1L EPB41L4A-AS1 NFE2 VSIG2 DHCR7 PODXL GLIS3 EMBP1 MPZL2 AHRR EGLN3 SLC30A3 LTBP3 PCARE LRRK1 EGR3 LINC02009 MAFB AKAP5 ARL4C HIVEP2 COL1A1 SCRN1 CD207 KDR SLC7A5 CD1C AP1M2 CD226 CALHM1 NAAA GPR35 ALOX5 BPI NSFP1 METTL9 CRACR2A CD1A ZNF469 IRF4 OVOL1 DNAJB9 COL5A3 TSPOAP1 PCSK6 CCL17 CD1B TNC RXFP2 DLGAP1-AS2 AOC3 KLHL3 MYLIP SLC9B2 SIPA1L2 GPRC5B ABCG2 TRAF5 KRT4 AK1 TRPV4 CCL1 RARA FASN CCL23 SPATA18 RASGRP2 RIPOR2 SLA P3H2 GNG2 MYLIP SH3RF2 PRKCE S100A16 CD1B GPR82 SHANK3 SPATA12 ENPP2 BPI CMKLR1 SRPX2 IRF4 NBEAL2 COL22A1 LONRF1 SPATA25 SIGLEC11 LILRA5 FAM95B1 LINC01588 FXYD6 RET BMF LIPM NWD1 SLC22A18AS ACSM1 EGFL7 CD209 TACSTD2 PHKA1 MOCOS TOGARAM2 LACC1 FRMPD2 STAC2 TGFA KRT78 LY9 MMP12 COL1A1 RPS6KA2 CD207 FCRLA ETNK2 AKAP5 SLC12A2 TGFB2 MYOSLID LBH EPHA2 PTK2 ACVRL1 PTX3 FPR3 IL7R LINC00607 LINC00900 STON1 LINC00265 ABCA1 LINC02611 ACACA CD244 DLX4 HTRA4 FN1 CCND3 PTGS1 AP1M2 PELI2 GGT5 MMP10 TMEM255A TCN1 ETS1 LPCAT3 KRT79 ARHGEF18 SREBF1 PROC TBL2 RXFP2 DZIP1L CD1D SPATA20P1 SIPA1L1 MYORG VSIG4 RASAL1 VCAN LPCAT3 DHRS3 MGAT3 AKR1C7P PZP KANK4 OTOAP1 CLEC4F OSBP2 BMF KCNJ15 KLHDC8B GRAMD1C CHMP4C P2RX7 ALOX15 RGS1 LRP4 NR4A3 UTRN ABCA1 SIGLEC16 CHPF RGL3 SLCO4C1 GPR35 NPR1 FADS2 LAMP3 PADI2 IL10 TOX S100A4 PKD2L1 LINC02009 ACSL3 AFF2 LINC02320 SLC46A1 COL14A1 TMEM131L LILRB1 PROC ACSL1 PCSK6 COLQ C1S OLMALINC KREMEN1 AFF2 ASCL2 KIF3C HAPLN3 GIPR DDIT3 CALHM1 SLC2A3 LILRA1 ADGRD1 OAF GPR82 MGAT3 CCDC163 SCD CHI3L2 SREBF1 CD1E PARM1 SDC3 GOLGA7B MARCKS MIR646HG CTNNAL1 FASN SLC16A10 CSF2RB ANKRD22 AGRP CAMK2B PALD1 NEDD4L ARHGEF16 OVOL1 ABCA3 LINC01268 TNNI2 FAM20A MMP12 ALPK3 KLHDC8B CD1C USP53 SCDP1 NANOS1 STEAP1B MTMR11 PKIA ADGRE3 MID2 TMEM255B TMEM156 COL7A1 DDR1 S100A3 PTPN13 C1S REEP1 LBH CCL17 ME3 HIVEP2 FZD4 FSCN1 KLK4 ATP9A CASZ1 TCEA3 REEP1 BATF3 CD1A ADAM12 KCNJ5 SLC35F2 Results 89 GPR160 CXCR1 SHANK3 TRIB3 MYOSLID LAPTM4B C1R IRF4 NOS1AP NEURL2 CPE SELENOM GPC1 IGFBP7 LILRA5 ME3 CDCA7L SYNPO HPGDS ALK FXYD2 IL1RN LGALS9C GPBAR1 SLC25A15 SCD CST6 RBKS FCN1 MARCKSL1 ENPP2 C7orf57 SYN2 SCN8A PTGDS SGPP2 SORBS1 IQGAP3 SCD S100A13 EMB CLDN1 THBD RDH12 TNFSF10 SLC20A1 DAPK2 SLC30A3 SMAGP MAP2 S100A9 LGMN GLDN SLC27A3 ITGA9 DPP4 C1orf226 ACHE ZP3 CAMK1G FAM189A2 PMAIP1 STON2 DMPK CXorf21 PLTP MGLL CXCL2 MGAT3 EFNB1 CD300A BEX3 ACSL4 P3H2 SYTL1 TRIM46 AMIGO2 MIR155HG SMPDL3A TNFAIP8L3 TXLNB TNFRSF11B MARCO RND3 CAMP PLEK2 CFP CYTL1 PID1 ARL4C FHL1 CD38 NPR1 IL1RAP MRO SPP1 TNFSF10 CXCR2P1 LINC01001 ATP6V0E2-AS1 IRS1 S100A10 TMEM156 CNKSR3 AK8 SMPDL3A HAMP DTX1 APLN FOS SDC3 TNFRSF21 CD80 CLEC19A LINC01127 SEMA3A HECW2 MFGE8 PITPNM3 SLC9A7P1 EGLN3 SNCAIP MMP2 TNK2-AS1 CCL17 ME1 SERPINB2 TPM2 TIMP4 ITIH3 PPFIA4 CHRNA3 ATP8B1 ATP9A CAMSAP3 HTRA1 DMWD LIMCH1 PLD4 PITPNM3 TESPA1 LINC02185 CD244 ALPK3 PLPP1 SCAT8 PKD1L1 CADM1 ITGA2 TMEM135 ACKR3 ABCA9 ABCB4 GABRR3 CMKLR1 KCNJ5 UST GYPC MYMX LINC01588 DHCR7 TMC5 PODXL GDF15 TREM1 FADS2 ORM1 ROR1-AS1 TSPAN4 GPR171 SEMA3A GRB10 CTSV TNFAIP8L3 ITLN1 SEP3 SLIT3 A2MP1 GAL GSDMA VENTX CLEC11A KCNJ10 HSD11B1 STAMBPL1 SV2A ARL4D KLHDC7B LIPG ENC1 SLCO4C1 ZNF608 PDPN IKBKGP1 ITGA7 PPP2R3A DNAH3 PLCB1 SUSD3 ALS2CL PTPRF GYPC STRIP2 PPFIA2 ATP9A APOBEC3A TNFRSF21 GPD1L CXCL9 TPST1 HAMP TRIM54 FAM135B CXCL11 MTUS1 IL31RA RHO ABCB1 CLEC4M SEP3 CLEC19A CITED4 PLEKHA5 ORM1 DRAXIN LRRC32 STK32B ITGA9 INAVA PDE6B ST6GALNAC3 SLC51B CD1E CREB3L1 ZNF395 KCNH4 KDR EEPD1 INSM2 KCNJ15 PSAT1 AIM2 AIM2 CAMSAP3 MS4A4A ALDH1L2 MCEMP1 SYNGR3 RTL9 RET DMGDH PPP1R3G DMPK NCKAP5-AS2 KRT79 G0S2 SYNPO2 NR4A1 LINC00987 LTA4H CHAC1 GNAI1 HCAR2 CCR6 SPP1 MLXIPL AOX1 TSPAN7 SCUBE1 ARMH1 VNN3 PCED1B-AS1 SRPX2 RXFP1 GALNT12 SLC6A9 CD1E TMEM135 GUCY1A2 STUM BEX2 MIR210HG TRAF1 ADAMTS17 HAL BHLHA15 GIPR EFHC2 NCKAP5 CNKSR3 ADM2 AKR1C3 GUCY1B1 CCL19 IRF6 WNT5A ABCA6 EXT1 ITLN1 LRGUK CXCR5 AQP3 S1PR3 NDST3 RGS16 CLGN SMPDL3A MAP1LC3C RHBDD2 CADPS2 RARA DACT1 HGF HID1 KRT78 PGM2L1 TLN2 GAL ZNF114 SCIMP CD180 CFP CCDC88C PNPLA3 PKD2L1 AKAP5 TMEM130 CD300A CORO2A CDC42EP3 CXCL10 C1orf21 MYRF WFDC21P CD163 C7orf57 GAREM2 NHSL2 PPFIA4 SERPINF1 VNN2 HPSE PMAIP1 FAXDC2 MID2 CD209 SEC14L2 SLC9B2 AUTS2 TTC39B SLC2A1 JADE3 DNASE2B SHANK3 HOMER2 PDGFC METTL7B CACNB1 SLC16A10 PAQR5 CYP4F22 SDSL EXT1 Results 90 Gene ontology analysis of the transcriptomes as well as DEGs of GW3965-treated and GSK2033-treated macrophages were next used as a mean to find new functions that might be related to LXR activity on human macrophages. GSEA on the “Hallmark” database (ftp.broadinstitute.org://pub/gsea/gene_sets/h.all.v7.4.symbols.gmt) of the ranked comparison of the gene profile of GW-M-MØ (figure 35B) showed that GW3965 upregulated terms including genes related to TNFα signaling, hypoxia, inflammatory response, WNT beta catenin signaling and angiogenesis, as well as cholesterol homeostasis or lipid metabolism, which are well known to be controlled by LXR. Moreover, GW3965 downregulated terms related to interferon alpha and gamma response. For the GSK-M-MØ (figure 35C), only terms related to oxidative phosphorylation and MYC targets appeared significantly upregulated, and only Myogenesis and Peroxisome were significantly downregulated by GSK2033. For GW/GSK-M-MØ (figure 35D), only terms related to oxidative phosphorylation and MYC targets resulted significant. For GM-MØ (figure 35I), GW3965 upregulated terms associated to PI3K AKT signaling, MTORC1 signaling (as in M-MØ) or Peroxisome, and downregulated terms related to coagulation and MYC targets V1, whereas GSK2033 treatment (figure 35J) only upregulated the term associated to the unfolded protein response with the highest significance and downregulated protein secretion. Gene ontology analyses on the DEG in GW3965- and GSK2033-treated cells using Panther tool (tables 5 to 14) showed that the genes upregulated in GW3965-M-MØ (figure 35E) are mostly related to functions associated with cholesterol metabolism and homeostasis and lipid transport and synthesis, while genes downregulated in GW-M-MØ are related to chronic inflammatory responses, response to interferon gamma or regulation of MAPK activity. Conversely, no function was significantly associated to upregulated DEG in GSK-M- MØ (figure 35F), while downregulated DEG in GSK-M-MØ were also associated to cholesterol homeostasis or metabolism and lipid transport and synthesis. In the case of GW/GSK-M-MØ (figure 35G), downregulated genes were related to Interleukin 2-mediated signaling pathway and negative regulation of interleukin 10 production. Regarding GW-GM-MØ (figure 35L), functions associated with upregulated genes included cholesterol-related, like cholesterol transport, metabolism, lipoprotein transport, fatty acid metabolism or biosynthesis, as well as antigen processing and presentation, endogenous and exogenous lipid antigen via MHC class Ib, supporting again the involvement of LXR in macrophage polarization. In the case of the genes downregulated in GW-GM-MØ, we observed a relationship to MAPK cascade and regulation of their cascade. The genes upregulated in GSK-GM-MØ (figure 35M) were associated to endoplasmic reticulum unfolded protein response, interleukin 8-production and other immune-related functions, while GSK-GM-MØ-downregulated genes were significantly associated to cholesterol homeostasis, metabolism and lipid synthesis and transport and, again, antigen processing and presentation, endogenous and exogenous lipid antigen via MHC class Ib, regulation of interleukin-13 production, and positive regulation of angiogenesis. In the case of GW/GSK-GM-MØ (figure 35N), we only observed functions related to cholesterol and lipid homeostasis for upregulated genes, and antigen processing and presentation and endogenous and exogenous lipid antigen via MHC class Ib for downregulated genes. file:///C:/Users/acorbi/Downloads/wetransfer_tesis-version-final-docx_2021-11-23_1000/(ftp.broadinstitute.org:/pub/gsea/gene_sets/h.all.v7.4.symbols.gmt) Results 91 Altogether, gene ontology results showed a novel set of functions that might be potentially related to LXR activity, particularly:  In antiinflammatory macrophages (M-MØ): implication in inflammatory TNFα- and interferon-dependent signaling, angiogenesis and myogenesis, and a possible relation of these process with WNT signaling.  In proinflammatory macrophages (GM-MØ): involvement of coagulation, endoplasmic reticulum stress and unfolded protein response and in antigen presentation of endogenous and exogenous lipids. Results 92 Results 93 Figure 35. Gene ontology analysis of LXR-modulated macrophages revealed new functions related to LXR activity. A. Schematic representation of the in vitro generation of M-MØ in the presence of LXR agonist GW3965 (GW-M-MØ), LXR inverse agonist GSK2033 (GSK-M-MØ) or both (GW/GSK-M-MØ) for 7 days during the differentiation process. B. NES representation of statistically significant terms of the GSEA Hallmark database that are positively or negatively enriched in GW-M-MØ. C. NES representation of statistically significant terms of the GSEA Hallmark database that are positively or negatively enriched in GSK-M-MØ. D. NES representation of statistically significant terms of the GSEA Hallmark database that are positively or negatively enriched in GW/GSK-M-MØ. E. Fold enrichment representation of biological processes of the Panther database that are significantly up or downregulated in GW-M-MØ. F. Fold enrichment representation of biological processes of the Panther database that are significantly up or downregulated in GSK-M-MØ. G. Fold enrichment representation of biological processes belonging of the Panther database that are significantly up or downregulated in human GW/GSK-M-MØ. FDR<0.250 was considered statistically significant for GSEA analysis and padj<0.05 was considered significant for Panther analysis. H. Schematic representation of the in vitro generation of GM-MØ in the presence of LXR agonist GW3965 (GW-GM-MØ), LXR inverse agonist GSK2033 (GSK-GM-MØ) or both (GW/GSK-GM-MØ) for 7 days during the differentiation process. I. NES representation of statistically significant terms of the Hallmark database that are positively or negatively enriched in GW-GM-MØ. J. NES representation of statistically significant terms of the Hallmark database that are positively or negatively enriched in GSK-GM-MØ. K. NES representation of statistically significant terms of the Hallmark database that are positively or negatively enriched in GW/GSK-GM-MØ. L. Fold enrichment representation of biological processes of the Panther database that are significantly up or downregulated in GW-GM-MØ. M. Fold enrichment representation of biological processes of the Panther database that are significantly up or downregulated in GSK- GM-MØ. N. Fold enrichment representation of biological processes of the Panther database that are significantly up or downregulated in GW/GSK-GM-MØ. FDR<0.250 was considered as statistically significant for GSEA analysis and p value<0.05 was considered significant for Panther analysis. Results 94 TABLE 5. UPREGULATED GW-M-MØ PREDICTED FUNCTIONS GO biological process complete Fold enrichment P value raw FDR nucleoside transmembrane transport (GO:1901642) 23.23 6.44E-04 2.87E-02 negative regulation of cholesterol storage (GO:0010887) 21.68 9.19E-05 6.76E-03 mitral valve morphogenesis (GO:0003183) 21.68 9.19E-05 6.73E-03 negative regulation of macrophage derived foam cell differentiation (GO:0010745) 20.85 1.34E-05 1.55E-03 vascular wound healing (GO:0061042) 20.32 8.74E-04 3.55E-02 establishment of T cell polarity (GO:0001768) 18.07 1.15E-03 4.21E-02 positive regulation of cholesterol efflux (GO:0010875) 17.34 1.01E-07 3.12E-05 alpha-linolenic acid metabolic process (GO:0036109) 16.68 2.09E-04 1.28E-02 long-chain fatty acid import into cell (GO:0044539) 16.26 1.47E-03 5.00E-02 regulation of phosphatidylcholine metabolic process (GO:0150172) 16.26 1.47E-03 4.99E-02 positive regulation of phospholipid transport (GO:2001140) 15.48 2.65E-04 1.55E-02 regulation of triglyceride biosynthetic process (GO:0010866) 14.26 6.08E-05 4.98E-03 regulation of cholesterol biosynthetic process (GO:0045540) 13.55 7.49E-05 5.78E-03 regulation of membrane invagination (GO:1905153) 13.55 4.08E-04 2.08E-02 phospholipid homeostasis (GO:0055091) 13.55 4.08E-04 2.07E-02 positive regulation of fatty acid biosynthetic process (GO:0045723) 12.90 9.14E-05 6.75E-03 regulation of establishment of endothelial barrier (GO:1903140) 12.75 4.97E-04 2.40E-02 regulation of endothelial cell development (GO:1901550) 12.75 4.97E-04 2.40E-02 cellular response to fatty acid (GO:0071398) 12.51 1.72E-07 5.03E-05 negative regulation of anoikis (GO:2000811) 12.04 5.99E-04 2.74E-02 reverse cholesterol transport (GO:0043691) 12.04 5.99E-04 2.74E-02 glucan catabolic process (GO:0009251) 12.04 5.99E-04 2.73E-02 negative regulation of macrophage activation (GO:0043031) 12.04 5.99E-04 2.72E-02 high-density lipoprotein particle remodeling (GO:0034375) 12.04 5.99E-04 2.71E-02 cellular response to low-density lipoprotein particle stimulus (GO:0071404) 11.41 7.15E-04 3.09E-02 cellular polysaccharide catabolic process (GO:0044247) 11.41 7.15E-04 3.08E-02 long-chain fatty-acyl-CoA biosynthetic process (GO:0035338) 11.41 7.15E-04 3.07E-02 intermembrane lipid transfer (GO:0120009) 11.29 8.15E-08 2.99E-05 intracellular cholesterol transport (GO:0032367) 10.84 8.46E-04 3.45E-02 linoleic acid metabolic process (GO:0043651) 10.32 9.92E-04 3.84E-02 triglyceride biosynthetic process (GO:0019432) 9.85 1.16E-03 4.20E-02 release of cytochrome c from mitochondria (GO:0001836) 9.85 1.16E-03 4.19E-02 heparan sulfate proteoglycan metabolic process (GO:0030201) 9.68 2.97E-04 1.68E-02 cholesterol biosynthetic process (GO:0006695) 9.48 2.04E-05 2.26E-03 cellular response to sterol (GO:0036315) 9.43 1.34E-03 4.64E-02 response to cholesterol (GO:0070723) 9.34 3.43E-04 1.83E-02 phospholipid transport (GO:0015914) 7.66 5.73E-08 2.38E-05 lipid translocation (GO:0034204) 7.44 8.23E-05 6.22E-03 vasodilation (GO:0042311) 7.32 9.32E-04 3.71E-02 unsaturated fatty acid biosynthetic process (GO:0006636) 7.13 1.04E-03 3.97E-02 triglyceride homeostasis (GO:0070328) 7.13 1.04E-03 3.96E-02 negative regulation of leukocyte apoptotic process (GO:2000107) 7.07 3.42E-04 1.83E-02 lipid storage (GO:0019915) 6.95 1.16E-03 4.21E-02 regulation of sodium ion transmembrane transporter activity (GO:2000649) 6.77 1.40E-04 9.15E-03 positive regulation of cellular carbohydrate metabolic process (GO:0010676) 6.14 6.82E-04 2.98E-02 regulation of glucose import (GO:0046324) 5.81 8.89E-04 3.57E-02 cholesterol homeostasis (GO:0042632) 5.74 5.24E-05 4.46E-03 positive regulation of interleukin-1 beta production (GO:0032731) 5.42 1.24E-03 4.40E-02 negative regulation of tumor necrosis factor production (GO:0032720) 5.42 1.24E-03 4.39E-02 multicellular organismal water homeostasis (GO:0050891) 5.20 6.19E-04 2.79E-02 endothelial cell differentiation (GO:0045446) 5.16 2.67E-04 1.55E-02 organ growth (GO:0035265) 4.99 7.72E-04 3.26E-02 regulation of phagocytosis (GO:0050764) 4.71 4.71E-04 2.32E-02 intracellular receptor signaling pathway (GO:0030522) 4.65 4.31E-07 1.06E-04 phosphatidylcholine metabolic process (GO:0046470) 4.57 1.25E-03 4.41E-02 positive regulation of stress-activated MAPK cascade (GO:0032874) 4.13 5.18E-04 2.48E-02 viral entry into host cell (GO:0046718) 4.09 1.12E-03 4.16E-02 negative regulation of ion transport (GO:0043271) 4.03 1.58E-04 9.98E-03 retinoid metabolic process (GO:0001523) 4.01 1.25E-03 4.42E-02 negative regulation of transmembrane transport (GO:0034763) 4.00 6.49E-04 2.87E-02 glucose homeostasis (GO:0042593) 3.93 2.67E-05 2.70E-03 negative regulation of secretion by cell (GO:1903531) 3.82 4.65E-04 2.30E-02 Results 95 positive regulation of angiogenesis (GO:0045766) 3.73 2.97E-04 1.67E-02 regulation of insulin secretion (GO:0050796) 3.44 3.18E-04 1.74E-02 transmembrane receptor protein serine/threonine kinase signaling pathway (GO:0007178) 3.41 3.48E-04 1.85E-02 response to transforming growth factor beta (GO:0071559) 3.39 1.11E-03 4.14E-02 cellular response to interleukin-1 (GO:0071347) 3.37 6.62E-04 2.92E-02 aminoglycan metabolic process (GO:0006022) 3.26 1.44E-03 4.93E-02 cell-cell junction organization (GO:0045216) 3.22 9.33E-04 3.71E-02 calcium ion transmembrane transport (GO:0070588) 3.14 1.15E-03 4.22E-02 regulation of synapse organization (GO:0050807) 3.10 7.72E-04 3.26E-02 anatomical structure maturation (GO:0071695) 3.04 1.45E-03 4.96E-02 cellular response to tumor necrosis factor (GO:0071356) 2.82 1.08E-03 4.06E-02 positive regulation of cell migration (GO:0030335) 2.61 2.29E-05 2.43E-03 mononuclear cell differentiation (GO:1903131) 2.60 1.48E-03 4.98E-02 regulation of nervous system development (GO:0051960) 2.45 5.21E-04 2.48E-02 positive regulation of protein kinase activity (GO:0045860) 2.41 1.34E-04 8.83E-03 cell morphogenesis involved in neuron differentiation (GO:0048667) 2.39 5.91E-04 2.72E-02 neuron projection morphogenesis (GO:0048812) 2.39 2.95E-04 1.67E-02 regulation of response to biotic stimulus (GO:0002831) 2.37 8.90E-04 3.57E-02 positive regulation of hydrolase activity (GO:0051345) 2.36 1.20E-04 8.21E-03 positive regulation of response to external stimulus (GO:0032103) 2.32 3.89E-04 2.01E-02 axon development (GO:0061564) 2.32 1.47E-03 5.02E-02 inflammatory response (GO:0006954) 2.29 6.24E-04 2.79E-02 response to hormone (GO:0009725) 2.25 1.78E-05 2.01E-03 neutrophil degranulation (GO:0043312) 2.25 9.97E-04 3.83E-02 positive regulation of apoptotic process (GO:0043065) 2.23 6.81E-04 2.98E-02 cytokine-mediated signaling pathway (GO:0019221) 2.13 4.61E-04 2.30E-02 cellular metal ion homeostasis (GO:0006875) 2.13 1.28E-03 4.50E-02 regulation of cell adhesion (GO:0030155) 2.08 4.08E-04 2.09E-02 cell adhesion (GO:0007155) 1.93 3.31E-04 1.81E-02 phosphorylation (GO:0016310) 1.92 7.87E-04 3.31E-02 positive regulation of cell population proliferation (GO:0008284) 1.85 1.18E-03 4.23E-02 regulation of immune response (GO:0050776) 1.79 5.56E-04 2.59E-02 chromatin organization (GO:0006325) .08 6.71E-05 5.39E-03 detection of chemical stimulus involved in sensory perception of smell (GO:0050911) < 0.01 4.64E-04 2.31E-02 ribonucleoprotein complex biogenesis (GO:0022613) < 0.01 3.12E-04 1.74E-02 ncRNA processing (GO:0034470) < 0.01 7.32E-04 3.12E-02 TABLE 6. DOWNREGULATED GW-M-MØ PREDICTED FUNCTIONS GO biological process complete Fold enrichment P value raw FDR chronic inflammatory response (GO:0002544) 19.68 1.07E-04 2.88E-02 positive regulation of myeloid cell differentiation (GO:0045639) 5.46 1.74E-04 3.72E-02 peptidyl-tyrosine phosphorylation (GO:0018108) 4.95 2.53E-05 1.00E-02 regulation of viral life cycle (GO:1903900) 4.65 9.61E-05 2.66E-02 positive regulation of leukocyte differentiation (GO:1902107) 4.42 1.45E-04 3.46E-02 cellular response to interferon-gamma (GO:0071346) 4.30 1.76E-04 3.65E-02 regulation of adaptive immune response based on somatic recombination of immune receptors built from immunoglobulin superfamily domains (GO:0002822) 4.10 2.55E-04 4.68E-02 cell chemotaxis (GO:0060326) 4.07 6.67E-05 2.11E-02 positive regulation of MAP kinase activity (GO:0043406) 3.56 2.19E-04 4.18E-02 response to tumor necrosis factor (GO:0034612) 3.47 8.73E-05 2.56E-02 cytokine-mediated signaling pathway (GO:0019221) 2.91 5.20E-07 7.47E-04 regulation of immune effector process (GO:0002697) 2.85 1.02E-04 2.77E-02 regulation of cell-cell adhesion (GO:0022407) 2.82 1.14E-04 2.95E-02 regulation of inflammatory response (GO:0050727) 2.79 3.60E-05 1.29E-02 cell adhesion (GO:0007155) 2.53 1.23E-06 1.39E-03 regulation of leukocyte activation (GO:0002694) 2.44 2.41E-04 4.48E-02 positive regulation of cell population proliferation (GO:0008284) 2.42 4.66E-06 2.73E-03 regulation of cytokine production (GO:0001817) 2.30 1.48E-04 3.43E-02 negative regulation of multicellular organismal process (GO:0051241) 2.24 2.20E-05 8.93E-03 response to oxygen-containing compound (GO:1901700) 1.85 1.26E-04 3.12E-02 negative regulation of response to stimulus (GO:0048585) 1.81 8.90E-05 2.56E-02 developmental process (GO:0032502) 1.35 2.17E-04 4.24E-02 multicellular organismal process (GO:0032501) 1.31 2.08E-04 4.21E-02 Results 96 TABLE 7. UPREGULATED GSK-M-MØ PREDICTED FUNCTIONS GO biological process complete Fold enrichment P value raw FDR lipid transport involved in lipid storage (GO:0010877) > 100 1.02E-04 1.38E-02 regulation of phosphatidylcholine catabolic process (GO:0010899) > 100 1.70E-04 2.00E-02 regulation of neurofibrillary tangle assembly (GO:1902996) > 100 1.70E-04 1.99E-02 cellular response to prostaglandin D stimulus (GO:0071799) > 100 2.54E-04 2.82E-02 cholesterol biosynthetic process via lathosterol (GO:0033490) > 100 2.54E-04 2.78E-02 cholesterol biosynthetic process via desmosterol (GO:0033489) > 100 2.54E-04 2.76E-02 response to caloric restriction (GO:0061771) > 100 2.54E-04 2.75E-02 chylomicron remnant clearance (GO:0034382) > 100 8.16E-06 1.79E-03 phospholipid efflux (GO:0033700) 79.83 4.88E-07 1.68E-04 very-low-density lipoprotein particle clearance (GO:0034447) 79.83 4.71E-04 4.48E-02 positive regulation of cholesterol esterification (GO:0010873) 79.83 1.49E-05 2.97E-03 negative regulation of cholesterol storage (GO:0010887) 71.84 1.93E-05 3.71E-03 regulation of cholesterol biosynthetic process (GO:0045540) 59.87 5.50E-08 3.22E-05 alpha-linolenic acid metabolic process (GO:0036109) 55.26 3.74E-05 6.72E-03 positive regulation of triglyceride biosynthetic process (GO:0010867) 55.26 3.74E-05 6.64E-03 negative regulation of macrophage derived foam cell differentiation (GO:0010745) 55.26 3.74E-05 6.57E-03 very-low-density lipoprotein particle assembly (GO:0034379) 55.26 3.74E-05 6.49E-03 positive regulation of cholesterol efflux (GO:0010875) 47.90 1.45E-07 7.17E-05 intracellular cholesterol transport (GO:0032367) 47.90 2.78E-06 7.57E-04 positive regulation of fatty acid biosynthetic process (GO:0045723) 45.61 3.30E-06 8.69E-04 negative regulation of interleukin-10 production (GO:0032693) 39.91 8.75E-05 1.26E-02 reverse cholesterol transport (GO:0043691) 39.91 8.75E-05 1.25E-02 high-density lipoprotein particle remodeling (GO:0034375) 39.91 8.75E-05 1.23E-02 cholesterol efflux (GO:0033344) 38.32 6.11E-06 1.42E-03 positive regulation of steroid biosynthetic process (GO:0010893) 37.81 1.01E-04 1.38E-02 linoleic acid metabolic process (GO:0043651) 34.21 1.32E-04 1.74E-02 amyloid precursor protein metabolic process (GO:0042982) 31.24 1.68E-04 2.00E-02 positive regulation of alcohol biosynthetic process (GO:1902932) 29.93 1.89E-04 2.18E-02 unsaturated fatty acid biosynthetic process (GO:0006636) 25.21 2.77E-05 5.02E-03 negative regulation of lipid biosynthetic process (GO:0051055) 23.48 3.57E-06 9.11E-04 cellular response to lipoprotein particle stimulus (GO:0071402) 23.18 3.78E-04 3.88E-02 fatty-acyl-CoA biosynthetic process (GO:0046949) 23.18 3.78E-04 3.84E-02 cholesterol homeostasis (GO:0042632) 22.54 4.90E-09 5.16E-06 regulation of amyloid-beta formation (GO:1902003) 20.53 5.27E-04 4.90E-02 intermembrane lipid transfer (GO:0120009) 19.96 6.48E-05 1.03E-02 long-chain fatty acid transport (GO:0015909) 19.63 8.09E-06 1.83E-03 triglyceride metabolic process (GO:0006641) 15.35 2.49E-05 4.68E-03 response to fatty acid (GO:0070542) 14.74 1.96E-04 2.25E-02 intracellular receptor signaling pathway (GO:0030522) 13.30 1.09E-09 1.43E-06 regulation of glial cell differentiation (GO:0045685) 12.94 3.14E-04 3.31E-02 endothelial cell differentiation (GO:0045446) 11.40 4.98E-04 4.66E-02 negative regulation of cell activation (GO:0050866) 7.01 2.51E-04 2.81E-02 regulation of endocytosis (GO:0030100) 6.84 2.84E-04 3.01E-02 positive regulation of response to external stimulus (GO:0032103) 4.19 3.23E-04 3.36E-02 positive regulation of multicellular organismal process (GO:0051240) 2.84 8.28E-05 1.20E-02 regulation of multicellular organismal development (GO:2000026) 2.70 4.06E-04 4.07E-02 regulation of immune system process (GO:0002682) 2.65 7.55E-05 1.14E-02 regulation of cell population proliferation (GO:0042127) 2.61 1.49E-04 1.90E-02 TABLE 8. DOWNREGULATED GSK-M-MØ PREDICTED FUNCTIONS GO biological process complete Fold enrichment P value raw FDR interleukin-2-mediated signaling pathway (GO:0038110) > 100 2.01E-05 1.45E-02 negative regulation of interleukin-10 production (GO:0032693) > 100 1.50E-07 2.37E-03 lymphocyte apoptotic process (GO:0070227) > 100 6.51E-05 3.32E-02 negative regulation of T cell proliferation (GO:0042130) 80.24 6.90E-06 8.39E-03 positive regulation of T cell proliferation (GO:0042102) 55.61 2.00E-05 1.51E-02 adaptive immune response (GO:0002250) 14.23 1.34E-05 1.17E-02 Results 97 TABLE 9. UPREGULATED GW-GM-MØ PREDICTED FUNCTIONS GO biological process complete Fold enrichment P value raw FDR antigen processing and presentation, endogenous lipid antigen via MHC class Ib (GO:0048006) 55.17 6.61E-05 1.22E-02 antigen processing and presentation of lipid antigen via MHC class Ib (GO:0048003) 39.40 1.39E-04 1.97E-02 alpha-linolenic acid metabolic process (GO:0036109) 28.29 2.78E-05 6.19E-03 virion attachment to host cell (GO:0019062) 27.58 3.25E-04 3.77E-02 regulation of phosphatidylcholine metabolic process (GO:0150172) 27.58 3.25E-04 3.74E-02 regulation of cholesterol biosynthetic process (GO:0045540) 18.39 1.17E-04 1.80E-02 positive regulation of cholesterol efflux (GO:0010875) 18.39 1.58E-05 4.54E-03 fatty-acyl-CoA biosynthetic process (GO:0046949) 17.80 2.55E-06 1.30E-03 linoleic acid metabolic process (GO:0043651) 17.51 1.38E-04 1.99E-02 dendritic cell migration (GO:0036336) 15.99 1.89E-04 2.50E-02 T cell migration (GO:0072678) 15.32 3.44E-05 7.25E-03 plasma lipoprotein particle assembly (GO:0034377) 13.13 3.70E-04 4.15E-02 acylglycerol biosynthetic process (GO:0046463) 12.68 4.18E-04 4.43E-02 intracellular lipid transport (GO:0032365) 11.21 1.32E-04 1.95E-02 chemokine-mediated signaling pathway (GO:0070098) 10.34 4.96E-07 4.61E-04 regulation of alcohol biosynthetic process (GO:1902930) 9.58 2.60E-04 3.18E-02 lymphocyte chemotaxis (GO:0048247) 9.38 2.84E-04 3.45E-02 long-chain fatty acid transport (GO:0015909) 9.04 8.38E-05 1.38E-02 lipid translocation (GO:0034204) 9.01 3.37E-04 3.83E-02 regulation of lipid storage (GO:0010883) 8.67 3.97E-04 4.30E-02 response to fatty acid (GO:0070542) 8.49 1.16E-04 1.80E-02 leukocyte cell-cell adhesion (GO:0007159) 8.36 4.65E-04 4.81E-02 neutrophil chemotaxis (GO:0030593) 8.36 3.41E-05 7.28E-03 regulation of organic acid transport (GO:0032890) 7.99 1.57E-04 2.16E-02 phospholipid transport (GO:0015914) 7.00 9.78E-05 1.58E-02 regulation of leukocyte mediated cytotoxicity (GO:0001910) 6.73 3.77E-04 4.20E-02 phosphatidylcholine metabolic process (GO:0046470) 6.65 4.01E-04 4.31E-02 intracellular receptor signaling pathway (GO:0030522) 6.50 7.78E-08 2.05E-04 positive regulation of lipid metabolic process (GO:0045834) 5.34 7.36E-05 1.32E-02 positive regulation of small molecule metabolic process (GO:0062013) 5.11 2.46E-04 3.12E-02 response to ketone (GO:1901654) 5.06 1.89E-05 4.98E-03 response to nutrient (GO:0007584) 4.87 1.44E-04 2.01E-02 lipid homeostasis (GO:0055088) 4.78 3.79E-04 4.19E-02 positive regulation of immune effector process (GO:0002699) 4.71 1.54E-05 4.50E-03 cellular response to lipopolysaccharide (GO:0071222) 4.57 2.25E-04 2.89E-02 response to alcohol (GO:0097305) 4.36 3.20E-05 6.94E-03 response to tumor necrosis factor (GO:0034612) 3.64 3.12E-04 3.65E-02 extracellular matrix organization (GO:0030198) 3.36 1.09E-04 1.72E-02 inflammatory response (GO:0006954) 3.32 1.31E-05 4.05E-03 cellular response to hormone stimulus (GO:0032870) 2.78 2.91E-04 3.48E-02 response to organic cyclic compound (GO:0014070) 2.55 2.27E-05 5.53E-03 regulation of hydrolase activity (GO:0051336) 2.32 6.01E-05 1.13E-02 immune response (GO:0006955) 1.86 8.46E-05 1.38E-02 regulation of multicellular organismal process (GO:0051239) 1.82 1.43E-05 4.36E-03 regulation of signaling (GO:0023051) 1.63 5.59E-05 1.08E-02 regulation of cell communication (GO:0010646) 1.62 7.70E-05 1.31E-02 regulation of response to stimulus (GO:0048583) 1.58 3.20E-05 7.03E-03 positive regulation of cellular process (GO:0048522) 1.47 2.49E-05 5.79E-03 Results 98 TABLE 10. DOWNREGULATED GW-GM-MØ PREDICTED FUNCTIONS GO biological process complete Fold enrichment P value raw FDR positive regulation of estradiol secretion (GO:2000866) > 100 2.97E-04 4.83E-02 neutrophil aggregation (GO:0070488) > 100 2.97E-04 4.78E-02 chronic inflammatory response (GO:0002544) 30.02 2.20E-04 4.01E-02 negative regulation of lymphocyte migration (GO:2000402) 30.02 2.20E-04 3.96E-02 neutrophil chemotaxis (GO:0030593) 14.56 1.60E-07 8.41E-04 endodermal cell differentiation (GO:0035987) 14.01 2.64E-04 4.34E-02 defense response to fungus (GO:0050832) 13.74 4.77E-05 1.51E-02 acute-phase response (GO:0006953) 13.34 3.14E-04 5.01E-02 monocyte chemotaxis (GO:0002548) 13.34 3.14E-04 4.96E-02 collagen metabolic process (GO:0032963) 11.48 1.05E-04 2.41E-02 chemokine-mediated signaling pathway (GO:0070098) 10.51 3.37E-05 1.16E-02 antimicrobial humoral immune response mediated by antimicrobial peptide (GO:0061844) 9.61 1.27E-05 6.91E-03 response to lipopolysaccharide (GO:0032496) 5.27 4.37E-06 4.32E-03 regulation of ERK1 and ERK2 cascade (GO:0070372) 4.77 6.39E-05 1.63E-02 regulation of inflammatory response (GO:0050727) 4.33 1.30E-06 2.05E-03 positive regulation of MAPK cascade (GO:0043410) 4.27 1.54E-06 2.03E-03 negative regulation of response to external stimulus (GO:0032102) 4.01 3.37E-06 3.55E-03 neutrophil degranulation (GO:0043312) 3.78 5.29E-05 1.52E-02 positive regulation of cell migration (GO:0030335) 3.50 1.11E-04 2.41E-02 positive regulation of multicellular organismal process (GO:0051240) 2.35 1.10E-04 2.42E-02 gene expression (GO:0010467) 0.13 4.77E-05 1.48E-02 cellular nitrogen compound biosynthetic process (GO:0044271) 0.09 2.25E-04 3.99E-02 RNA metabolic process (GO:0016070) < 0.01 1.38E-05 6.83E-03 TABLE 11. UPREGULATED GSK-GM-MØ PREDICTED FUNCTIONS GO biological process complete Fold enrichment P value raw FDR regulation of macrophage activation (GO:0043030) 16.27 2.06E-05 1.09E-02 endoplasmic reticulum unfolded protein response (GO:0030968) 13.89 1.95E-07 3.85E-04 regulation of interleukin-8 production (GO:0032677) 10.72 1.34E-04 4.62E-02 regulation of response to endoplasmic reticulum stress (GO:1905897) 10.60 1.42E-04 4.77E-02 negative regulation of leukocyte activation (GO:0002695) 7.97 1.01E-05 6.67E-03 cellular response to lipopolysaccharide (GO:0071222) 7.05 7.80E-05 3.25E-02 positive regulation of cytokine production (GO:0001819) 4.10 9.23E-05 3.56E-02 apoptotic process (GO:0006915) 3.79 6.62E-07 9.51E-04 protein phosphorylation (GO:0006468) 3.72 2.74E-05 1.36E-02 negative regulation of multicellular organismal process (GO:0051241) 3.24 1.18E-05 7.17E-03 intracellular signal transduction (GO:0035556) 2.61 1.28E-05 7.50E-03 cell surface receptor signaling pathway (GO:0007166) 2.26 9.44E-06 6.49E-03 immune system process (GO:0002376) 2.01 1.06E-04 3.90E-02 regulation of biological quality (GO:0065008) 2.01 1.87E-06 2.11E-03 regulation of signal transduction (GO:0009966) 1.98 6.02E-05 2.57E-02 Results 99 TABLE 12. DOWNREGULATED GSK-GM-MØ PREDICTED FUNCTIONS GO biological process complete Fold enrichment P value raw FDR antigen processing and presentation, endogenous lipid antigen via MHC class Ib (GO:0048006) 74.89 1.47E-06 7.03E-04 antigen processing and presentation, exogenous lipid antigen via MHC class Ib (GO:0048007) 53.49 3.78E-06 1.25E-03 negative regulation of myeloid leukocyte mediated immunity (GO:0002887) 28.08 3.08E-04 3.01E-02 phospholipid efflux (GO:0033700) 23.40 4.82E-04 4.17E-02 positive regulation of interleukin-13 production (GO:0032736) 23.40 4.82E-04 4.14E-02 reverse cholesterol transport (GO:0043691) 20.80 7.65E-05 1.20E-02 high-density lipoprotein particle remodeling (GO:0034375) 20.80 7.65E-05 1.19E-02 regulation of cholesterol biosynthetic process (GO:0045540) 18.72 1.09E-04 1.48E-02 positive regulation of cholesterol efflux (GO:0010875) 14.98 2.34E-04 2.47E-02 positive regulation of T cell mediated cytotoxicity (GO:0001916) 12.91 3.91E-04 3.53E-02 cellular response to fatty acid (GO:0071398) 12.00 9.78E-05 1.37E-02 apoptotic cell clearance (GO:0043277) 10.40 1.81E-04 2.03E-02 intermembrane lipid transfer (GO:0120009) 9.75 2.39E-04 2.51E-02 positive regulation of lipid localization (GO:1905954) 7.00 3.08E-05 6.08E-03 retinoid metabolic process (GO:0001523) 6.93 3.27E-05 6.24E-03 response to retinoic acid (GO:0032526) 6.75 3.93E-05 7.07E-03 proteoglycan metabolic process (GO:0006029) 6.61 4.11E-04 3.69E-02 cholesterol homeostasis (GO:0042632) 6.61 4.11E-04 3.67E-02 positive regulation of cell junction assembly (GO:1901890) 6.42 1.60E-04 1.88E-02 long-chain fatty acid metabolic process (GO:0001676) 5.60 3.54E-04 3.27E-02 response to nutrient (GO:0007584) 5.51 2.27E-05 4.78E-03 vitamin metabolic process (GO:0006766) 5.33 4.71E-04 4.09E-02 fatty acid biosynthetic process (GO:0006633) 5.28 4.94E-04 4.17E-02 intracellular receptor signaling pathway (GO:0030522) 5.20 1.47E-05 3.22E-03 positive regulation of lipid metabolic process (GO:0045834) 4.83 3.50E-04 3.26E-02 female pregnancy (GO:0007565) 4.63 2.05E-04 2.26E-02 negative regulation of secretion (GO:0051048) 4.54 5.21E-04 4.38E-02 positive regulation of epithelial cell proliferation (GO:0050679) 4.34 3.21E-04 3.10E-02 regulation of protein localization to membrane (GO:1905475) 4.19 4.11E-04 3.65E-02 response to alcohol (GO:0097305) 4.07 1.22E-04 1.52E-02 inflammatory response (GO:0006954) 3.95 1.65E-07 1.18E-04 extracellular matrix organization (GO:0030198) 3.91 5.78E-06 1.69E-03 angiogenesis (GO:0001525) 3.83 5.46E-05 9.28E-03 regulation of angiogenesis (GO:0045765) 3.65 3.01E-04 2.96E-02 negative regulation of cell adhesion (GO:0007162) 3.61 3.29E-04 3.15E-02 regulation of cell-cell adhesion (GO:0022407) 3.20 1.04E-04 1.45E-02 wound healing (GO:0042060) 3.16 1.18E-04 1.48E-02 regulation of inflammatory response (GO:0050727) 3.07 5.84E-05 9.72E-03 cell junction organization (GO:0034330) 2.98 1.34E-04 1.62E-02 positive regulation of response to external stimulus (GO:0032103) 2.91 1.74E-04 1.97E-02 cell-cell adhesion (GO:0098609) 2.91 1.77E-04 2.00E-02 regulation of hormone levels (GO:0010817) 2.78 2.85E-04 2.85E-02 response to hormone (GO:0009725) 2.63 3.16E-05 6.09E-03 cytokine-mediated signaling pathway (GO:0019221) 2.59 1.91E-04 2.13E-02 positive regulation of intracellular signal transduction (GO:1902533) 2.34 7.27E-05 1.17E-02 response to organic cyclic compound (GO:0014070) 2.29 3.69E-04 3.39E-02 positive regulation of developmental process (GO:0051094) 2.21 5.73E-05 9.64E-03 locomotion (GO:0040011) 2.09 1.66E-04 1.91E-02 positive regulation of catalytic activity (GO:0043085) 2.04 5.22E-04 4.36E-02 immune response (GO:0006955) 1.94 2.56E-05 5.13E-03 animal organ development (GO:0048513) 1.66 1.16E-04 1.47E-02 cellular developmental process (GO:0048869) 1.55 4.90E-04 4.17E-02 RNA processing (GO:0006396) < 0.01 9.27E-05 1.32E-02 Results 100 TABLE 14. DOWNREGULATED GW/GSK-GM-MØ PREDICTED FUNCTIONS GO biological process complete Fold enrichment P value raw FDR antigen processing and presentation, endogenous lipid antigen via MHC class Ib (GO:0048006) > 100 5.50E-06 1.45E-02 antigen processing and presentation, exogenous lipid antigen via MHC class Ib (GO:0048007) 90.99 1.17E-05 2.31E-02 extracellular matrix organization (GO:0030198) 6.10 2.38E-06 1.26E-02 regulation of cell migration (GO:0030334) 3.57 2.03E-05 2.91E-02 tissue development (GO:0009888) 2.70 1.55E-05 2.44E-02 positive regulation of cellular process (GO:0048522) 1.78 7.03E-06 1.59E-02 TABLE 13. UPREGULATED GW/GSK-GM-MØ PREDICTED FUNCTIONS GO biological process complete Fold enrichment P value raw FDR alpha-linolenic acid metabolic process (GO:0036109) 66.01 9.89E-07 7.81E-03 linoleic acid metabolic process (GO:0043651) 40.86 5.11E-06 8.97E-03 fatty-acyl-CoA biosynthetic process (GO:0046949) 34.60 6.51E-07 1.03E-02 unsaturated fatty acid biosynthetic process (GO:0006636) 28.23 1.62E-06 6.40E-03 intracellular receptor signaling pathway (GO:0030522) 8.67 5.28E-06 8.34E-03 Results 101 To extend these results and dig into the functional role of LXR in macrophages, we next performed a clustering analysis using Genesis and a k-means clustering analysis on the DEG identified in GW- and GSK-differentiated macrophages. Five clusters were defined in the case of M-MØ (figure 36A) and seven clusters were defined for in GM-MØ-related cells (figure 37A), all of which includes all the GW3965 and GSK2033 dependent changes in gene expression. These analyses confirmed the previous conclusions that: 1) GSK2033 preferentially upregulates, and GW3965 downregulates, the expression of the “Antiinflammatory gene set” in M-MØ (figure 36B); and 2) most genes of the “Antiinflammatory gene set” are upregulated in GSK-GM-MØ (figure 37B). Of note, gene ontology analysis of the identified clusters confirmed the results obtained using GSEA on DEG (figure 36C, figure 37C). Results 102 Results 103 Figure 36. Clustering analysis of LXR-dependent differentially expressed genes in M-MØ. A. Expression of differentially expressed genes in M-MØ differentiated in the presence of LXR agonist GW3965 (GW-M-MØ), LXR inverse agonist GSK2033 (GSK-M-MØ) or both (GW/GSK-M-MØ) for 7 days after clustering using k-means. Heatmap illustrates the level of expression of each gene after normalization. The panel in the right part of the figure represents the variations of the expression of the genes of each cluster in the distinct cells. The number of genes included in every cluster is indicated. B. Identification of M-MØ-specific and GM-MØ-specific genes in each cluster. C. Gene ontology analysis of the genes within each cluster using the Panther database. Fold enrichment and p value of enriched terms are shown. Only biological processes significantly enriched (pvalue<0.05) are shown. Results 104 Results 105 Figure 37. Clustering analysis of LXR-dependent differentially expressed genes in GM-MØ. A. Expression of differentially expressed genes in GM-MØ differentiated in the presence of LXR agonist GW3965 (GW-GM-MØ), LXR inverse agonist GSK2033 (GSK-GM-MØ) or both (GW/GSK-GM-MØ) for 7 days after clustering using k-means. Heatmap illustrates the level of expression of each gene after normalization. The panel in the right part of the figure represents the variations of the expression of the genes of each cluster in the distinct cells. The number of genes included in every cluster is indicated. B. Identification of M-MØ-specific and GM-MØ- specific genes in each cluster. C. Gene ontology analysis of the genes within each cluster using the Panther database. Fold enrichment and p value of enriched terms are shown. Only biological processes significantly enriched (pvalue<0.05) are shown. Results 106 To further extend these results, we next compared the genes upregulated by GW3965 and downregulated by GSK2033 with currently known LXR target genes (table 2), and defined a list of novel putative LXR target genes. The list of 42 genes identified in upregulated GW- and downregulated GSK-M-MØ (figure 38A, 38B), included a number of SREBP targets (DHCR7, DHCR24, LDLR, INSIG1), cholesterol-related genes (RUNX2674,675, STARD4676,677), and genes related to macrophage activation or polarization (CLEC4E678, CD226679, MIR155HG680), macrophage involvement in cancer (DLL1681), macrophage responses and differentiation (CXCR4682,683), the gene encoding the CD82 receptor, important for bone marrow quiescence684, or the guanylate-binding protein GBP2-encoding gene, that controls interferon responses685. The list of 19 genes in downregulated GW- and upregulated GSK-M-MØ (figure 38C) included genes of the antiinflammatory gene set (THBS1, LGI2, RAB3IL1686–688) and genes associated to angiogenesis (LYVE1689,690), cellular communication (MLC1691,692), osteoclast differentiation (BMP2693,694) or macrophage activation and polarization (KLF2695–697, DAB2698,699). In the case of GM-MØ counterparts (figure 39A, 39B), the list was shorter and included genes of the “Proinflammatory gene set”, genes related to antigen presentation lipids to T cells (CD1A, CD1B and CD1E700–702) or inflammation132,155,156,703,704 and other aspects, like polarization (EXT1705, CLDN1706, CXCR2707,708), activation (HCAR2709,710, TNFS10711), inflammasome response (AIM2712,713), or cellular movement (RSG1714). The list of genes for downregulated GW- and upregulated GSK-GM-MØ included 5 genes (figure 39C), related to macrophages behavior in cancer715– 721 except for BPI, linked to antibacterial responses and bacterial phagocytosis716,722. Results 107 Figure 38. Analysis of LXR-dependent DEGs in M-MØ generated in the presence of either GW3965 or GSK2033. A. Schematic depiction of the in vitro generation of human M-MØ differentiated in the presence of LXR agonist GW3965 (GW-M-MØ), LXR inverse agonist GSK2033 (GSK-M-MØ) or both (GW/GSK-M-MØ) for 7 days. B. Comparison of DEGS in GW-M-MØ upregulated and GSK-M-MØ downregulated genes with the LXR targets gene set. C. Comparison of DEGs in GW-M-MØ downregulated and GSK-M-MØ upregulated genes with the LXR targets gene set. Results 108 Figure 39. Analysis of LXR-dependent DEGs in GM-MØ generated in the presence of either GW3965 or GSK2033. A. Schematic depiction of the in vitro generation of human M-MØ differentiated in the presence of LXR agonist GW3965 (GW-GM-MØ), LXR inverse agonist GSK2033 (GSK-GM-MØ) or both (GW/GSK-GM-MØ) for 7 days. B. Comparison of DEGS in GW-GM-MØ upregulated and GSK-GM-MØ downregulated genes with the LXR targets gene set. C. Comparison of DEGs in GW-GM-MØ downregulated and GSK-GM-MØ upregulated genes with the LXR targets gene set. Results 109 LXR instruct several transcription factors in macrophage differentiation After finding the link between LXR activity and the macrophage polarization state, we attempted to decipher the mechanisms that control this connection. For that purpose, we focused on previous data on the factors that determine macrophage polarization. First, we determined protein expression of MAFB and MAF, that control antiinflammatory polarization195-(Simón-Fuentes et al, unpublished), in GW-, GSK- and GW/GSK-M-MØ and GW-, GSK- and GW/GSK-GM-MØ (figure 40A). We found increased protein expression of both MAFB and MAF in GSK-M-MØ (figure 40B), an effect that was prevented in the presence of GW3965 (GW/GSK-M-MØ). A similar effect was observed in GM-MØ (figure 40C), where GW3965 treatment also diminished significantly MAF expression. All these effects are well in line with our previous results of a defined antiinflammatory effect of GSK2033 and proinflammatory effect of GW3965 on macrophages. Second, we investigated protein expression of IRF4 and production of their target CCL17, that have been defined to control GM-CSF-dependent macrophage polarization155,156. Besides that, the RNA-seq analysis that we performed earlier to define some new putative LXR target genes pointing out to IRF4 and CCL17 as candidates (figure 38). We found (figure 40D, E) that the expression of IRF4 was augmented in GW-M-MØ and GW-GM-MØ but at a higher extent in GM-MØ. GSK-M-MØ also showed an increase of IRF4 expression. For CCL17, the global production was higher for GM-MØ than M-MØ. In this sense, GW3965 increased CCL17 production in GM-MØ, in consonance with IRF4 increment, but decreased it in M-MØ. GSK-GM-MØ showed a decrease in CCL17 production. As other authors, we saw a correspondence between IRF4 expression and CCL17 production in GM-MØ but not in M-MØ where the increase in IRF4 expression did not translate to changes in CCL17. IRF4 increased expression in GW-GM-MØ is in line with our previous results, which pointed to a proinflammatory effect of GW3965. Third, PPARγ was defined as essential for GM-CSF dependent polarization and has an established relation with LXR39,247,723,724. We found that PPARγ (PPARG gene) mRNA expression was upregulated in GW-M-MØ and GW-GM-MØ and downregulated in GSK-M- MØ and GSK-GM-MØ (figure 40 E, G) in line with our previous results. Fourth, the implication of HIF transcription factor in M-CSF or GM-CSF-dependent polarization is not well defined yet, but several studies showed HIF1α guide LXR-dependent training potentiation ability311. Moreover, we determined that hypoxia and glycolysis were enriched in our LXR-altered macrophages (figure 35). We observed that HIF1α (HIF1A gene) mRNA expression was augmented in GW-M-MØ and diminished in GSK-M-MØ (figure 40H), a tendency that was not observed in GM-MØ (figure 40I). Concomitant with this, lactate levels significantly increase in supernatants of GW3965-M-MØ (figure 40H). These results confirmed a proinflammatory effect of GW3965 in M-MØ that might be dependent of HIF1α and lactate. Results 110 Figure 40. Several transcription factors are influenced by LXR in macrophage differentiation. A. Schematic representation of the in vitro generation of human M-MØ and GM-MØ differentiated in the presence of LXR agonist GW3965 (GW-M-MØ; GW-GM-MØ), LXR inverse agonist GSK2033 (GSK-M-MØ; GSK- GM-MØ) or both (GW/GSK- M-MØ; GW/GSK-GM-MØ) for 7 days. B. Protein expression of MAFB and MAF transcription factors in CNT- M-MØ, GW-M-MØ, GSK-M- MØ and GW/GSK-M-MØ. Representative images of western blot protein expression are shown. Vinculin was used as a loading control. C. Protein expression of MAFB and MAF transcription factors in CNT- GM-MØ, GW-GM-MØ, GSK- GM-MØ and GW/GSK-GM- MØ. Representative images of western blot protein expression are shown. Vinculin was used as a loading control. D. IRF4 protein expression and CCL17 production in CNT-M- MØ, GW-M-MØ, GSK-M-MØ and GW/GSK-M-MØ. A representative image of western blot protein expression is shown. GAPDH was used as loading control. E. IRF4 protein expression and CCL17 production in CNT-GM-MØ, GW-GM-MØ, GSK-GM-MØ and GW/GSK- GM-MØ. A representative image of western blot protein expression is shown. GAPDH was used as loading control. F. Average read counts of PPARG in CNT-M-MØ, GW-M-MØ, GSK-M-MØ and GW/GSK-M-MØ, as determined by RNAseq. G. Average read counts of PPARG in CNT-GM-MØ, GW-GM-MØ, GSK-GM-MØ and GW/GSK-GM-MØ, as determined by RNAseq. H. Average read counts of HIF1A in CNT-M- MØ, GW-M-MØ, GSK-M-MØ and GW/GSK-M-MØ, determined by RNAseq, and lactate production in their supernatants. I. Average read counts of HIF1A in CNT-GM-MØ, GW-GM-MØ, GSK-GM-MØ and GW/GSK-GM- MØ, determined by RNAseq, and lactate production in their supernatants. For CCL17, experiments represent the individual values plus the mean of four (M-MØ) or seven (GM-MØ) independent donors. For the rest cases, mean ± SEM quantification of three independent donors is shown. For all cases, paired-t-test was used to compare between groups and a pvalue<0.05 was considered as statistically significant *p<0.05, **p<0.01. Results 111 Next, we evaluated if we can modulate any of these factors to find if LXR were cooperating with them to exert their effects on macrophage differentiation. We try to deplete MAFB and IRF4 in monocytes but the experimental model didn’t allow us to have a successful elimination of these factors prior to LXR modulation. Besides, the HIF1α inhibitors we used did not show the expected effects in HIF1α targets genes. In this sense, we have the same issue using SREBP inhibitors; as we previously commented they are some of the principal factors LXR regulate in their control of lipid accumulation. Considering our limitations, we search for different strategies to uncover the implication of these transcription factors in LXR actions. We asked whether the MAFB downregulation induced by GW3965 could underlie its proinflammatory effects. Since GSK3-dependent phosphorylation leads to MAFB degradation, we used the specific GSK3β inhibitor CHIR99021618, that leads to incremented MAFB expression. So, monocytes were exposed to CHIR99021 and GW3965 and allowed to differentiate into M-MØ (figure 41A). MAFB expression was elevated by CHIR99021 in CHIR-M-MØ, while GW3965 was still capable of slightly downregulate MAFB in GW-M-MØ but CHIR maintains MAFB expression high in GW/CHIR-M-MØ (figure 41B). In terms of gene expression (figure 41C), CHIR99021 hindered the influence of GW3965 on several genes of the “Antiinflammatory gene set” (including FOLR2, IL10, CD163, CCL2, LGMN, CD209 and FCGBP) but not others (IGF1, HTR2B, STAB1 and CXCL2) in GW/CHIR-M-MØ. In line with these findings, exposure of M-MØ at day 5 (when MAFB expression is already high195) with both GW3965 and CHIR99021 resulted in similar results (data not shown). These results confirmed that modulation of GSK3β, and therefore MAFB expression, abrogates some of the proinflammatory effects of GW3965 in human macrophages, implying that MAFB partly mediates the inhibitory action of GW3965 on the acquisition of the “Antiinflammatory gene set”. Results 112 Figure 41. Molecular mechanisms underlying the macrophage polarizing effect of LXR activation. A. Schematic representation of the in vitro generation of human M-MØ differentiated in the presence of LXR agonist GW3965 (GW-M-MØ), GSK3β inhibitor CHIR99021 (CHIR-M-MØ) or both (GW/CHIR-M-MØ) for 7 days. B. Protein expression of MAFB in CNT-M-MØ, GW-M-MØ, CHIR-M-MØ and GW/CHIR-M-MØ. Representative images of western blot protein expression are shown. C. mRNA expression of antiinflammatory M-MØ-specific genes in CNT-M-MØ, GW-M-MØ, CHIR-M-MØ and GW/CHIR-M-MØ. ABCA1 was used as readout of the efficacy of GW3965. For all cases, mean ± SEM quantification of three independent donors is shown. Paired-t-test was used to compare between groups and a pvalue<0.05 was considered as statistically significant *p<0.05, **p<0.01, ***p<0.001. Results 113 LXR modulation alters responses of basal and activated macrophages We next addressed whether LXR modulation affects critical functions of macrophages, namely cytokine production, antitumoral activity, T cell activation and MTX response. First, we evaluated whether LXR activity modulation influences cytokine production by analyzing cell-conditioned media of GW-M-MØ, GSK-M-MØ and GW/GSKM-MØ (figure 42 and 43) in basal conditions or after LPS activation (18 hours). Compared to CNT M-MØ, GW-M-MØ produced higher levels of IL-1β, Activin A, CCL19 and lower levels of the antiinflammatory cytokine IL-10 (figure 42). This proinflammatory trend was confirmed after LPS stimulation, as GW-M-MØ secreted higher levels of TNF, IL-6, IFNβ and IL1β than CNT M-MØ. Moreover, although LPS-treated GW-M- MØ also secreted higher levels of IL-10, the fold induction was considerably higher for TNFα. Thus, since the proinflammatory effects of GW3965 treatment were impaired or abolished by GSK2033 (GSK-M-MØ and GW/GSK-M-MØ), these results confirm that modulation of LXR activity impacts the inflammatory activity of M-MØ, and that LXR activation prompts monocytes towards the generation of monocyte-derived macrophages with a higher pro- inflammatory transcriptional and cytokine profile. Similarly, the effects exerted by LXR modulation on the GM-MØ transcriptome were also translated into their cytokine secretion (figure 43). GW-GM-MØ produced lower levels of IL-10, IL-6, CCL2 and Activin A compared to CNT-GM-MØ. This distinct response was also observed after LPS stimulation, as GW-GM-MØ produced higher levels of TNFα, IL1β, IFNβ and CCL19 with an associated increase in IL-10 production at greater induction than TNFα. Lower levels of CCL2 and Activin A were also noted. In this case, both the anti- and proinflammatory actions of GW3965 were abrogated by GSK2033 presence (GW/GSK-GM- MØ). However, we observed a GSK2033-dependent increase of TNFα that was greater than the increment in IL-10 production. These results are in line with the transcriptomic results where we showed a change in the antiinflammatory and proinflammatory gene set under GW3965 influence. As a whole, cytokine results show that LXR activity enhancement by GW3965 tends to increase proinflammatory cytokine production. All these results are summarized in Table 15. Results 114 TABLE 15. CYTOKINE PRODUCTION IN M-MØ AND GM-MØ DIFFERENTIATED IN THE PRESENCE OF LXR MODULATORS GM-MØ Basal (vs CNT-GM-MØ ) LPS (vs CNT-GM-MØ) GW-GM-MØ GSK-GM-MØ GW/GSK- GM-MØ GW-GM-MØ GSK-GM-MØ GW/GSK- GM-MØ TNFα -/- Up*/- Down/- Up*/Up* Down/- Up/- IL-10 Down*/Down* Up/Down* -/Down Up*/Up -/Down* -/Down IL-6 Down*/Down Up*/- Down/- Down*/Up* Down*/Up Down/- IL-1β -/Up Down*/- Down*/- Up*/Up* Down*/- Up/Up CCL2 Down/Down Up/Down -/- Down/Down Up/- Up/Down CCL8 Down/Down Down/Down Down/Down Down/Down Down*/Down* Down/Down* CCL19 Up/Up* -/- -/- Up*/Down* Down/Down* Down/Down* IFNβ -/- -/- -/- Up*/Up* Down/- Down/Up Activin A Down*/Up* Down*/- Down*/- Down*/Up Down*/- Down*/Down GW-M-MØ GSK-M-MØ GW/GSK- M-MØ GW-M-MØ GSK-M-MØ GW/GSK-M- MØ Basal (vs CNT-M-MØ) LPS (vs CNT-M-MØ) M-MØ *Statistically significant vs Control Results 115 Results 116 Figure 42. LXR modulation alters cytokine production by M-MØ in basal and LPS-activating conditions. A. Schematic representation of the in vitro generation of human M-MØ differentiated in the presence of LXR agonist GW3965 (GW-M-MØ), LXR inverse agonist GSK2033 (GSK-M-MØ) or both (GW/GSK-M-MØ) for 7 days and treatment of these macrophages with LPS for 18 hours. B. IL-10 (left) and TNFα (center) production in non-activated (basal) GW-M-MØ, GSK-M-MØ and GW/GSK-M-MØ. Ratio between TNFα/IL-10 (right) is also represented. C. IL-10 (left) and TNFα (center) production in LPS-activated GW-M-MØ, GSK-M-MØ and GW/GSK- M-MØ. Ratio between TNFα/IL-10 (right) is also represented. D. IL-6 (top) and IL-1β (bottom) production in basal and LPS-activated GW-M-MØ, GSK-M-MØ and GW/GSK-M-MØ. E. CCL2 (left) and CCL8 (right) production in basal and LPS-activated GW-M-MØ, GSK-M-MØ and GW/GSK-M-MØ. F. IFNβ (left) and CCL19 (right) production in basal and LPS-activated GW-M-MØ, GSK-M-MØ and GW/GSK-M-MØ. G. Activin A production in basal and LPS-activated GW-M-MØ, GSK-M-MØ and GW/GSK-M-MØ. All experiments represent the individual values plus the mean of six independent donors. Paired-t-test was used to compare between groups and a pvalue<0.05 was considered as statistically significant *p<0.05, **p<0.01, *** p<0.001. Legend box refers to all panels. Results 117 Results 118 Figure 43. LXR modulation alters cytokine production by GM-MØ in basal and LPS-activating conditions. A. Schematic representation of the in vitro generation of human GM-MØ differentiated in the presence of LXR agonist GW3965 (GW-GM-MØ), LXR inverse agonist GSK2033 (GSK-GM-MØ) or both (GW/GSK-GM-MØ) for 7 days and treatment of these macrophages with LPS for 18 hours. B. IL-10 (left) and TNFα (center) production in non-activated (basal) GW-GM-MØ, GSK-GM-MØ and GW/GSK-GM-MØ. Ratio between TNFα/IL-10 (right) is also represented. C. IL-10 (left) and TNFα (center) production in LPS-activated GW-GM-MØ, GSK-GM-MØ and GW/GSK-GM-MØ. Ratio between TNFα/IL-10 (right) is also represented. D. IL-6 (top) and IL-1β (bottom) production in basal and LPS-activated GW-GM-MØ, GSK-GM-MØ and GW/GSK-GM- MØ. E. CCL2 (left) and CCL8 (right) production in basal and LPS-activated GW-GM-MØ, GSK-GM-MØ and GW/GSK-GM-MØ. F. IFNβ (left) and CCL19 (right) production in basal and LPS-activated GW-GM-MØ, GSK-GM- MØ and GW/GSK-GM-MØ. G. Activin A production in basal and LPS-activated GW-GM-MØ, GSK-GM-MØ and GW/GSK-GM-MØ. All experiments represent the individual values plus the mean of six independent donors. Paired-t-test was used to compare between groups and a pvalue<0.05 was considered as statistically significant *p<0.05, **p<0.01, *** p<0.001. Legend box refers to all panels. Results 119 Next, we analyzed the antitumoral activity of macrophages whose LXR activity had been modulated using the melanoma BLM cell line as a model (figure 44A). Results were similar for both M-MØ (figure 44B) and GM-MØ (figure 44C), as GW3965 or GSK2033 treatment cause a lower proliferation of BLM cell line compared to non-treated cells. In the case of M-MØ supernatants, the effect of GSK2033 was more potent than GW3965. As a control, experiments performed with BLM cells treated only with GW3965 and GSK2033 (figure 44D) at regular concentrations (1 µM) showed that the agonists themselves have minimal antitumoral capacity, indicating that secreted factors from macrophages are responsible for the observed antitumoral capacity. Finally, and considering the results derived from gene ontology analysis, we compared the T-cell activating ability of macrophages generated in the absence or presence of LXR modulators. Mixed Leukocyte Reaction (MLR) experiments showed that GW3965 treatment increases the T-cell stimulating ability of GM-MØ (figure 45B and C) whereas GSK2033 treatment had no effect. This could be a consequence of the higher expression of costimulatory molecule CD80 in GW-GM-MØ (figure 45D). In the case of M-MØ (figure 45E and F), both modulators decreased T-cell proliferation to a similar extent. In all cases, macrophages or T lymphocytes alone did not show proliferation, as well as macrophages or T lymphocytes treated with GW3965 or GSK2033 alone (data not shown). Therefore, modulation of LXR activity has a direct effect on the T-cell stimulatory activity of human macrophages. Results 120 Figure 44. LXR-altered human macrophages supernatants exert powerful antitumoral activities. A. Schematic representation of the in vitro generation of human M-MØ and GM-MØ differentiated in the presence of LXR agonist GW3965 (GW-M-MØ; GW-GM-MØ), LXR inverse agonist GSK2033 (GSK-M-MØ; GSK-GM-MØ) or both (GW/GSK-M-MØ; GW/GSK-GM-MØ) for 7 days and analysis of the effects of their supernatants on the proliferation of the melanoma cell line BLM. B-C. Proliferation index of BLM cells (normalized to non-treated cells) exposed to supernatants of the indicated cell subsets. D. MTT absorbance of BLM cells treated with vehicle (DMSO), GW3965, GSK2033 or both at 1µM (left) or 10 µM (right). In B and C, the individual values plus the mean of the effects of supernatants from seven independent macrophage donors are shown. In D, five replicates from every sample are represented. Paired-t-test was used to compare between groups and a pvalue<0.05 was considered as statistically significant *p<0.05, **p<0.01, *** p<0.001. Results 121 Figure 45. LXR activity modulation alters the T-cell stimulatory ability of macrophages. A. Schematic representation of the in vitro generation of human M-MØ and GM-MØ differentiated in the presence of LXR agonist GW3965 (GW-M-MØ; GW-GM-MØ), LXR inverse agonist GSK2033 (GSK-M-MØ; GSK-GM-MØ) or both (GW/GSK-M-MØ; GW/GSK-GM-MØ) for 7 days and analysis of their ability to affect T-lymphocyte proliferation. B. Allogeneic T lymphocyte proliferation induced by CNT-GM-MØ, GW-GM-MØ, GSK-GM MØ or GW/GSK-GM-MØ in every donor. Mean ± SEM of 3 H-Thymidine counts of eight replicates from every donor is shown. C. Proliferation rate of allogeneic T lymphocyte in the presence of CNT-GM-MØ, GW-GM-MØ, GSK-GM MØ or GW/GSK-GM-MØ. 3 H-Thymidine counts in each case were normalized to those observed with CNT-GM- MØ. Mean ± SEM of six independent donors is shown. D. Average read counts of CD80 in CNT-GM-MØ, GW- GM-MØ, GSK-GM-MØ and GW/GSK-GM-MØ as determined by RNAseq. E. Allogeneic T lymphocyte proliferation induced by CNT-M-MØ, GW-M-MØ, GSK-M MØ or GW/GSK-M-MØ in every donor. Mean ± SEM of 3 H-Thymidine counts of eight replicates from every donor is shown. F. Proliferation rate of T lymphocytes incubated with CNT-M-MØ, GW-M-MØ, GSK-M MØ or GW/GSK-M-MØ. 3 H-Thymidine counts in each case were normalized to those observed with CNT-M-MØ. Mean ± SEM of six independent donors is shown. Paired-t-test was used to compare between groups and a pvalue<0.05 was considered as statistically significant *p<0.05, **p<0.01, *** p<0.001. Results 122 Previous studies have shown that MTX response is specific for GM-MØ and the identity of MTX-responsive genes is known588,589. Consequently, we evaluated the expression of MTX-response genes in MTX-treated GW-GM-MØ and GSK-GM-MØ (MTX/GW-GM-MØ, MTX/GSK-GM-MØ) (figure 46A, 46B). Results indicated that treatment with either GW3965 or GSK2033 decrease MTX responsiveness, although both treatments poorly affected TYMS expression and GSK2033 exerted less effect in ABCA1 than previous times. Altogether, our results showed that LXR activation tend to polarize macrophages towards a more pro-inflammatory state while LXR inactivation exhibits a net antiinflammatory effect on monocyte-derived macrophages. Results 123 Figure 46. LXR activity modulation on human macrophages influences responsiveness to Methotrexate. A. Schematic representation of the in vitro generation of GM-MØ in the presence of LXR agonist GW3965 (GW-GM-MØ) or LXR inverse agonist GSK2033 (GSK-GM-MØ) for 7 days and the subsequent exposure to Methotrexate (MTX) for 2 days (MTX-GM-MØ, GW/MTX-GM-MØ and GSK/MTX-GM-MØ). B. Relative mRNA expression of the indicated MTX-responsive genes in GM-MØ treated with (MTX-GM-MØ, GW/MTX-GM-MØ and GSK/MTX-GM-MØ) or without MTX (CNT-GM-MØ, GW-GM-MØ and GSK-GM-MØ). C. MTX inducibility of MTX-responsive genes in MTX-GM-MØ, GW/MTX-GM-MØ and GSK/MTX-GM-MØ. mRNA expression was normalized to MTX-GM-MØ. For all cases, mean + SEM of four to five independent donors is represented. Paired-t-test was used to compare between groups and a pvalue<0.05 was considered as statistically significant *p<0.05, **p<0.01, *** p<0.001, **** p<0.0001. Results 124 LXR direct the polarization effect of pathological fluids over human monocytes As we commented, LXR has proven to be the most enriched pathway in synovial macrophages and also in large TAM from colorectal liver metastasis225,226; macrophages that resembles GM-MØ and M-MØ. Of note, small TAM which also can be found in colorectal liver metastasis resembles GM-MØ too. Thus, to find out the potential relevance of modulating LXR activity under pathological settings, we evaluated whether altering LXR activity was also capable of modifying the macrophage-polarizing ability of tumor-derived ascitic fluids (TAF) or Rheumatoid Arthritis Synovial Fluid (RASF) of distinct origin205,673. Monocytes were differentiated into macrophages in the presence of TAF and either with or without GW3695 (figure 47A). Comparison of the resulting macrophages (TAF-MØ, GW/TAF-MØ) revealed that LXR activation greatly modifies the transcriptome of macrophages generated under the influence of tumor-derived ascitic fluids, as the expression of almost 1000 genes was significantly altered (figure 47B). As expected, GW/TAF-MØ significantly over-expressed genes regulated by LXR and SREBP, as well as of genes upregulated in GW-M-MØ and downregulated in GSK-M-MØ (figure 47C). More importantly, GSEA revealed that the gene profile of GW/TAF-MØ showed a very strong over- representation of GM-MØ specific genes and an under-representation of M-MØ-specific genes (figure 47D) as well as of MAFB-dependent genes (figure 47E), a result further supported by gene ontology analysis using Enrichr (figure 47F). Indeed, and as shown in figure 47G, the expression of representative MAF, MAFB and MAFB-dependent genes (blue) was reduced by GW3965 in all GW/TAF-MØ samples, where the expression of GW3965-upregulated genes (red, black) was higher. Finally, analysis of the transcriptome of GW/TAF-MØ evidenced a very significant downregulation of the genes that define the gene profile of “large TAM” (adjp, 7.54e-27), and a positive enrichment of the genes that characterize “small TAM” (adjp 9.13e-14) from colorectal liver metastasis226 (figure 47F). On the other hand, monocytes-derived macrophages were differentiated in the presence of RASF and either GSK2033 or not (figure 48A). LXR inactivation exerted an even more profound impact on RASF-MØ evidenced by the almost 2000 genes that were differentially expressed in RASF/GSK-MØ (figure 48B). Similar to TAF, LXR and SREBP- dependent genes were downregulated in GSK/RASF-M-MØ as well as upregulated genes in GW-GM-MØ and downregulated genes in GSK-GM-MØ (figure 48C). Interestingly, downregulated genes in GW-GM-MØ were also downregulated in RASF/GSK-MØ. GSEA analysis showed clearly an overrepresentation of M-MØ specific genes and underrepresentation of GM-MØ-specific genes in GSK/RASF-MØ (figure 48D). Besides, MAFB-dependent genes were upregulated in GSK/RASF-MØ and MAF transcription factor was associated with RASF/GSK-MØ upregulated genes (figure 48E-F). In contrast to TAF, genes that define the gene profile of “small TAM” were downregulated in GSK/RASF-MØ (figure 48E) and indeed genes that define RA macrophages were downregulated also in GSK/RASF-MØ (figure 48F). Expression of MAF and MAFB-dependent genes was upregulated in GSK/RASF-MØ, while LXR-dependent gene ABCG1 and GM-MØ specific CFS1 and FCGR3A genes (figure 48G). These results confirm that LXR activation exerts the same effect on macrophages generated in the presence of either M-CSF- or TAF-macrophages while LXR inactivation exert similar actions on GM-CSF- or RASF-macrophages. Indeed, these results demonstrate Results 125 that LXR activation impeded the polarizing action of pathological TAF, impairing the acquisition of the genes that characterize antiinflammatory (M-CSF-dependent) and enhancing the expression of genes that define proinflammatory and macrophages. Oppositely, LXR inactivation blocked the polarizing effect of RASF, abrogating expression of genes that define proinflammatory (GM-CSF-dependent) macrophages and boosting expression of genes that define antiinflammatory macrophages. Thus, LXR establish as essential factors for the acquisition of the proinflammatory and antiinflammatory gene profile in macrophages also in pathological conditions. All the main results of this chapter are summarized in figure 49. Results 126 Figure 47. Effect of LXR activation on the transcriptional profile of macrophages generated in the presence of tumor-derived ascitic fluid. A. Schematic representation of the generation of monocyte-derived macrophages in the presence of ascitic fluid from tumor patients, with (GW/TAF-MØ) or without (TAF-MØ) exposure to LXR agonist GW3965. B. Number of differentially expressed genes (adjp<0.05) between GW/TAF- MØ and TAF-MØ. C. Summary of GSEA of the indicated gene sets on the ranked comparison of the GW/TAF-MØ and TAF-MØ transcriptomes. D-E. GSEA of the “Proinflammatory gene set” and “Antiinflammatory gene set” (D) and MAFB-regulated gene sets (E) on the ranked comparison of the GW/TAF-MØ and TAF-MØ transcriptomes, showing representative genes within the indicated leading edges. In C-E, Normalized Enrichment Score (NES) and False Discovery Rate q value (FDRq) are indicated. F. Gene ontology analysis of the Top 250 genes downregulated (upper panel) or upregulated (lower panel) in GW/TAF-MØ using Enrichr in the indicated databases. G. Read counts of the indicated genes in GW/TAF-MØ and TAF-MØ generated using four independent tumor-derived ascitic fluids (TAF 1-4), as determined by RNA-seq. Results 127 Figure 48. Effect of LXR inactivation on the transcriptional profile of macrophages generated in the presence of rheumatoid arthritis synovial fluid. A. Schematic representation of the generation of monocyte-derived macrophages in the presence of synovial fluids from rheumatoid arthritis patients, with (GSK/RASF- MØ) or without (RASF-MØ) exposure to LXR inverse agonist GSK2033. B. Number of differentially expressed genes (adjp<0.05) between GSK/RASF-MØ and RASF- MØ. C. Summary of GSEA of the indicated gene sets on the ranked comparison of the GSK/RASF-MØ and RASF-MØ transcriptomes. D-E. GSEA of the “Proinflammatory gene set” and “Antiinflammatory gene set” (D) and MAFB- regulated gene sets (E) on the ranked comparison of the GSK/RASF-MØ and RASF-MØ transcriptomes, showing representative genes within the indicated leading edges. In C-E, Normalized Enrichment Score (NES) and False Discovery Rate q value (FDRq) are indicated. F. Gene ontology analysis of the Top 250 genes downregulated (upper panel) or upregulated (lower panel) in GSK/RASF-MØ using Enrichr in the indicated databases. G. GSEA of Rheumatoid Arthritis (RA) macrophages-specific genes on the ranked comparison of the GSK/RASF-MØ and RASF-MØ transcriptomes, showing representative genes within the indicated leading edges. H. Read counts of the indicated genes in GSK/RASF-MØ and RASF-MØ generated using six independent rheumatoid arthritis synovial fluids (RASF 1-6), as determined by RNA-seq. Results 128 Figure 49. LXR activation guides monocytes to acquire a more proinflammatory phenotype while LXR inactivation instructs monocytes to differentiate into a more antiinflammatory polarization state. Graphical abstract of the effect of LXR modulation on monocytes treated with M-CSF, that differentiate to antiinflammatory macrophages (M-MØ), or treated with GM-CSF, that differentiate to proinflammatory macrophages (GM-MØ). LXR activation with GW3965 during monocyte to macrophage transition allows macrophages to acquire a more proinflammatory polarization while LXR inactivation with GSK2033 directs them to acquire a more antiinflammatory phenotype. Arrow distance represents potency of LXR modulators, as GW3965 exert a stronger effect on M-CSF-dependent macrophages and GSK2033 on GM-CSF-dependent macrophages. The main effects on cytokine secretion or macrophage functional profile are also represented. In a pathological scenario, LXR activation impairs the antiinflammatory effect of Tumour Ascitic Fluids on monocytes whereas LXR inactivation impedes the proinflammatory effect of Rheumatoid Arthritis Synovial Fluids on them. LXR contribute to the AhR-dependent antiinflammatory polarization of human macrophages 130 Results Sustained AhR inhibition impairs the acquisition of the transcriptional signature of M-MØ and their functional differentiation In parallel to the analysis of the role of LXR in human macrophage polarization, we investigated the role of AhR in polarization of human monocyte-derived macrophages. Experiments performed in the lab in collaboration with Dr. Ignacio Rayo and Dr. Eduardo Patiño-Martínez showed that sustained inhibition of AhR during the generation of M-MØ skews macrophages towards the acquisition of a proinflammatory phenotype (figure 50, 51) We treated monocytes with the AhR inhibitor CH223191, that blocks the nuclear translocation and genomic signaling pathways of AhR621, during all days on the generation of M-MØ and analyzed the transcriptome of these macrophages (CH-M-MØ) (figure 50A). Transcriptome analyses showed 1022 genes upregulated and 806 genes downregulated in CH-M-MØ (figure 50B). GSEA showed that upregulated genes were enriched in genes belonging to GSEA Hallmarks database terms “TNFA signaling via NFkB”, “Hypoxia”, “Inflammatory Response” and “Glycolysis” (figure 50B). Actually, expression of the M-MØ- specific and GM-MØ-specific gene sets204,725 showed a negative enrichment of M-MØ- specific genes in CH-M-MØ, where expression of GM-MØ-specific genes was concomitantly enhanced (figure 50C). Of note, GSEA revealed that CH233191 significantly downregulated genes of the "Antiinflammatory gene set" (figure 50D, left) while upregulated genes of the "Proinflammatory gene set" (figure 50D, right). Next, we evaluated whether AhR inhibition altered cytokine production after LPS activation (figure 50E). CH-M-MØ produced higher levels of TNFα, IL-6 and Activin A after LPS-activation while secreted lower levels of IL-10 (figure 50F). In line with the ability of Activin A to limit tumor cell proliferation204, CH-M-MØ-conditioned medium exhibited a significantly higher ability to suppress proliferation of BLM melanoma cells (figure 50G). In addition, CH-M-MØ tent to exhibit a higher capacity to induce T-cell proliferation than CNT- M-MØ (figure 50H). We next addressed if AhR inhibition was not limited to polarization-specific markers but also affected the glucose metabolism of M-MØ. CH-M-MØ not only expressed higher levels of genes encoding key glycolytic enzymes (PKM2, LDHA, SLC2A1, FBP1, figure 51A) but exhibited higher oxygen consumption rate (OCR, figure 51B) and extracellular acidification rate (ECAR, figure 51C), and CH-M-MØ-conditioned medium contained higher lactate concentration than CNT-M-MØ (figure 51D); results that are in line with the enrichment of the "Glycolysis" GSEA Hallmark term. Of note, OCR and ECAR were not altered when differentiation took place in the presence of the AhR ligand FICZ (figure 51B- C). Since "Hypoxia" term was also enriched in the CH-M-MØ transcriptome, we also analyzed HIF expression in CH-M-MØ, both in the absence and in the presence of the HIF1α stabilizer Deferoxamine (DFO, figure 51F). HIF1α protein expression was found to be slightly upregulated in CH-M-MØ, whose HIF1 levels were, however, lower than those detected after DFO treatment. Furthermore, expression of the HIF-1 target gene EGLN3 was higher in CH-M-MØ than in CNT-M-MØ counterparts (Figure 51E). Altogether, these results showed that CH233191-dependent AhR inhibition hinders the anti-inflammatory phenotype of M-CSF-dependent M-MØ and simultaneously potentiates the acquisition of proinflammatory capabilities normally associated to GM-MØ. 131 Results Figure 50. AhR inhibition impairs the acquisition of the transcriptional signature of M-MØ and their functional differentiation. A. Schematic representation of the in vitro generation of M-MØ in the absence (CNT-M-MØ) or presence (CH-M-MØ) of the AhR antagonist CH-223191. B. Left panel: number of differentially expressed genes (adjp<0.05) in CH-M-MØ relative to CNT-M-MØ. Right panel: summary of GSEA on the ranked comparison of the transcriptome of CH-M-MØ and CNT-M-MØ, using the Hallmark gene set database. Normalized Enrichment Score and FDRq values are indicated in each case. C. Heatmap of the expression of the GM-MØ-specific and M-MØ-specific gene sets in CH-M-MØ and CNT-M-MØ. D. GSEA of the genes upregulated (left) or downregulated (right) genes in CH-M-MØ on the ranked comparison of the GM-MØ and M-MØ specific gene sets. Normalized Enrichment Score (NES) and FDRq values are indicated. E. Schematic representation of the LPS activation of M-MØ generated in the absence (CNT-M-MØ) or presence (CH-M-MØ) of the AhR antagonist CH-223191. F. Production of the indicated cytokines in CNT-M-MØ, CH-M MØ, LPS-M-MØ and 132 Results CH/LPS-M-MØ. Mean ± SEM of three independent donors is shown. G. Proliferation of BLM melanoma cells exposed for 72 hours to culture supernatant from CH-M-MØ or CNT-M-MØ. Results show cell proliferation relative to the proliferation of BLM maintained in complete medium (control). Mean ± SEM of five independent experiments is shown. H. Allogeneic T lymphocyte proliferation induced by CNT-M-MØ and CH-M-MØ in every donor. Mean ± SEM of 3 H-Thymidine counts of eight replicates from every donor is shown. In all cases, paired-t- test was used to compare between groups and a pvalue<0.05 was considered as statistically significant *p<0.05, **p<0.01, **** p<0.0001. 133 Results Figure 51. Chronic inhibition of AhR during M-MØ differentiation results in altered bioenergetic profile. A. Relative expression of the indicated genes in CH-M-MØ and CNT-M-MØ. Mean ± SEM of four independent samples is shown. B-C. Bioenergetics parameters of M-MØ differentiated in the presence of DMSO (CNT-M-MØ), the AhR antagonist CH-223191 (CH-M-MØ) or the AhR agonist FICZ (FICZ-M-MØ). Mean ± SEM of two independent samples is shown. D. Lactate concentration in the culture supernatant of CH-M-MØ and CNT- M-MØ. Mean ± SEM of three independent samples is shown. E. Relative expression of EGLN3 in CH-M-MØ and CNT-M-MØ. Mean ± SEM of eight independent samples is shown. Legend box refers to panels D and E. F. Expression of HIF-1α in CH-M-MØ and CNT-M-MØ, and in the presence of Deferoxamine (DFO-M-MØ and DFO/CH-M-MØ) as determined by western blot. Vinculin protein levels were determined in parallel as a protein loading control. A representative image of western blot protein expression is shown. The right panel illustrates the HIF-1α/vinculin ratio in two independent experiments. In all cases, paired-t-test was used to compare between groups and a pvalue<0.05 was considered as statistically significant *p<0.05, **p<0.01, *** p<0.001, **** p<0.0001. 134 Results LXR transcription factors regulate transcriptional changes in M-MØ differentiated in AhR-inhibited conditions Gene ontology analysis (Enrichr) of the CH223191-affected genes (red or blue in figure 49B) revealed a strong link between sustained AhR inhibition and the expression of genes regulated by either MAF or the LXRα-encoding gene NR1H3 (figure 52B), and association that was confirmed as the transcriptome of CH-M-MØ shows a positive enrichment of NR1H3-regulated genes (figure 52C). This relationship was validated by RT-PCR and western blot analysis in CH-M-MØ which showed augmented expression of NR1H3 (figure 52D), LXRα (figure 52E) and the LXR target proteins ABCA1 and ABCG1 (figure 52F). Besides, CH-M-MØ also displayed a higher LXR activity than control M-MØ (figure 52G), although the difference did not reach statistical significance. In this sense, the elevated expression of NR1H3 and LXRα in CH-M- MØ correlated with a higher expression of representative of LXR-dependent (ABCG1, SCD) and SREBP-dependent (DHCR24, FADS1) genes in CH-M-MØ (figure 52H). Of note, along with LXRα upregulation, an almost complete loss of the SREBP1 precursor was found in CH- M-MØ (figure 52I). Next, and considering our previous results with LXR, we decided to investigate if the proinflammatory effect of CH223191-dependent AhR inhibition was dependent of LXR activity. For that purpose, we generated CH-M-MØ in the presence of GSK2033 (figure 53A). Exposure to GSK2033 partially abrogated the diminished expression of FOLR2, IL10 and MAF in CH-M-MØ and impaired the enhanced expression of MMP12 and INHBA (figure 53B). Interestingly, the effect of AhR inhibition on NR1H3 was clearly blocked by GSK2033 preincubation. However, LXR inhibition had no effect in the bioenergetic profile of CH-M-MØ, as it did not affect lactate production (figure 53C). Since CH-M-MØ showed enhanced SREBP1 activation (figure 53I), we also assessed whether the enhanced level of LXRα, which is secondary to sustained AhR inhibition, affected the expression of SREBP-regulated genes351. CH-M-MØ exhibited significantly higher levels of the SREBP target genes HMGCR and SQLE, as well as of HMGCS1, DHCR24, SREBF1 and SREBF2 (figure 53D). Importantly, the enhanced expression of SREBP target genes in CH-M-MØ was prevented by the LXR inverse agonist GSK2033 (figure 53D) an effect that reached statistical significance in the case of SQLE and SREBF2. Therefore, LXR significantly contributes to the enhanced expression of proinflammatory genes and of genes involved in cholesterol and fatty acid metabolism caused by the continuous inhibition of AhR. Consequently, we can conclude that AhR and LXR crosstalk to control human macrophage polarization and cholesterol homeostasis. All the results of this chapter are summarized in figure 54. 135 Results Figure 52. Sustained AhR inhibition along M-MØ differentiation modifies the expression of the transcription factors LXRα and SREBP. A. Schematic representation of the in vitro generation of M-MØ in the absence (CNT-M-MØ) or presence (CH-M-MØ) of the AhR antagonist CH-223191. B. Gene ontology (Enrichr) analysis of the downregulated and upregulated genes in CH-M-MØ in the indicated databases. C. GSEA of genes regulated by the LXRα agonist GW3965 (GSE156783) on the ranked comparison of the transcriptomes of CH-M- MØ vs. CNT-M-MØ. Normalized Enrichment Score (NES) and FDRq values are indicated. D. Relative expression of NR1H3 (LXRα gene) in CNT-M-MØ and CH-M-MØ. Mean ± SEM of three independent samples is shown. E. Expression of LXRα in CH-M-MØ and CNT-M-MØ as determined by Western blot. Vinculin protein levels were determined in parallel as a protein loading control. A representative image of western blot protein expression is shown. The right panel illustrates the mean ± SEM of LXRα/vinculin ratio in four independent experiments. F. Expression of ABCA1 and ABCG1 proteins in CH-M-MØ and CNT-M-MØ as determined by Western blot. Vinculin protein levels were determined in parallel as a protein loading control. A representative image of western blot protein expression is shown. The right panel illustrates the mean ± SEM of ABCA1/vinculin and ABCG1/vinculin ratio in three independent experiments. G. LXR-dependent transcriptional activity in CNT-M-MØ and CH-M-MØ transfected with LXRE-luciferase promoter. Experiments represent the mean ± SEM of the ratio of Firefly/Renilla luciferase values obtained in ten to twelve independent samples. H. Average read counts of the indicated LXR- or SREBP-dependent genes in CH-M-MØ and CNT-M-MØ, as determined by RNAseq. I. Expression of SREBP1 in CH-M-MØ and CNT-M-MØ as determined by Western blot. Vinculin protein levels were determined in parallel as a protein loading control. A representative image of western blot protein expression is shown. The right panel illustrates the mean ± SEM of SREBP1/vinculin ratio in three independent experiments. In all cases, paired-t-test was used to compare between groups and a pvalue<0.05 was considered as statistically significant *p<0.05, *** p<0.001. 136 Results Figure 53. LXR mediate the transcriptional changes secondary to chronic AhR inhibition during M-MØ differentiation. A. Schematic representation of the in vitro generation of CNT-M-MØ and CH-M-MØ in absence or presence (GSK-M-MØ, CH/GSK-MØ) of the LXR inverse agonist GSK2033. D. Relative expression of the indicated polarization-specific genes (blue, M-MØ specific; red, GM-MØ specific) in CNT-M-MØ, CH-M-MØ, GSK-M-MØ and CH/GSK-M-MØ. Mean ± SEM of four independent samples is shown. E. Lactate concentration in the culture supernatant of CNT-M-MØ, CH-M-MØ, GSK-M-MØ and CH/GSK-M-MØ. Mean ± SEM of four independent samples is shown. Relative expression of the indicated SREBP-dependent genes in CNT-M-MØ, CH-M-MØ, GSK-M-MØ and CH/GSK-M-MØ. Mean ± SEM of four independent samples is shown. Legend box refers to all panels. In all cases, paired-t-test was used to compare between groups and a pvalue<0.05 was considered as statistically significant *p<0.05, **p<0.001, **** p<0.0001. 137 Results Figure 54. LXR and AhR cooperation controls human antiinflammatory macrophage polarization. Graphical abstract of the effect of AhR inhibition in M-CSF-differentiated antiinflammatory macrophages (M-MØ). AhR inhibition guides M-MØ to acquire a proinflammatory signature characterized by greater secretion of proinflammatory cytokines, lower production of antiinflammatory cytokines in response to LPS and augmented T lymphocyte proliferation as a consequence of a more antigen presentation ability of macrophages. This is accompanied by an upregulation of macrophage glycolytic enzymes and an increased production of lactate. In these conditions, LXRα is heavily induced along with some of its targets. LXR blockage by LXR inverse agonist GSK2033 partially impedes AhR-dependent proinflammatory actions in proinflammatory transcriptome but completely abrogates the AhR effect on SREBP downstream signaling. DISCUSSION 139 Discussion In this PhD thesis we have investigated the role of Liver X Receptors (LXR) in the transcriptional and functional polarization of human M-CSF-differentiated (M-MØ) antiinflammatory macrophages and GM-CSF-differentiated (GM-MØ) proinflammatory macrophages. In the first part of the thesis, we aimed to unravel how LXR modulation controls human macrophage transcriptome and functional profile. In the second part, we aimed to discover the LXR implication in the effect of AhR inhibition on human antiinflammatory polarization. We have discovered that LXR are crucial for human macrophage polarization: LXR activation directs macrophages to acquire a proinflammatory phenotype while LXR inactivation skews macrophage to acquire an antiinflammatory phenotype. In this sense, LXR activity conditions the polarizing effect of tumor ascitic fluids and rheumatoid arthritis synovial fluids. Besides, LXR affect MAFB, IRF4, PPARγ and HIF1α expression; transcription factors involved in macrophage polarization. Besides, LXR regulate the functional profile of human macrophages, especially in terms of cytokine production, antitumoral ability, antigen presentation to T lymphocytes and Methotrexate response. Finally, we have discovered that LXR contribute to the AhR-dependent antiinflammatory polarization and control the AhR regulation of SREBP-dependent signaling. Here we have presented a comprehensive research of how modulation of LXR activity controls human macrophage transcriptional and functional polarization. First, we determined LXR expression in human monocyte-derived M-MØ and GM- MØ. Between the two members of LXR family, LXRα and LXRβ, we observed that LXRα expression was higher in GM-MØ whereas LXRβ expression was higher in M-MØ. Our results agree with previous findings that showed that LXR expression varied between the different tissue-resident macrophages75. In contrast, LXRα is the most expressed member in tissue resident macrophages215–217, that resemble M-MØ. Considering that M-CSF predominates in homeostatic conditions and GM-CSF predominates in damaged tissues, our results suggest that the tissue microenvironment impacts LXR expression in macrophages. Besides, LXR target genes (table 2) showed a different distribution between M-MØ and GM- MØ, what could be a consequence of the different expression of LXR members in these macrophages. For example, bona fide LXR target genes ABCA1 and ABCG1 showed a remarkably opposite expression in M-MØ and GM-MØ. ABCA1 is ubiquitously expressed while ABCG1 predominates in liver and macrophages264,266 but these transporters have a similar regulation and collaborate in some situations267. This implies that probably M-CSF and GM-CSF could be conditioning macrophages to acquire a specific pattern of expression of these two proteins A similar phenomenon have been addressed in ABCG1 and ABCA1 regulation of pulmonary surfactant levels726. Maybe macrophages downregulate ABCA1 and upregulate ABCG1 in inflammatory scenarios, where GM-CSF production is increased. In inflammatory responses, macrophages eliminate the apoptotic cells that are generated in the tissues. Thus, ABCG1 upregulation may help macrophages to eliminate the phagocytosis- dependent increase of intracellular cholesterol or waste products. Next, we treated M-MØ and GM-MØ with LXR agonist GW3965 or LXR inverse agonist to activate and inhibit LXR, respectively. However, we only observed changes in the antiinflammatory gene set in GW-treated M-MØ, suggesting LXR activation have a stronger effect in M-MØ than in GM-MØ. In parallel, we used a different approach to impair LXR expression in macrophages. We depleted LXR members by a siRNA-dependent strategy, using specific siRNA for LXRα and for LXRβ. We did not observe any effects in 140 Discussion macrophages antiinflammatory or proinflammatory gene expression but we were unable to deplete both LXR proteins at the same time (double silencing experiments). Maybe macrophages have mechanisms to assure that one of the members of LXR family is expressed at sufficient levels to permit that homeostatic functions like cholesterol efflux or lipid metabolism keep functioning properly. Interestingly, GSK2033 impaired all LXR- dependent target gene expression but we were not able to deplete both LXR proteins using siRNA. The only difference is that GSK2033 is not depleting LXR protein expression while siRNA does. Perhaps, LXR proteins heterodimerize with other unknown proteins to maintain physiological processes, independently of their gene regulation. Modulation of Liver X Receptors modifies the monocyte-to-macrophage differentiation in response to M-CSF or GM-CSF LXR activation by GW3965 increased all the proinflammatory signature of M-MØ and LXR inactivation by GSK2033 increased all the antiinflammatory signature of M-MØ and GM- MØ. GW3965 effect on the gene signature of GM-MØ was unusual, as it tended to decrease the proinflammatory gene set but also the antiinflammatory gene set. This result contradicts previous experiments performed with this agonist in mouse: GW3965 showed clear antiinflammatory effects in macrophages232,293,340. However, in atherosclerotic plaques, LXR activation did show this dual effect291,292. So, a profound analysis of the antiinflammatory genes that are upregulated in GW3965-GM-MØ is essential to clarify how LXR is regulating GM-MØ transcriptome. In M-MØ, we observed a clear proinflammatory effect of GW3965, so our results suggest again that GM-CSF is exerting an effect on LXR target genes that could be independent of LXR activation. Finally, it is important to note that all the LXR antiinflammatory effects reported in mouse macrophages have been observed upon short treatments of LXR agonist whereas the proinflammatory effects reported in human macrophages have been seen with long treatments (≥ 48h). Importantly, implication of GSK2033 or another LXR inverse agonist in macrophage biology has been poorly explored and our data showed that GSK2033 has important actions on macrophages. Apart from one study238, the knowledge of how GSK2033 regulates LXR- dependent signaling and how GSK2033 affects macrophage physiology or pathology is currently unknown. Here we have described the GSK2033-dependent transcriptome in M- MØ and GM-MØ and how GSK2033 regulates the functional polarization of these macrophages. In this sense, we wonder if GSK2033 would have the same striking effects on macrophages in culture conditions with lower concentrations of serum or in presence of inhibitors for enzymes of cholesterol pathway (like zaragozic acid), where the availability of LXR endogenous activators (cholesterol derivatives) would be limited. Comparison of our lists of genes with the available data from ChipSeq in human macrophages treated with LXR agonist T0901317 revealed that some proinflammatory genes like MMP12 or INHBA have LXRE binding sites (DR4 motif)727,728. This reinforces our evidence that many of the proinflammatory effects that we have seen in human macrophages are directly regulated by LXR. However, these Chip-seq were conducted in THP1-like macrophages treated with T0901317 or in human atherosclerotic foam cells. First, none of these two cellular models resemble all the characteristics of primary human monocyte-derived macrophages. Second, T0901317 is not the preferred LXR agonist as it can also activate Farnesoid X Receptors (FXR)234. Therefore, the necessity for a LXR Chip- Seq in primary human monocytes and monocyte-derived macrophages is patent. 141 Discussion LXR alters expression of transcription factors important in macrophage polarization We found that GW-M-MØ, GW-GM-MØ, GSK-M-MØ and GSK-GM-MØ exhibited changes in the expression of various transcription factors that regulate macrophage polarization. First, we found that the expression of the transcription factors MAFB and MAF, that control human antiinflammatory polarization195,Simón-Fuentes et al, in preparation, was diminished in GW-M-MØ. The relationship between LXR and MAFB has been addressed in the past729, but in contrast to those studies, we observed that LXR activation led to lower MAFB expression and LXR inactivation boosted MAFB expression. A link between MAF and LXR has not been established yet but LXR activation seemed to regulate MAF in different directions between GW-M-MØ and GW-GM-MØ. Considering that MAFB and MAF control distinct genes of the M-MØ transcriptome (data not shown), this suggests that LXR activation is exerting a different action on these two transcription factors. The analysis of publicly available ChipSeq data of human macrophages treated with LXR agonists showed that MAFB gene has LXR binding sites (data not shown). Therefore, we pretreated monocytes with CHIR99021, an inhibitor of GSK3β, before differentiating them to GW-M-MØ. CHIR99021 maintained MAFB protein expression elevated in M-MØ even in the presence of GW3965. In these conditions, we observed that the relative effect of GW3965 on antiinflammatory genes was decreased. Importantly, when we treated cells with CHIR99021 at day 5 of differentiation we observed similar results, illustrating the importance of MAFB in the effects of GW3965. Curiously, in the presence of GSK3β inhibitor, GW3965 exerted a lower upregulation of ABCA1 expression specially at day 0 treatments. ABCA1 gene suffers posttranslational modifications and LXR-independent regulations730,731. For example, CCL2, a cytokine that is regulated by MAFB195, controls ABCA1 expression in HepG2 cells732. Thus, this could mean that there is a competition between LXR and MAFB to bind to ABCA1 gene or that MAFB is repressing ABCA1 gene by an unknown mechanism. Notably, GSK2033 increased MAFB and MAF expression in both GSK-M-MØ and GSK-GM-MØ, evidencing that LXR inhibition determines the antiinflammatory macrophage polarization. We tried to deplete MAFB in monocytes, but monocyte cell viability greatly decreased upon transfecting with MAFB-specific siRNA. In the case of IRF4, we observed increased IRF4 protein expression and CCL17 production in GW-GM-MØ. IRF4 has been recently linked to GM-CSF-dependent proinflammatory polarization in human macrophages155,156, so IRF4 is probably mediating some of the LXR effects in GW-GM-MØ. The fact that IRF4 expression was unaltered in GW- M-MØ supports the idea that LXR controls human macrophage polarization by different pathways in the presence of M-CSF and GM-CSF. Surprisingly, we observed that LXR activation led to an increase in IRF4 expression but other authors have shown that LXR activation in GM-CSF-treated mouse TAM led to a decrease in IRF4 and CCL17 expression513. This could be due to the fact that different proteins of IRF family control mouse and human macrophage polarization and that LXR regulation is different between mouse and human cells189,190,246. Besides, our experiments were done treating directly the monocytes with LXR agonists while Carbó et al analyzed TAM macrophages treating mice intravenously with LXR agonists, what could activate LXR in the distinct cells of the tumor microenvironment and therefore affect IRF4 regulation. 142 Discussion PPARγ has been implicated in the generation of GM-MØ and alveolar macrophages that are highly dependent on GM-CSF39. Therefore, the upregulation of PPARγ gene (PPARG) in GW-M-MØ and GW-GM-MØ and its downregulation in GSK-M-MØ and GSK- GM-MØ supported our transcriptomic results. Considering this, we tried to analyze its implication in LXR-dependent effects. Unfortunately, we were not able to block PPARγ action using a well-known antagonist (GW9662733) as in our experiments it activated PPARγ target genes. Consequently, we activated PPARγ before treating monocytes with GSK2033 in their differentiation to GM-MØ (data not shown). We observed that activation of PPARγ in the presence of GSK2033 slightly prevented the upregulation of some antiinflammatory genes whose expression was increased in GSK-GM-MØ. LXR and PPARγ cooperation has been extensively described for several functions723,724,734,735 but these results suggest that LXR and PPARγ cooperates in the control of transcriptomic signature of human macrophages. In the future, we will analyze the transcriptome of alveolar macrophages to delve into the possible LXR-PPARγ connection. HIF1α commands hypoxia responses and regulates cellular glycolytic metabolism736. Moreover, HIF1α control production of proinflammatory mediators like ROS or IL1β, in activated macrophages112. In this sense, an enhanced HIF1α expression and consequently a greater glycolytic metabolism reshapes macrophages to acquire proinflammatory properties129. Indeed, we observed an upregulation of HIF1α gene (HIF1A) and an increased production of extracellular lactate in GW-M-MØ but not on GW-GM-MØ. These results agree with the enhanced proinflammatory phenotype of GW-M-MØ and suggest that HIF1α could have a role in LXR-dependent proinflammatory effect. In fact, two studies demonstrated that there is a crosstalk between LXR and HIF1α 1) to induce expression and production of IL1β, 2) to induce expression of glycolytic enzymes and 3) to promote a proinflammatory phenotype in monocytes and macrophages311,312. In these studies, HIF-1α inhibition abolished the impact of LXR on IL-1β mRNA expression. Unfortunately, we were not capable of inhibiting HIF1α in our experimental system. Analysis of LXR-modulated transcriptome exposes novel roles of LXR receptors and distinct gene regulation in human macrophages Gene ontology analysis of macrophages differentiated in the presence of LXR modulators revealed a plethora of novel functions that may be controlled by LXR. Antigen processing and presentation of lipids was significantly upregulated in GW-GM-MØ while unfolded protein response was significantly upregulated in GSK-GM-MØ. In the case of unfolded protein response (UPR), the predicted association to this process could be of vital importance for many pathological diseases, especially inflammatory disorders, as UPR regulation has been shown to be central in the pathogenesis of some disorders737–739. Curiously, this function was only predicted in GSK-GM-MØ and not on GSK-M-MØ, where GSK2033 had stronger effects. It is important to mention that predicted upregulation of UPR could be derived from a cellular stress that GSK2033 might be causing, independently of LXR inactivation. In the future, we will use a different LXR inverse agonist, SR9238740, to address this question. Recently, Xin Rong and colleagues related LXR activity to UPR: activation of LXR led to the upregulation of LPCAT3 enzyme that limited fatty acid-induced UPR289. We haven’t checked if LXR inactivation is increasing intracellular fatty acid content but many of the enzymes that control this route, including LPCAT3, are downregulated in GSK-GM-MØ. Curiously, we observed a downregulation of LPCAT3 in both GSK-GM-MØ and GSK-M-MØ, but we didn’t observe a predicted UPR response in GSK-M-MØ. Moreover, 143 Discussion LXR inactivation could also be affecting enzymes necessary for PUFA biosynthesis and causing UPR342. Considering all these results, we propose that LXR inactivation by GSK2033 is probably triggering unknown mechanisms that guide exclusively GM-MØ towards an endoplasmic reticulum response. Moreover, interferon response was predicted to be downregulated in GW-M-MØ and this function has not been related to LXR so far. In this sense, when we analyzed the differential expressed genes (DEG) we found that CXCR4 was upregulated in GW-GM-MØ and downregulated in GSK-GM-MØ. The connection between LXR and CXCR4 is unknown but CXCR4 has also been related to LXR-dependent proinflammatory effects in other studies312. Interestingly, we also observed AIM2 upregulated in GW-GM-MØ and downregulated in GSK-GM-MØ, a gene that is associated with the inflammasomes and consequently with IL1β activation and secretion. The link between IL1β and LXR in human monocytes has been described, but the mechanism by which LXR promotes IL1β production is only partially explored311,312. We hypothesize that LXR could increase IL1β by activation of AIM2 inflammasome. Next, we defined a number of clusters that encompassed all the possible changes in gene expression caused by LXR modulation: for example, in the case of GM-MØ, cluster 4 was composed by the genes that were upregulated in GW-GM-MØ and were downregulated in GSK-GM-MO, compared to vehicle conditions (CNT-GM-MØ). These clusters allowed us to confirm that in GW/GSK-GM-MØ or GW/GSK-M-MØ not all the genes regulated by GW3965 were blocked by pretreatment with GSK2033, as we expected since GSK2033 impedes recruitment of coactivators. Surprisingly, we found that not all of the genes that were modulated in GW-M-MØ or GW-GM-MØ were blocked in GW/GSK-M-MØ or GW/GSK- GM-MØ. Perhaps GW3965 is more potent than we expected and it is capable of moving LXR-bound GSK2033 or maybe LXR proteins have more binding sites for GW3965 that are not occupied by GSK2033. It is noticeable that LXR activity modulation affects M-MØ in a more complex way that in GM-MØ, as we observed a higher number of clusters in M-MØ than in GM-MØ. Surprisingly, we saw new functions like “antigen processing and presentation of proteins” and “interferon gamma mediated signaling pathway” that were associated with downregulated genes in GW-M-MØ. This suggest that LXR control antigen presentation of different molecules in GM-MØ and M-MØ, revealing one more time that both macrophages are really distinctive in terms of LXR-dependent regulation. All these results suggest that alteration of LXR may be beneficial or detrimental depending on the macrophages state of polarization and their microenvironment. LXR modulation alters the responses of resting and activated macrophages. Analysis of cytokine secretion by M-MØ and GM-MØ differentiated in the presence of LXR modulators revealed singular differences. The induction of TNFα was greater than IL-10 induction in GSK-GM-MØ but the total levels of both cytokines revealed that IL-10 production was higher compared to TNFα in GSK-GM-MØ. To our knowledge, there are no studies in human macrophages that link IL-10 production with LXR inactivation. Considering LXR inactivation have the opposite effect in IL-10 production in M-MØ, maybe LXR inactivation is affecting M-CSF and GM-CSF-dependent signaling in different directions, altering the production of this cytokine. Recent experiments demonstrated that, in contrast to our results, LXR activation cause the secretion of TNFα of human monocytes668, what suggest that TNFα increased production could be an indirect consequence of LXR inactivation. In the case of 144 Discussion LPS-activated macrophages, we observed an increased production of IL-10 and TNFα in LPS-activated macrophages. Recently investigations showed that LXR potentiate LPS response in monocytes by a training potentiation mechanism311. We here also observed a mechanism of training potentiation, not only in TNF-α but also for other proinflammatory cytokines like IL-6 or IL-1β. The experimental conditions we used were similar since Sohrabi and colleagues312 stimulated their cells during 6 days and we stimulated them during 7 days. The only difference is that we added M-CSF or GM-CSF during differentiation while they differentiate the monocytes in the presence of human serum. In our experience, monocytes don’t differentiate into macrophages in the presence of human serum, so this has to be taking in consideration when comparing these results. Recently, it was reported that GM- CSF and IL-3 priming enhanced TNF-α production in LPS-activated monocytes741. Thus, LXR activation could be inducing proinflammatory cytokine secretion by a training mechanism that is dependent of GM-CSF or LXR activation may be potentiating GM-CSF signaling in monocytes. Sohrabi et al312, showed that LXR-dependent training potentiation was regulated by IL1β but as we said our macrophages are not differentiated under the same culture conditions. Besides, it is surprising that GW3965 is capable of also increase the secretion of IL-10. A possible explanation is that LXR activation is elevating the levels of extracellular TNFα to a point that the cells response in an autocrine way to increase their production of IL-10, in order to contain that inflammation. Besides, we observed significantly greater production of IL1β only in LPS-activated macrophages, what was also observed by other groups311,312. As we previously commented, we observed an upregulation of AIM2 protein in GW-GM-MØ but not in GW-M-MØ. In this sense, it was previously described that SREBP regulates the mouse NLRP1 inflammasomes367,368 and IL1β production. Thus, maybe LXR guide IL1β production by two different mechanisms: direct activation of AIM2 inflammasome in GM-MØ and SREBP- dependent activation of NLRP1 inflammasome in M-MØ. Of note, Sohrabi et al found that depletion or inhibition of SREBP1 superinduced the training capacity of LXR312 but as we noted before, the culture conditions that they used were different than ours. GW-GM-MØ showed an increase in their capacity to induce T cell proliferation whereas both GW-M-MØ and GSK-M-MØ display a diminished ability to stimulate T cell proliferation. GW-M-MØ results agree with our gene ontology analyses in which genes that were associated with “antigen processing and presentation of proteins” (including HLA-DR) were downregulated. In GSK-M-MØ we didn’t observe downregulation of these proteins and considering GSK-GM-MØ did not increase or decrease T cell proliferation we wonder if LXR inactivation is affecting other pathways that could be hindering T cell proliferation. For example, LXR inactivation could lead to a decrease in the availability of extracellular fatty acids and cholesterol that could affect T lymphocyte proliferation. Of note, for these experiments, we used low concentrations of human serum. Furthermore, LXR regulate some aspects of T lymphocyte proliferation and differentiation223,304,742 but, in this case, the modulators were not present in the final coculture so we discard that possibility. Altogether, this implies that LXR may be directly regulating HLA-DR proteins and coreceptors that intervene in the immunological synapsis between macrophages and T lymphocytes. Besides, previous transcriptomic analysis of GW-GM-MØ predicted an enrichment of genes associated to “antigen processing and presentation of lipids”. Indeed, CD1B, CD1D and CD1E expression was upregulated in GW-GM-MØ (data not shown). Our results point to the fact that LXR is regulating antigen processing and presentation in macrophages and to our knowledge no one has currently implied LXR transcription factors in this important process. 145 Discussion LXR direct the polarization effect of pathological fluids on human monocytes The use of pathological fluids is a potential tool for the in vitro study on how the microenvironment affects monocyte or macrophage polarization. Here, we have shown that LXR dominate the response of monocytes to synovial fluid (RASF)- or tumor fluid (TAF)- driven polarization. Our results revealed that both pathological stimuli altered LXR activity in monocytes, what might have implications for in vivo conditions. We also showed that modulating LXR activity in monocytes causes a stronger effect than in macrophages. Thus, we propose that LXR alteration in monocytes might be a useful strategy for these inflammatory diseases, as this procedure would re-program monocytes recruited into either affected joints or tumors. Besides, previous research determined that LXR pathway was the most enriched in synovial macrophages225 and colon “large TAM”226, supporting our idea that modifying LXR activity at the monocyte stage would be effective. Nevertheless, the dose of available synthetic LXR activators should be adjusted to avoid hepatic consequences 232,340. In this regard, the use of these pathological fluids in vitro might allow the identification of the specific molecular cues that determine macrophage polarization, through the use of different biochemistry techniques. As an example, the sequential use of biochemical fractionation (chromatography), transcriptional and functional screening and proteomics (mass spectrometry) might identify the specific molecule(s) that affect macrophage polarization. We anticipate that it is highly unlikely that a single molecule is responsible for the observed effects of RASF or TAF, and postulate that their effects are caused by a combination of different factors. For instance, in the case of tumour microenvironment, although the majority of TAM acquire a tumour-supporting antiinflammatory phenotype, TAM with a proinflammatory or mixed phenotype also exist, what reinforces our prediction. Notably, whereas GM-CSF might favor the proinflammatory effect of RASF, RASF greatly differ in their GM-CSF content205, further suggesting the existence of other molecules contributing to the polarizing action of RASF. The identification of these molecules is of special relevance for the design of specific therapies for these inflammatory diseases. In the second part of the thesis, we aimed to unravel if LXR was involved in the AhR- dependent macrophage polarization. Previous findings of our lab showed that the M-MØ transcriptome was significantly enriched in AhR target genes, whereas the GM-MØ transcriptome was enriched in genes negatively regulated by AhR. Considering the plethora of endogenous ligands that AhR has, we decided to differentiate monocytes to M-MØ in the presence of an AhR inhibitor (CH233191). AhR-inhibited macrophages (CH-M-MØ) developed a proinflammatory phenotype, characterized by 1) greater secretion of proinflammatory cytokines and lower production of antiinflammatory cytokines in response to LPS, 2) increased glycolytic metabolism associated to an upregulation of HIF1α and an increment of lactate production, 3) greater antigen presentation to T lymphocytes and 4) a positive enrichment of the proinflammatory gene set. Our results contradict previous studies that showed that AhR activation instruct monocytes to differentiate into dendritic cells while impairing their differentiation into macrophages414. These experiments were performed using 146 Discussion an in vitro culture system where macrophage differentiation was achieved using M-CSF and dendritic cells were generated using M-CSF, IL-4 and TNF414. Thus, it is possible that the distinct effect of AhR in our studies derive from differences in the culture system used for monocyte-to-macrophage differentiation. LXRα protein expression was highly upregulated in CH-M-MØ and this translated to a greater protein expression of bona fide LXR targets ABCA1 and ABCG1. However, some other LXR target genes were downregulated in CH-M- MØ (data not shown). Previously, we reported that LXR target genes showed a dual distribution between M-MØ and GM-MØ (figure 27). Here, we observed that all the M-MØ- associated LXR target genes were downregulated in CH-M-MØ while all the GM-MØ- associated LXR target genes were upregulated in CH-M-MØ. Curiously, we showed that ABCA1 was preferentially expressed in M-MØ while ABCG1 was mainly expressed in GM- MØ but AhR-inhibition seemed to upregulate both transporters. This suggests that AhR- dependent upregulation of LXRα is regulating macrophage polarization but not controlling LXR-dependent cholesterol efflux or lipid metabolism. In this sense, when we preincubated CH-M-MØ with LXR inverse agonist GSK2033, we observed that some of the proinflammatory effects caused by AhR inhibition were blocked. However, we found that upregulation of SREBF1, SREBF2 and SREBP2 target genes in CH-M-MØ was completely dependent on LXR. The relationship between AhR and SREBP has been described in hepatocytes437,438 but not in macrophages. In fact, Rachel Tanos et al437, showed that AhR regulate biosynthetic genes independent of a XRE-response element. Our results suggest that LXR could be the nexus between both processes in hepatocytes. That being said, here we show that AhR and LXR regulate expression of SREBF1, SREBF2 and SREBP2 target genes in human macrophages. Besides, we describe a crosstalk between AhR and LXR to regulate several routes that lead to macrophage proinflammatory polarization. Curiously, AhR-dependent upregulation of cholesterol biosynthetic genes correlates with a proinflammatory shift of M-MØ, what is in line with the preferential expression of SREBP and their target genes in GM-MØ (data not shown). Importantly, these results suggest that AhR KO mice could either develop hepatic damage and have elevated levels of cholesterol and hepatic enzymes because of a constitutive upregulation of LXRα and SREBP1/2 or either could be more resistant to atherosclerosis or cholesterol related diseases because LXRα upregulation would impede intracellular cholesterol excess. Consequently, modulation of AhR activity might constitute a potential strategy to reprogram macrophages in inflammatory pathologies but considering the possible effects on AhR-dependent regulation of LXR and SREBP. CONCLUSIONS Conclusions 148 The conclusions for this doctoral thesis work are: 1. The expression of LXRα and LXRβ proteins, and their encoding genes, is dependent on the macrophage polarization state. 2. Modulation of LXR activity in fully differentiated M-MØ and GM-MØ has a minor effect on their respective transcriptional profiles. 3. Modulation of LXR activity in human monocytes greatly influences their differentiation into M-MØ or GM-MØ in response to M-CSF or GM-CSF, respectively. LXR over- activation skews macrophages to acquire a proinflammatory transcriptional and functional profile, while LXR activity inhibition prompts the generation of macrophages with stronger antiinflammatory transcriptional and functional profile. 4. LXR regulate numerous new target genes and new predicted biological functions in M-MØ and GM-MØ. Specifically, Unfolded Protein Response appears as the most significant function in GSK-GM-MØ. 5. LXR over-activation impairs the capacity of tumor-derived ascitic fluids to promote the acquisition of an antiinflammatory transcriptional profile in monocyte-derived macrophages. 6. LXR activity inhibition hinders the capacity of rheumatoid arthritis synovial to promote the acquisition of a proinflammatory transcriptional profile in monocyte-derived macrophages. 7. LXR activity modulation alters the expression of transcription factors that regulate human macrophage polarization: a) LXR over-activation upregulates PPARγ and IRF4, which mediate GM-CSF-dependent polarization, and downregulates MAFB and MAF, which mediate M-CSF-dependent polarization; b) LXR inhibition upregulates MAFB and MAF and downregulates PPARγ. 8. The diminished expression of MAFB contributes to the proinflammatory effect of the LXR agonist in macrophages, as suggested in experiments using a GSK3β inhibitor. 9. 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Tesis Arturo González de la Aleja Molina PORTADA INDEX ILLUSTRATION INDEX TABLE INDEX ABBREVIATIONS RESUMEN ABSTRACT INTRODUCTION HYPOTHESIS AND OBJECTIVES EXPERIMENTAL PROCEDURES RESULTS DISCUSSION CONCLUSIONS REFERENCES DDña: Arturo González de la Aleja Molina estudiante en el Programa de Doctorado: Bioquímica, Biología Molecular y Biomedicina Facultades: [Ciencias Químicas] dia: [3] mes: [febrero] año: [22] titulada 1: Liver X Receptors command the transcriptional and functional polarization of human macrophages y dirigida por 1: Ángel Luis Corbí López y Antonio Castrillo Viguera y dirigida por 2: y dirigida por 3: titulada 2: