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Comprehensive Plasma Metabolomic Profile of Patients with Advanced Neuroendocrine Tumors (NETs). Diagnostic and Biological Relevance

dc.contributor.authorSoldevilla, Beatriz
dc.contributor.authorLópez López, Angeles
dc.contributor.authorLens Pardo, Alberto
dc.contributor.authorCarretero Puche, Carlos
dc.contributor.authorLopez Gonzalvez, Angeles
dc.contributor.authorLa Salvia, Anna
dc.contributor.authorGil Calderon, Beatriz
dc.contributor.authorRiesco Martinez, Maria C.
dc.contributor.authorEspinosa Olarte, Paula
dc.contributor.authorSarmentero, Jacinto
dc.contributor.authorRubio-Cuesta, Beatriz
dc.contributor.authorRincón, Raúl
dc.contributor.authorBarbas, Coral
dc.contributor.authorGarcía Carbonero, Rocío
dc.date.accessioned2023-06-17T08:32:39Z
dc.date.available2023-06-17T08:32:39Z
dc.date.issued2021-05-27
dc.descriptionThis work was partially funded by Pfizer, Project G1808 from the Spanish National Taskforce on Neuroendocrine Tumors (GETNE), Ministry of Science, Innovation and Universities of Spain (MICINN) and FEDER funding (Ref. RTI2018-095166-B-I00) and Autonomous Community of Madrid (NOVELREN-CM. Ref: B2017/BMD3751). B.S. is funded by AECC (POSTDO46SOLD, Spain). A.L.-L. thanks CEU-International Doctoral School (CEINDO) for her fellowship. A.L.-P. is funded by CAM (PEJD-2019-PRE/BMD-17058, Progama de Empleo Juvenil (YEI), co-funded by European Union (ERDF/ESF, “Investing in your future”). C.C.-P. was partially funded by CAM (PEJD-2016-PRE/BMD-2666). B.R.-C. was partially funded by CAM (PEJD-2017-PRE/BMD-4981). ALS is funded by Instituto de Salud Carlos III (Contrato Rio Hortega). M.R.-M. is funded by AECC (CLSEN19003RIES).
dc.description.abstractPurpose: High-throughput “-omic” technologies have enabled the detailed analysis of metabolic networks in several cancers, but NETs have not been explored to date. We aim to assess the metabolomic profile of NET patients to understand metabolic deregulation in these tumors and identify novel biomarkers with clinical potential. Methods: Plasma samples from 77 NETs and 68 controls were profiled by GC−MS, CE−MS and LC−MS untargeted metabolomics. OPLS-DA was performed to evaluate metabolomic differences. Related pathways were explored using Metaboanalyst 4.0. Finally, ROC and OPLS-DA analyses were performed to select metabolites with biomarker potential. Results: We identified 155 differential compounds between NETs and controls. We have detected an increase of bile acids, sugars, oxidized lipids and oxidized products from arachidonic acid and a decrease of carnitine levels in NETs. MPA/MSEA identified 32 enriched metabolic pathways in NETs related with the TCA cycle and amino acid metabolism. Finally, OPLS-DA and ROC analysis revealed 48 metabolites with diagnostic potential. Conclusions: This study provides, for the first time, a comprehensive metabolic profile of NET patients and identifies a distinctive metabolic signature in plasma of potential clinical use. A reduced set of metabolites of high diagnostic accuracy has been identified. Additionally, new enriched metabolic pathways annotated may open innovative avenues of clinical research.
dc.description.departmentDepto. de Medicina
dc.description.facultyFac. de Medicina
dc.description.refereedTRUE
dc.description.sponsorshipUnión Europea
dc.description.sponsorshipMinisterio de Ciencia e Innovación (España)
dc.description.sponsorshipComunidad de Madrid
dc.description.sponsorshipGrupo Español de Tumores Neuroendocrinos y Endocrinos (GETNE)
dc.description.sponsorshipAsociación Española Contra el Cáncer (AECC)
dc.description.sponsorshipInstituto de Salud Carlos III
dc.description.sponsorshipPfizer
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/77540
dc.identifier.doi10.3390/cancers13112634
dc.identifier.issn2072-6694
dc.identifier.officialurlhttps://doi.org/10.3390/cancers13112634
dc.identifier.relatedurlhttps://www.mdpi.com/2072-6694/13/11/2634
dc.identifier.urihttps://hdl.handle.net/20.500.14352/7406
dc.issue.number11
dc.journal.titleCancers
dc.language.isoeng
dc.page.initial2634
dc.publisherMDPI
dc.relation.projectIDFEDER
dc.relation.projectIDRTI2018-095166-B-I00
dc.relation.projectIDNOVELREN-CM. Ref: B2017/BMD3751 ; PEJD-2019-PRE/BMD-17058 ; Programa de Empleo Juvenil ; PEJD-2016-PRE/BMD-2666 , PEJD-2017-PRE/BMD-4981
dc.relation.projectIDProject G1808
dc.relation.projectIDPOSTDO46SOLD ; CLSEN19003RIES
dc.relation.projectIDContrato Rio Hortega
dc.rightsAtribución 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/es/
dc.subject.cdu616-006-089.5
dc.subject.keywordNETs
dc.subject.keywordDisease modelling
dc.subject.keywordMachine learning
dc.subject.keywordMetabolic signaling
dc.subject.keywordMolecular pathways
dc.subject.keywordPlasma metabolites
dc.subject.keywordDiagnostic biomarkers
dc.subject.ucmMedicina
dc.subject.ucmOncología
dc.subject.unesco32 Ciencias Médicas
dc.subject.unesco3201.01 Oncología
dc.titleComprehensive Plasma Metabolomic Profile of Patients with Advanced Neuroendocrine Tumors (NETs). Diagnostic and Biological Relevance
dc.typejournal article
dc.volume.number13
dspace.entity.typePublication
relation.isAuthorOfPublicationa3e10db8-836b-4582-9b84-86b538b02ea1
relation.isAuthorOfPublication.latestForDiscoverya3e10db8-836b-4582-9b84-86b538b02ea1

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