Person:
Díaz Del Arco, Cristina

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First Name
Cristina
Last Name
Díaz Del Arco
URI
https://hdl.handle.net/20.500.14352/86470
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Medicina
Department
Medicina Legal, Psiquiatría y Patología
Area
Anatomía Patológica
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UCM identifierORCIDScopus Author IDWeb of Science ResearcherIDDialnet IDGoogle Scholar ID

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Author: Fernández Aceñero, María Jesús ×

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    p53 and p63 Proteoforms Derived from Alternative Splicing Possess Differential Seroreactivity in Colorectal Cancer with Distinct Diagnostic Ability from the Canonical Proteins
    (Cancers, 2023) Montero Calle, Ana; Garranzo Asensio, María; Torrente Rodríguez, Rebeca Magnolia; Ruiz Valdepeñas Montiel, Víctor; Poves, Carmen; Dziakova, Jana; Sanz, Rodrigo; Díaz Del Arco, Cristina; Pingarrón Carrazón, José Manuel; Fernández Aceñero, María Jesús; Campuzano Ruiz, Susana; Barderas Manchado, Rodrigo
    Colorectal cancer (CRC) is the third most common cancer and the second most frequent cause of cancer-related death worldwide. The detection in plasma samples of autoantibodies against specific tumor-associated antigens has been demonstrated to be useful for the early diagnosis of CRC by liquid biopsy. However, new studies related to the humoral immune response in cancer are needed to enable blood-based diagnosis of the disease. Here, our aim was to characterize the humoral immune response associated with the different p53 and p63 proteoforms derived from alternative splicing and previously described as aberrantly expressed in CRC. Thus, here we investigated the diagnostic ability of the twelve p53 proteoforms and the eight p63 proteoforms described to date, and their specific N-terminal and C-terminal end peptides, by means of luminescence HaloTag beads immunoassays. Full-length proteoforms or specific peptides were cloned as HaloTag fusion proteins and their seroreactivity analyzed using plasma from CRC patients at stages I-IV (n = 31), individuals with premalignant lesions (n = 31), and healthy individuals (n = 48). p53γ, Δ40p53β, Δ40p53γ, Δ133p53γ, Δ160p53γ, TAp63α, TAp63δ, ΔNp63α, and ΔNp63δ, together with the specific C-terminal end α and δ p63 peptides, were found to be more seroreactive against plasma from CRC patients and/or individuals with premalignant lesions than from healthy individuals. In addition, ROC (receiver operating characteristic) curves revealed a high diagnostic ability of those p53 and p63 proteoforms to detect CRC and premalignant individuals (AUC higher than 85%). Finally, electrochemical biosensing platforms were employed in POC-like devices to investigate their usefulness for CRC detection using selected p53 and p63 proteoforms. Our results demonstrate not only the potential of these biosensors for the simultaneous analysis of proteoforms’ seroreactivity, but also their convenience and versatility for the clinical detection of CRC by liquid biopsy. In conclusion, we here show that p53 and p63 proteoforms possess differential seroreactivity in CRC patients in comparison to controls, distinctive from canonical proteins, which should improve the diagnostic panels for obtaining a blood-based biomarker signature for CRC detection.
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    Impact of Age at Diagnosis on Clinicopathological Features, Prognosis, and Management of Gastric Cancer: A Retrospective Single-Center Experience from Spain
    (Cancers, 2023) Estrada Muñoz, Lourdes; Molina Roldán, Elena; García Gómez de las Heras, Soledad; Díaz Del Arco, Cristina; Ortega Medina, Luis; Fernández Aceñero, María Jesús
    The incidence of renal mass detection has increased during recent decades, with an increased diagnosis of small renal masses, and a final benign diagnosis in some cases. To avoid unnecessary surgeries, there is an increasing interest in using radiomics tools to predict histological results, using radiological features. We performed a narrative review to evaluate the use of radiomics in renal mass characterization. Conventional images, such as computed tomography (CT) and magnetic resonance (MR), are the most common diagnostic tools in renal mass characterization. Distinguishing between benign and malignant tumors in small renal masses can be challenging using conventional methods. To improve subjective evaluation, the interest in using radiomics to obtain quantitative parameters from medical images has increased. Several studies have assessed this novel tool for renal mass characterization, comparing its ability to distinguish benign to malign tumors, the results in differentiating renal cell carcinoma subtypes, or the correlation with prognostic features, with other methods. In several studies, radiomic tools have shown a good accuracy in characterizing renal mass lesions. However, due to the heterogeneity in the radiomic model building, prospective and external validated studies are needed.