1. A combination of molecular and clinical parameters provides a new strategy for high-grade serous ovarian cancer patient management
- Author
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Melissa Bradbury, Eva Borràs, Marta Vilar, Josep Castellví, José Luis Sánchez-Iglesias, Assumpció Pérez-Benavente, Antonio Gil-Moreno, Anna Santamaria, Eduard Sabidó, Institut Català de la Salut, [Bradbury M] Centre de Regulació Genòmica, Barcelona Institute of Science and Technology (BIST), Barcelona, Spain. Universitat Pompeu Fabra, Barcelona, Spain. Grup de Recerca Biomèdica en Ginecologia, Vall d’Hebron Institut de Recerca (VHIR), Barcelona, Spain. Universitat Autònoma de Barcelona, Bellaterra, Spain. Servei de Ginecologia, Vall d’Hebron Hospital Universitari, Barcelona, Spain. [Borràs E, Sabidó E] Centre de Regulació Genòmica, Barcelona Institute of Science and Technology (BIST), Barcelona, Spain. Universitat Pompeu Fabra, Barcelona, Spain. [Vilar M] Centre de Regulació Genòmica, Barcelona Institute of Science and Technology (BIST), Barcelona, Spain. Grup de Recerca Biomèdica en Ginecologia, Vall d’Hebron Institut de Recerca (VHIR), Barcelona, Spain. Universitat Autònoma de Barcelona, Bellaterra, Spain. [Castellví J] Servei d’Anatomia Patològica, Vall d’Hebron Hospital Universitari, Barcelona, Spain. [Sánchez-Iglesias JL, Pérez-Benavente A] Grup de Recerca Biomèdica en Ginecologia, Vall d’Hebron Institut de Recerca (VHIR), Barcelona, Spain. Universitat Autònoma de Barcelona, Bellaterra, Spain. Servei de Ginecologia, Vall d’Hebron Hospital Universitari, Barcelona, Spain. [Gil-Moreno A] Grup de Recerca Biomèdica en Ginecologia, Vall d’Hebron Institut de Recerca (VHIR), Barcelona, Spain. Universitat Autònoma de Barcelona, Bellaterra, Spain. Servei de Ginecologia, Vall d’Hebron Hospital Universitari, Barcelona, Spain. Centro de Investigación Biomédica en Red (CIBERONC), Instituto de Salud Carlos III, Madrid, Spain. [Santamaria A] Grup de Recerca Biomèdica en Ginecologia, Vall d’Hebron Institut de Recerca (VHIR), Barcelona, Spain. Universitat Autònoma de Barcelona, Bellaterra, Spain. Laboratori de Cicle Cel·lular i Càncer, Grup de Recerca Biomèdica en Urologia, Vall d’Hebron Institut de Recerca (VHIR), Barcelona, Spain. Universitat Autònoma de Barcelona, Bellaterra, Spain, and Vall d'Hebron Barcelona Hospital Campus
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Proteomics ,Ovarian Neoplasms ,Neoplasms::Neoplasms by Site::Endocrine Gland Neoplasms::Ovarian Neoplasms [DISEASES] ,Marcadors tumorals ,Otros calificadores::Otros calificadores::/farmacoterapia [Otros calificadores] ,factores biológicos::biomarcadores::marcadores tumorales [COMPUESTOS QUÍMICOS Y DROGAS] ,Proteins ,General Medicine ,Ovaris - Càncer - Tractament ,neoplasias::neoplasias por localización::neoplasias de las glándulas endocrinas::neoplasias ováricas [ENFERMEDADES] ,Other subheadings::Other subheadings::/drug therapy [Other subheadings] ,General Biochemistry, Genetics and Molecular Biology ,Cystadenocarcinoma, Serous ,Neoplasms::Neoplasms by Histologic Type::Neoplasms, Glandular and Epithelial::Carcinoma::Adenocarcinoma::Cystadenocarcinoma::Cystadenocarcinoma, Serous [DISEASES] ,Biomarkers, Tumor ,Humans ,Female ,Biological Factors::Biomarkers::Biomarkers, Tumor [CHEMICALS AND DRUGS] ,neoplasias::neoplasias por tipo histológico::neoplasias glandulares y epiteliales::carcinoma::adenocarcinoma::cistoadenocarcinoma::cistoadenocarcinoma seroso [ENFERMEDADES] - Abstract
Biomarker; Prediction; Proteomics Biomarcador; Predicción; Proteómica Biomarcador; Predicció; Proteòmica Background High-grade serous carcinoma (HGSC) is the most common and deadly subtype of ovarian cancer. Although most patients will initially respond to first-line treatment with a combination of surgery and platinum-based chemotherapy, up to a quarter will be resistant to treatment. We aimed to identify a new strategy to improve HGSC patient management at the time of cancer diagnosis (HGSC-1LTR). Methods A total of 109 ready-available formalin-fixed paraffin-embedded HGSC tissues obtained at the time of HGSC diagnosis were selected for proteomic analysis. Clinical data, treatment approach and outcomes were collected for all patients. An initial discovery cohort (n = 21) were divided into chemoresistant and chemosensitive groups and evaluated using discovery mass-spectrometry (MS)-based proteomics. Proteins showing differential abundance between groups were verified in a verification cohort (n = 88) using targeted MS-based proteomics. A logistic regression model was used to select those proteins able to correctly classify patients into chemoresistant and chemosensitive. The classification performance of the protein and clinical data combinations were assessed through the generation of receiver operating characteristic (ROC) curves. Results Using the HGSC-1LTR strategy we have identified a molecular signature (TKT, LAMC1 and FUCO) that combined with ready available clinical data (patients’ age, menopausal status, serum CA125 levels, and treatment approach) is able to predict patient response to first-line treatment with an AUC: 0.82 (95% CI 0.72–0.92). Conclusions We have established a new strategy that combines molecular and clinical parameters to predict the response to first-line treatment in HGSC patients (HGSC-1LTR). This strategy can allow the identification of chemoresistance at the time of diagnosis providing the optimization of therapeutic decision making and the evaluation of alternative treatment strategies. Thus, advancing towards the improvement of patient outcome and the individualization of HGSC patients’ care. This work was supported by the PhD4MD collaborative research program between the Vall d’Hebron Research Institute (VHIR) and the Centre for Genomic Regulation (CRG). It has been supported by grants from the Instituto Carlos III (PI18/01017), the Miguel Servet Program (CPII18/00027) and the Ministerio de Economía y Competitividad y Fondos FEDER (RTC-2015-3821-1 to AS and CTQ2016-80364-P to ES). This project has also received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 823839 (EPIC-XS).The CRG/UPF Proteomics Unit is part of the Spanish Infrastructure for Omics Technologies (ICTS OmicsTech) and it is supported by “Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement de la Generalitat de Catalunya” (2017SGR595 and 2017SGR1661). We also acknowledge support of the Spanish Ministry of Science and Innovation to the EMBL partnership, the Centro de Excelencia Severo Ochoa and the CERCA Programme / Generalitat de Catalunya.
- Published
- 2022