Exploring Metabolic Signatures of Ex Vivo Tumor Tissue Cultures for Prediction of Chemosensitivity in Ovarian Cancer

التفاصيل البيبلوغرافية
العنوان: Exploring Metabolic Signatures of Ex Vivo Tumor Tissue Cultures for Prediction of Chemosensitivity in Ovarian Cancer
المؤلفون: Rita Mendes, Gonçalo Graça, Fernanda Silva, Ana C. L. Guerreiro, Patrícia Gomes-Alves, Jacinta Serpa, Erwin R. Boghaert, Paula M. Alves, Ana Félix, Catarina Brito, Inês A. Isidro
المساهمون: Instituto de Tecnologia Química e Biológica António Xavier (ITQB), NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM), iNOVA4Health - pólo NMS
المصدر: Cancers; Volume 14; Issue 18; Pages: 4460
بيانات النشر: MDPI AG, 2022.
سنة النشر: 2022
مصطلحات موضوعية: ovarian carcinoma, Cancer Research, SDG 3 - Good Health and Well-being, Oncology, ex vivo models, drug response, biomarkers, chemoresistance, tumor microenvironment, metabolomics
الوصف: Predicting patient response to treatment and the onset of chemoresistance are still major challenges in oncology. Chemoresistance is deeply influenced by the complex cellular interactions occurring within the tumor microenvironment (TME), including metabolic crosstalk. We have previously shown that ex vivo tumor tissue cultures derived from ovarian carcinoma (OvC) resections retain the TME components for at least four weeks of culture and implemented assays for assessment of drug response. Here, we explored ex vivo patient-derived tumor tissue cultures to uncover metabolic signatures of chemosensitivity and/or resistance. Tissue cultures derived from nine OvC cases were challenged with carboplatin and paclitaxel, the standard-of-care chemotherapeutics, and the metabolic footprints were characterized by LC-MS. Partial least-squares discriminant analysis (PLS-DA) revealed metabolic signatures that discriminated high-responder from low-responder tissue cultures to ex vivo drug exposure. As a proof-of-concept, a set of potential metabolic biomarkers of drug response was identified based on the receiver operating characteristics (ROC) curve, comprising amino acids, fatty acids, pyrimidine, glutathione, and TCA cycle pathways. Overall, this work establishes an analytical and computational platform to explore metabolic features of the TME associated with response to treatment, which can leverage the discovery of biomarkers of drug response and resistance in OvC. publishersversion published
وصف الملف: application/pdf
تدمد: 2072-6694
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a12fbf64d92535b85a8fc35309ccee04Test
https://doi.org/10.3390/cancers14184460Test
حقوق: OPEN
رقم الانضمام: edsair.doi.dedup.....a12fbf64d92535b85a8fc35309ccee04
قاعدة البيانات: OpenAIRE