Metabolomics Contributions to the Discovery of Prostate Cancer Biomarkers
Prostate cancer (PCa) is one of the most frequently diagnosed cancers and a leading cause of death among men worldwide. Despite extensive efforts in biomarker discovery during the last years, currently used clinical biomarkers are still lacking enough specificity and sensitivity for PCa early detect...
| Autores: | , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2019 |
| País: | España |
| Institución: | Universidad Católica de Valencia San Vicente Mártir |
| Repositorio: | RIUCV. Repositorio de la Universidad Católica de Valencia San Vicente Mártir |
| Idioma: | inglés |
| OAI Identifier: | oai:riucv.ucv.es:20.500.12466/5030 |
| Acceso en línea: | http://hdl.handle.net/20.500.12466/5030 |
| Access Level: | acceso abierto |
| Palabra clave: | Metabolomics Metabolism Prostate cancer Biomarkers Early diagnosis Prognosis 3201.01 Oncología |
| Sumario: | Prostate cancer (PCa) is one of the most frequently diagnosed cancers and a leading cause of death among men worldwide. Despite extensive efforts in biomarker discovery during the last years, currently used clinical biomarkers are still lacking enough specificity and sensitivity for PCa early detection, patient prognosis, and monitoring. Therefore, more precise biomarkers are required to improve the clinical management of PCa patients. In this context, metabolomics has shown to be a promising and powerful tool to identify novel PCa biomarkers in biofluids. Thus, changes in polyamines, tricarboxylic acid (TCA) cycle, amino acids, and fatty acids metabolism have been reported in different studies analyzing PCa patients’ biofluids. The review provides an up-to-date summary of the main metabolic alterations that have been described in biofluid-based studies of PCa patients, as well as a discussion regarding their potential to improve clinical PCa diagnosis and prognosis. Furthermore, a summary of the most significant findings reported in these studies and the connections and interactions between the different metabolic changes described has also been included, aiming to better describe the specific metabolic signature associated to PCa. |
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