The potential of cell-free and exosomal microRNAs as biomarkers in liquid biopsy in patients with prostate cancer

Autor: Monyse de Nóbrega, Mariana Bisarro dos Reis, Érica Romão Pereira, Marilesia Ferreira de Souza, Ilce Mara de Syllos Cólus
Rok vydání: 2022
Předmět:
Zdroj: Journal of Cancer Research and Clinical Oncology. 148:2893-2910
ISSN: 1432-1335
0171-5216
DOI: 10.1007/s00432-022-04213-9
Popis: Prostate cancer (PCa) is the 4th most diagnosed cancer and the 8th leading cause of cancer-related death worldwide. Currently, clinical risk stratification models including factors like PSA levels, Gleason score, and digital rectal examination are used for this purpose. There is a need for novel biomarkers that can distinguish between indolent and aggressive pathology and reduce the risk of overdiagnosis/overtreatment. Liquid biopsy has a non-invasive character, can lead to less morbidity and provide new biomarkers, such as miRNAs, that regulate diverse important cellular processes. Here, we report an extended revision about the role of cell-free and exosomal miRNAs (exomiRNAs) as biomarkers for screening, diagnosis, prognosis, or treatment of PCa.A comprehensive review of the published literature was conducted focusing on the usefulness, advantages, and clinical applications of cell-free and exomiRNAs in serum and plasma. Using PubMed database 53 articles published between 2012 and 2021 were selected and discussed from the perspective of their use as diagnostic, prognostic and therapeutic biomarkers for PCa.We identify 119 miRNAs associated with PCa development and the cell-free and exosomal miR-21, miR-141, miR-200c, and miR-375 were consistently associated with progression in multiple cohorts/studies. However, standardized experimental procedures, and well-defined and clinically relevant cohort studies are urgently needed to confirm the biomarker potential of cell-free and exomiRNAs in serum or plasma.Cell-free and exomiRNAs in serum or plasma are promising tools for be used as non-invasive biomarkers for diagnostic, prognosis, therapy improvement and clinical outcome prediction in PCa patients.
Databáze: OpenAIRE
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