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A piece in prostate cancer puzzle: Future perspective of novel molecular signatures

Prostate cancer (PCa) has a variable biological potential. It constitutes the second most common cancer amongst men worldwide and the fifth most common cancer in Saudi Arabia. Identifying men at higher risk of developing PCa, differentiating indolent from aggressive disease and predicting the likeli...

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Detalles Bibliográficos
Autor principal: Nassir, Anmar M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7105665/
https://www.ncbi.nlm.nih.gov/pubmed/32256177
http://dx.doi.org/10.1016/j.sjbs.2020.02.003
Descripción
Sumario:Prostate cancer (PCa) has a variable biological potential. It constitutes the second most common cancer amongst men worldwide and the fifth most common cancer in Saudi Arabia. Identifying men at higher risk of developing PCa, differentiating indolent from aggressive disease and predicting the likelihood of progression will improve decision-making and selection for active surveillance protocols. Biomarkers have been utilized for PCa screening and predicting cancer behavior and response to treatment. The prostate specific antigen (PSA) screening helps detect PCa in early stages, while implementing a plan for management and outcome. However, PSA screening is still controversial, due to the risks of over diagnosis and treatment, and its inability to detect a good proportion of advanced tumors. Alternatively, a new era of PCa biomarkers has emerged with higher PCa specificity than PSA and its isoforms hopefully improving screening methods, such as Prostate Health Index (PHI) score, Progensa Prostate Cancer Antigen 3 (PCA3), Mi-Prostate Score (MiPS), Prostate Stem Cell Antigen (PSCA), 4Kscore test, and Urokinase Plasminogen Activation (uPA and uPAR). Few novel biomarkers have shown promise in preliminary results. This review will display promising biomarkers including some important FDA approved ones, highlighting their clinical implication and future place in the PCa puzzle, along with addressing their current limitations.