Tissue-based biomarkers in prostate cancer. Issue 5 (3rd September 2017)

• Record Type: Journal Article
• Authors: Clinton, Timothy N.; Bagrodia, Aditya; Lotan, Yair; Margulis, Vitaly; Raj, Ganesh V.; Woldu, Solomon L.
• Is Part Of: Expert review of precision medicine and drug development. Volume 2:Issue 5(2017)
• Page Start: 249
• Page End: 260
• Publication Date: 2017-09-03
• Subjects: Active surveillance -- adjuvant therapy -- biomarker -- genomics -- prostate cancer; Personalized medicine -- Periodicals; Drug development -- Periodicals; 615.19005
• DOI: 10.1080/23808993.2017.1372687
• Languages: English
• ISSNs: 2380-8993

Abstract

ABSTRACT: Introduction : Prostate cancer is a heterogeneous disease. Existing risk stratification tools based on standard clinlicopathologic variables (prostate specific antigen [PSA], Gleason score, and tumor stage) provide a modest degree of predictive ability. Advances in high-throughput sequencing has led to the development of several novel tissue-based biomarkers that can improve prognostication in prostate cancer management. Areas covered : The authors review commercially-available, tissue-based biomarker assays that improve upon existing risk-stratification tools in several areas of prostate cancer management, including the appropriateness of active surveillance and aiding in decision making regarding the use of adjuvant therapy. Additionally, some of the obstacles to the widespread adoption of these biomarkers and discuss several investigational sources of new biomarkers are discussed. Expert commentary : Work is ongoing to answer pertinent clinical questions in prostate cancer management including which patients should undergo biopsy, active surveillance, receive adjuvant therapy, and what systemic therapy is best in the first-line. Incorporation into novel biomarkers may allow for the incorporation of a 'personalized' approach to management. Further validation will be required and questions of cost must be considered before wide scale adoption of these biomarkers. Tumor heterogeneity may impose a ceiling on the prognostic ability of biomarkers using currently available techniques.