The role of treatment modality on the utility of predictive tissue biomarkers in clinical prostate cancer: A systematic review - Abstract

BACKGROUND: Tissue biomarkers could pivotally improve clinical outcome prediction following prostate cancer therapy.

Clinically, prostate cancer is managed by diverse treatment modalities whose individual influence on a biomarker's predictive ability is not well understood and poorly investigated in the literature.

OBJECTIVE: We conducted a systematic review to assess the predictive value of biomarkers in different treatment contexts in prostate cancer.

STUDY METHODOLOGY: A literature search was performed using the MeSH headings "prostate neoplasms" and "biological markers". Rigorous selection criteria identified studies correlating expression with clinical outcomes from primary androgen deprivation therapy (ADT), radical prostatectomy and radiotherapy (± neoadjuvant ADT).

STUDY RESULTS: Of 10,668 studies identified, 481 papers matched initial inclusion criteria. Following rescreening, 384 studies identified 236 individual tissue biomarkers, of which 29 were predictive on multivariate analysis in at least 2 independent cohorts. The majority were only tested in surgical cohorts. Only 8 predictive biomarkers were tested across all 3 treatments with Ki67 identified as universal predictive marker. p16 showed potential for treatment stratification between surgery and radiotherapy but needs further validation in independent studies.

CONCLUSIONS: Despite years of research, very few tissue biomarkers retain predictive value in independent validation across therapy context. Currently, none have conclusive ability to help treatment selection. Future biomarker research should consider the therapy context and use uniform methodology and evaluation criteria.

Written by:
Kachroo N, Gnanapragasam VJ.   Are you the author?
Translational Prostate Cancer Group, Hutchison MRC Research Centre, University of Cambridge, Hills Road, Cambridge, CB2 0XZ, UK.

Reference: J Cancer Res Clin Oncol. 2012 Nov 28. Epub ahead of print.
doi: 10.1007/s00432-012-1351-7


PubMed Abstract
PMID: 23187933

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