Genetic polymorphisms as predictive and prognostic biomarkers in gynecological cancers: a systematic review.

Ivan Diaz-Padilla, Eitan Amir, Sharon Marsh, Geoffrey Liu, Helen Mackay

Division of Medical Oncology, Princess Margaret Hospital, University of Toronto, Ontario, Canada. ivan.padilla@uhn.on.ca

Gynecologic oncology 2012 Feb

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Numerous studies have explored the potential role of genetic polymorphisms as predictive or prognostic biomarkers in gynecologic malignancies. A systematic review for all eligible polymorphisms has not yet been reported. The aim of this study was to summarize the current status of the field and provide direction for future research. We searched literature databases (MEDLINE, EMBASE, Cochrane) from 2006 to April 2011 to identify studies evaluating the association between gene polymorphisms and clinical outcome in ovarian, endometrial, cervical, or vulvar cancer. The main outcome measures were overall survival (OS) and progression-free survival (PFS). Studies reporting relationships between polymorphisms and toxicity were also included. Sixty two studies met the inclusion criteria. The median sample size was 140. Most of the included studies (n=50, 81%) were conducted in ovarian cancer patients. Almost a third assessed potential predictive associations between gene polymorphism and outcome in ovarian cancer. The most commonly evaluated genes were ERCC1, VEGF, ABCB1 (MDR), and GSTP1. Most studies (n=44, 71%) were observational case-series. Only four studies (6%) included a validation arm and patient population ethnicity was explicitly stated only in 27% of included studies. No consistent association between any gene polymorphism and clinical outcome in gynecological cancers has been found across studies. There is incomplete adherence to the REMARK guidelines and inadequate methodology reporting in most studies. Moving forward, analysis of large trial-based clinical samples; adherence to the highest methodological standards, and focus on validation analyses are necessary to identify clinically useful pharmacogenomic biomarkers of outcome. Copyright © 2011 Elsevier Inc. All rights reserved.

Citation

Ivan Diaz-Padilla, Eitan Amir, Sharon Marsh, Geoffrey Liu, Helen Mackay. Genetic polymorphisms as predictive and prognostic biomarkers in gynecological cancers: a systematic review. Gynecologic oncology. 2012 Feb;124(2):354-65