Genetic variants as ovarian cancer first-line treatment hallmarks: A systematic review and meta-analysis

• Type: Another Publication in an International Scientific Journal
• Date: 2017

Authors

Assis, J (Author) Other; Pereira, C (Author) FMUP; Nogueira, A (Author) Other; Pereira, D (Author) Other; Carreira, R (Author) Other; Rui Medeiros (Author) ICBAS

Journal

Title: Cancer Treatment Reviews

Vol. 61

Pages: 35-52

ISSN: 0305-7372

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 5 Citations

Scopus - 15 Citations

Other information

Authenticus ID: P-00N-5XK

DOI: 10.1016/j.ctrv.2017.10.001

Abstract (EN): Background: The potential predictive value of genetic polymorphisms in ovarian cancer first-line treatment is inconsistently reported. We aimed to review ovarian cancer pharmacogenetic studies to update and summarize the available data and to provide directions for further research. Methods: A systematic review followed by a meta-analysis was conducted on cohort studies assessing the involvement of genetic polymorphisms in ovarian cancer first-line treatment response retrieved through a MEDLINE database search by November 2016. Studies were pooled and summary estimates and 95% confidence intervals (CI) were calculated using random or fixed-effects models as appropriate. Results: One hundred and forty-two studies gathering 106871 patients were included. Combined data suggested that GSTM1-null genotype patients have a lower risk of death compared to GSTM1-wt carriers, specifically in advanced stages (hazard ratio (HR), 0.68; 95% CI, 0.48-0.97) and when submitted to platinum-based chemotherapy (aHR, 0.61; 95% CI, 0.39-0.94). ERCC1 rs11615 and rs3212886 might have also a significant impact in treatment outcome (aHR, 0.67; 95% CI, 0.51-0.89; aHR, 1.28; 95% CI, 1.01-1.63, respectively). Moreover, ERCC2 rs13181 and rs1799793 showed a distinct ethnic behavior (Asians: aHR, 1.41; 95% CI, 0.80-2.49; aHR, 1.07; 95% CI, 0.62-1.86; Caucasians: aHR, 0.10; 95% CI, 0.01-0.96; aHR, 0.18; 95% Cl, 0.05-0.68, respectively). Conclusion(s): The definition of integrative predictive models should encompass genetic information, especially regarding GSTM1 homozygous deletion. Justifying additional pharmacogenetic investigation are variants in ERCC1 and ERCC2, which highlight the DNA Repair ability to ovarian cancer prognosis. Further knowledge could aid to understand platinum-treatment failure and to tailor chemotherapy strategies.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 18