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American Association for Cancer Research, Clinical Cancer Research, 18(14), p. 5833-5839, 2008

DOI: 10.1158/1078-0432.ccr-08-0819

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The effects of common genetic variants in oncogenes on ovarian cancer survival

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Abstract Purpose: The 5-year survival rate for invasive epithelial ovarian cancer is <35%. It has been suggested that common, germline genetic variation may influence survival after cancer diagnoses, which might enable the prediction of response to treatment and survival in the clinical setting. The aim of this study was to evaluate associations between common germline genetic variants in the oncogenes BRAF, ERBB2, KRAS, NMI, and PIK3CA, and survival after a diagnosis of epithelial ovarian cancer. Experimental Design: We evaluated the association between 34 tagging single nucleotide polymorphisms and survival in 1,480 cases of invasive epithelial ovarian cancer cases from three different studies. Cox regression analysis, stratified by study, was used to estimate per rare allele hazard ratios (HR). Results: The minor allele rs6944385 in BRAF was significantly associated with poor survival [HR, 1.19; 95% confidence intervals (95% CI), 1.02-1.39; P = 0.024]. The association remained after adjusting for prognostic factors (adjusted HR, 1.20; 95 CI, 1.03-1.40; P = 0.018). A haplotype of BRAF was also associated with poor survival (HR, 1.24; 95% CI, 1.02-1.51; P = 0.029) and was more significant after adjustment (HR, 1.44; 95% CI, 1.15-1.81; P = 0.001). We also found evidence of an association between a KRAS haplotype and poor survival in serous subtype (HR, 1.69; 95% CI, 1.21-2.38; P = 0.002), but this was no longer significant after adjustment. Finally, when analyses were restricted to the serous histologic subtype, the rare allele rs10842513 in KRAS, was associated with poor survival (HR, 1.40; 95% CI, 1.10-1.78; P = 0.007). Conclusion: Common genetic variants in the BRAF and KRAS oncogenes may be important in the prediction of survival in patients with invasive epithelial ovarian cancer.