| Summary: | Combinations of common germline low-moderate susceptibility alleles may be responsible for some of the 90% of ovarian cancer (OC) cases not explained by known risk genes. These alleles may also affect survival of OC patients. The effects of 34 tagging single nucleotide polymorphisms (tSNPs) from candidate oncogenes (BRAF, ERBB2, KRAS, NMI and PIK3CA) and 63 tSNPs from “functionally” relevant genes (AIFM2, AKTIP, AXIN2, CASP5, FILIP1L, RBBP8, RGC32, RUVBL1 and STAG3) on the risk and survival of OC sufferers were evaluated with ~1,800 cases and 3,045 controls. Associations were found between disease risk and NMI rs11683487 (P-dominant=0.004) and RUVBL1 rs13063604 (P-trend=0.0192). These associations were not independently validated with additional samples, however, they remained significant when the results from both stages of genotyping were combined (P<0.05). Global tests of association with OC risk were significant for BRAF, ERBB2, CASP5 and RUVBL1 (P-global<0.05). However, there was no evidence of an excess of significant associations from 340 SNPs investigated with the admixture maximum likelihood test (P-trend=0.068). BRAF, FILIP1L, KRAS, RBBP8 and RUVBL1 were also associated with the survival of all OC cases (P<0.05). When analysis was restricted to the 4 main histological subtypes of OC, additional associations were identified. Although these results are of particular interest, they were based on relatively small numbers of samples and have not been corrected for multiple testing, therefore they should be treated with caution. The results from the secondary objective of the project, to evaluate whole genome amplification (WGA) of DNA and SNP multiplex platforms, are also described. To conclude, associations were identified between candidate oncogenes and functionally relevant genes on the survival and susceptibility of ovarian cancer. The performance of WGA DNA on SNP multiplex genotyping platforms highlighted the importance of comparing WGA DNA with corresponding gDNA in order to ascertain quality of genotyping on the platform.
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