Abstract 2738: Insights into survival from ovarian cancer revealed by gene set analysis
Authors: Brooke L. Fridley, Gregory D. Jenkins, Ya-Yu Tsai, David Fenstermacher, Joellen Schildkraut, Rebecca Sutphen, Y. Ann Chen, Edwin Iversen, Robert A. Vierkant, Julie M. Cunningham, Zhihua Chen, Thomas A. Sellers, Ellen L. Goode
Journal: Cancer Research (2011)

Abstract Epithelial ovarian cancer (EOC) is the 6th most commonly diagnosed cancer among women in the world, accounting for 4% of all female cancers. On a worldwide basis, an estimated 204,000 new cases are diagnosed and 125,000 women die of EOC annually, with 5-year survival rate at 45%. Metastasis and its complications are the usual cause of EOC-related deaths. Thus, factors related to tumor aggressiveness, response to therapy, and the underlying health state of the patient often predict survival. Candidate gene and genome-wide association studies (GWAS) for survival from EOC have discovered only a few the genetic variants, accounting for only a small proportion of the heritability. One explanation for the missing heritability is that the common analysis approach _ assessing the effect of each single nucleotide polymorphism (SNP) individually _ is not well suited to the detection of small effects of multiple SNPs. Gene set analysis (GSA) overcomes this limitation by assessing the overall evidence of association of a phenotype with all measured variation in a set of genes or pathway. Therefore, we conducted a GSA using data from an EOC GWAS, using the Illumina 610-quad SNP array, to determine novel gene sets (GSs) associated with overall survival (OS) from EOC (N cases = 1057, N deaths = 495). All subjects were non-Hispanic, non-Jewish Caucasians, with sample and SNP call rates &amp;gt;95%. Subjects with ambiguous gender, unresolved identical genotypes, and less than 80% European ancestry were also excluded. SNPs were mapped to genes within 20 kb, with genes then mapped to GSs defined by the following: KEGG, Gene Ontology (biological, cellular, molecular) and PharmGKB. GSA was completed in which the association of each gene with OS was assessed using a principal component gene-level test (adjusting for study site, age and population sub-structure based on the first eigenvector from EigenStrat), followed by the aggregation of the gene-level p-values using the Gamma method with a soft truncation threshold of 0.15. Empirical p-values were determined using permutation methods. Of the 2,573 GSs assessed, 30 GSs had a p-value &amp;lt; 0.01. The top GSs were related to: mismatch repair (p = 3.0E-4), platelet formation (p=0.001), leukocyte adhesive activation (p=0.002), antigen processing and presentation of endogenous antigens (p = 0.002) or peptide antigens (p = 0.002), platinum pathway (p = 0.003), aging and lifespan (p = 0.004, p = 0.007), immune system development (p = 0.004) and somatic diversification (p=0.007). These results illustrate the usefulness of GSA for the development of novel hypotheses that can be followed-up with additional clinical or functional studies. Moreover, application of GSA to survival from EOC allowed the detection of significant GSs (and the corresponding genes/SNPs within these GSs) that impact OS that were not detected by assessing each SNP individually, where the smallest p-value from single SNP analysis of the GWAS for OS was 1.3E-05. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 2738. doi:10.1158/1538-7445.AM2011-2738