Abstract 5572: Tracking the functional analysis of cancer risk variants

Abstract

Abstract Genome-wide association studies (GWAS) have identified thousands of alleles associated with cancer risk, but understanding the functional effects of these variants has proceeded more slowly. In addition, although catalogs of variants exist, tracking progress to determine variant function is challenging. We conducted a literature search and review to assess the trajectory of functional characterization of GWAS results and describe the types of analysis conducted and tools and databases used. We used the PubTator Web-based tool, which uses advanced text-mining techniques to accelerate manual literature curation, to search the literature for articles describing functional annotation of cancer GWAS hits. We generated a list of 646 unique SNPs from the Cancer Genomics and Epidemiology Navigator (CGEN) and imported the list to PubTator. We identified a total of 292 articles that included both variant discovery by GWAS and functional analysis, and reviewed the articles for information including cancer type, variant functional class (e.g., intron, exon, intergenic, etc.), and type of functional analysis conducted. These articles included 40 different cancer types or subtypes. The majority of cancer risk variants were intronic or intergenic, with only a small number located in coding regions. Most of the functional analyses were focused on the potential modification/disruption of regulatory processes by the risk allele (e.g., alteration of transcription factor binding sites, putative expressed quantitative trait loci), in line with current hypotheses regarding cancer risk variant function. Most studies also described effects of variants at the molecular, or cellular, rather than organismal level. We also reviewed the literature pertaining to variants identified for three cancers with possible pleiotropy - ovarian, breast, and prostate - to understand the trajectory of functional analyses beyond the initial discovery of the variants. We describe our use of the PubTator tool and provide a literature-based overview of progress in understanding the function of cancer risk variants identified via GWAS. Citation Format: Sharna Tingle, Danielle Carrick, Sheri Schully, Mindy Clyne, Stefanie A. Nelson. Tracking the functional analysis of cancer risk variants. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 5572. doi:10.1158/1538-7445.AM2015-5572