Abstract 1220: Integrative genomic analysis discovers the causative regulatory mechanisms of a breast cancer-associated genetic variant

Genome-wide association studies (GWAS) have identified genetic variants that may significantly modulate breast cancer susceptibility. However, the precise molecular mechanisms behind these associations remain largely unknown; often, it is not even clear whether the GWAS variants are functional themselves or just genetically linked to other functional variants. We here provide an integrated method for identifying functional regulatory variants associated with breast cancer and their target genes by combining the analyses of expression quantitative trait loci (eQTL), a modified version of allele-specific expression (ASE) systematically utilizing haplotype information, transcription factor (TF) binding preference, and epigenetic information. Application of our method to the breast cancer susceptibility region in 5p12 demonstrates that the GWAS risk allele rs4415084-T is correlated with higher expression levels of the protein-coding gene MRPS30 and lncRNA RP11-53O19.1. We propose that an intergenic SNP, in linkage disequilibrium (LD) with the GWAS SNP rs4415084, is the predicted functional SNP. We provide multiple levels of evidence that the risk allele of the predicted functional SNP, in phase with the GWAS risk allele rs4415084-T, creates a GATA3 binding motif within a regulatory element, resulting in differential GATA3 binding and chromatin accessibility, which thereby promote the transcription of MRPS30 and RP11-53O19.1. MRPS30 encodes a member of the mitochondrial ribosomal proteins, implicating the risk SNP9s role in modulating mitochondrial activities in breast cancer. Our computational framework can be extended to facilitate the rapid functional characterization of other genetic variants modulating cancer susceptibility and provides an effective way of integrating GWAS results with high-throughput genomic and epigenomic data. Citation Format: Yi Zhang, Mohith Manjunath, Shilu Zhang, Deborah Chasman, Sushmita Roy, Jun S. Song. Integrative genomic analysis discovers the causative regulatory mechanisms of a breast cancer-associated genetic variant [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1220.