To date, genome-wide association studies (GWAS) have reported common variants in over 50 loci

with weak to moderate effects on CRC risk. These genetic factors in aggregate explain only a small

fraction of familial risk of CRC. To aid in the discovery of novel CRC loci, we integrated large

transcriptome data, including those generated in the Genotype-Tissue Expression (GTEx) Project in

genetic association analyses of CRC. The computational method, PrediXcan, was used to predict

transcript levels in relevant tissues and perform gene-level association tests with CRC. Prediction

models were developed using whole blood transcriptomes (n=922) from the depression genes and

networks (DGN), as well as colon transcriptomes (transverse n=169 and sigmoid n=124) from

GTEx datasets, along with high-density genotyping data from the same subjects. Genetically

determined expression levels were tested for association with CRC in 12,186 cases and 14,718

controls from GECCO-CCFR and suggestive associations (false discovery rate = 0.2) were evaluated

in 7,481 cases and 17,796 controls from the Asia Colorectal Cancer Consortium (ACCC) and 22,974

cases and 14,392 controls from the Colorectal Transdisciplinary (CORECT) study. We attempted to

replicate novel associations for eight genes and found statistically significant associations with

CXCR1 (OR=1.21 (1.10-1.33), p-value=7.8x10-5) and CXCR2 (OR=1.24 (1.11-1.38), p-value=9.9x10-

5). We also recovered previous associations at six known GWAS loci, thereby providing additional

support for putative target genes. CXCR1 and CXCR2 are therapeutic targets for the anticancer agent

Reparixin, which is currently being investigated in a stage II clinical trial for triple negative breast

cancer. As such, these findings provide preliminary support for new molecular targets that could

potentially repurpose a putative cancer therapeutic. These findings highlight the utility integrating

transcriptome data for novel discovery and biological insight of risk loci.

Citation Format: Stephanie A. Bien, Xingyi Guo, Yu-Ru Su, Tabitha A. Harrison, Conghui Qu, Yingchang Lu, Jiron Long, Sai Chen, Andrew T. Chan, David V. Conti, Hyun M. Kang, Michael Hoffmeister, Thomas J. Hudson, Mark A. Jenkins, Loic Le Marchand, Polly A. Newcomb, Martha L. Slattery, Emily White, Goncalo R. Abeçasis, Stephen B. Gruber, Deborah A. Nickerson, Stephanie L. Schmit, Graham Casey, Li Hsu, Wei Zheng, Ulrike Peters, GECCO-CCFR-AAAC-CORECT. Genetic predictors of gene expression associated with risk of colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1300. doi:10.1158/1538-7445.AM2017-1300