Multilevel-analysis identify a cis-expression quantitative trait locus associated with risk of renal cell carcinoma
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Xiang Shu1,*, Mark P. Purdue2,*, Yuanqing Ye1, Christopher G. Wood3, Meng Chen1, Zhaoming Wang4, Demetrius Albanes2, Xia Pu1, Maosheng Huang1, Victoria L. Stevens5, W. Ryan Diver5, Susan M. Gapstur5, Jarmo Virtamo6, Wong-Ho Chow1, Nizar M. Tannir7, Colin P. Dinney3, Nathaniel Rothman2, Stephen J. Chanock2,*, Xifeng Wu1,*
1Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
2Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, USA
3Urology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
4Cancer Genomics Research Laboratory, SAIC-Frederick Inc., National Cancer Institute-Frederick, Frederick, Maryland, USA
5Epidemiology Research Program, American Cancer Society, Atlanta, Georgia, USA
6Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
7Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
*These authors have contributed equally to this work
Xifeng Wu, e-mail: [email protected]
Keywords: RCC, GWAS, GSEA, eQTL
Received: November 07, 2014 Accepted: December 21, 2014 Published: February 25, 2015
We conducted multilevel analyses to identify potential susceptibility loci for renal cell carcinoma (RCC), which may be overlooked in traditional genome-wide association studies (GWAS). A gene set enrichment analysis was performed utilizing a GWAS dataset comprised of 894 RCC cases and 1,516 controls using GenGen, SNP ratio test, and ALIGATOR. The antigen processing and presentation pathway was consistently significant (P = 0.001, = 0.004, and < 0.001, respectively). Versatile gene-based association study approach was applied to the top-ranked pathway and identified the driven genes. By comparing the expression of the genes in RCC tumor and adjacent normal tissues, we observed significant overexpression of HLA genes in tumor tissues, which was also supported by public databases. We sought to validate genetic variants in antigen processing and presentation pathway in an independent GWAS dataset comprised of 1,311 RCC cases and 3,424 control subjects from the National Cancer Institute; one SNP, rs1063355, was significant in both populations (Pmeta-analysis = 9.15 × 10−4, Pheterogeneity = 0.427). Strong correlation indicated that rs1063355 was a cis-expression quantitative trait loci which associated with HLA-DQB1 expression (Spearman’s rank r = −0.59, p = 5.61 × 10−6). The correlation was further validated using a public dataset. Our results highlighted the role of immune-related pathway and genes in the etiology of RCC.
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