M9 - NCI GWAS in Renal Cell Carcinoma (RCC): Expansion of a Primary Scan

This page provides study documentation for consortium study M9. For description of the specimen results, see Specimen Results Description (open to public). Data sets of the specimen results are included in the existing WHI datasets located on the WHI Data on this site (sign in and a completed Data Distribution Agreement are required; see details on the Data site).
Investigator Names and Contact Information

Steve Channock, PhD, NCI


There is clear evidence that genetic factors influence susceptibility to RCC.  In most studies, having a first-degree relative affected with RCC has been associated with increased relative risk of this cancer (1-3).  Very high rates of RCC are observed among patients with Von-Hipel-Lindau (VHL) syndrome, a dominantly inherited multisystemic genetic disorder, with a cumulative risk greater than 70% observed by the age of 60 (4).  The VHL syndrome and other relevant genetic disorders (including hereditary papillary renal cell carcinoma, Birt Hogg Dubé disease, and hereditary leiomyomatosis renal cell cancer) account for a small proportion of overall RCC cases.  However, the majority of sporadic RCC tumors demonstrate VHL gene inactivation or broader dysregulation of the VHL/hypoxia-inducing factor/vascular endothelial growth factor pathway (5). Thus, it is plausible that genetic variation in VHL-related pathways could also influence risk of sporadic RCC.  Few studies have been carried out to investigate common, low-penetrant genetic susceptibility factors for RCC.  Until recently, the investigations conducted thus far have used a focused, candidate-gene approach, and have not yielded clear evidence suggestive of susceptibility loci.
A genome-wide association study (GWAS) of 317,000 single-nucleotide polymorphisms (SNPs) recently completed within a large Eastern European case-control study of renal cell carcinoma (RCC; 1,150 cases and 2,200 controls) is poised to advance our understanding of the contribution of genetic factors to the pathogenesis of this cancer.  However, the statistical power of this project to detect relatively weak genetic effects is limited.  In order to improve the project’s power to detect associations across a wide range of allele frequencies and magnitudes of effect, we are planning an expansion of this scan.  We are in the process of assembling a collection of RCC cases and controls from several studies (the PLCO, ATBC, ACS-CPSII and WHI cohorts and a large U.S. case-control study of RCC), with an expected sample size of at least 1,750 cases and 2,145 controls.  This sample will be analyzed using the Illumina® Human610-Quad BeadChip platform, which genotypes ~620,000 markers (including the 317,000 SNPs from the initial scan).  This proposed project will be a very important contribution to the area of kidney cancer genetics; we anticipate that SNPs highly likely to be markers for genetic variants related to RCC risk will emerge from this analysis and lead to further studies of gene-gene and gene-environment interactions with established RCC risk such as body mass index and smoking.  In order to accelerate the pace of discovery and characterization of genetic markers associated with RCC, the results of the analysis of the expanded GWAS will be made available to the research community. The genotyping data from will also be posted on a controlled-access web site, available to the biomedical research community.
1)    The primary aim of the GWAS is to identify genetic variants associated with RCC risk.  Such variants would be immediate and important candidates for further investigation though fine-mapping studies and clinical and laboratory-based investigations.  The inclusion of WHI samples to the expanded scan will be valuable for optimizing the statistical power of the project to detect weak associations with genetic markers.
2)    Using the best candidates from the combined scans, this project will establish a foundation for the investigation of gene-environment interactions with RCC risk factors such as body mass index, smoking and history of hypertension.  Inclusion of the WHI study, with prospective collection of questionnaire data and biological specimens, will be valuable for the evaluation of gene-environment interactions, and will enable evaluation of relationships with biomarkers of exposure and intermediate endpoints in future studies.
3)    The summary analyses of each SNP will be available on a publicly accessible data portal (identical to what is currently used for CGEMS) in order to accelerate the discovery and replication of genetic variants associated with the risk for RCC. The de-linked genotype results with limited covariates will be publicly accessible through a controlled-access registered website within months after completion and assessment of quality control analyses. Requesting investigators will require institutional verification for access to controlled data for research purposes only.
(1)   McLaughlin JK, Mandel JS, Blot WJ, Schuman LM, Mehl ES, Fraumeni JF, Jr. A population--based case--control study of renal cell carcinoma. J Natl Cancer Inst 1984;72(2):275-84.
(2)   Schlehofer B, Pommer W, Mellemgaard A, Stewart JH, McCredie M, Niwa Set al. International renal-cell-cancer study. VI. the role of medical and family history. Int J Cancer 1996;66(6):723-6.
(3)   Gago-Dominguez M, Yuan JM, Castelao JE, Ross RK, Yu MC. Family history and risk of renal cell carcinoma. Cancer Epidemiol Biomarkers Prev 2001;10(9):1001-4.
(4)   Maher ER. Inherited renal cell carcinoma. Br J Urol 1996;78(4):542-5.
(5)   Atkins MB, Ernstoff MS, Figlin RA, Flaherty KT, George DJ, Kaelin WG, Jr.et al. Innovations and challenges in renal cell carcinoma: summary statement from the Second Cambridge Conference. Clin Cancer Res 2007;13(2 Pt 2):667s-70s.