NEW YORK – Using a combination of genetic, transcriptomic, and proteomic data, a team led by investigators at the National Institutes of Health has unearthed genes with new and known ties to renal cell carcinoma (RCC), a type of kidney cancer.
The study, published in the American Journal of Human Genetics on Monday, "represents an important advance in prioritizing candidate genes and molecular targets associated with RCC risk for further laboratory investigation," according to National Cancer Institute researchers Diptavo Dutta and Mark Purdue, the study's co-corresponding authors, and their coauthors.
For their study, researchers at the National Cancer Institute, the University of Pennsylvania, and the University of Southern California searched for RCC genetic contributors by combining transcriptome-wide association, proteome-wide association, and genome-wide association studies.
"A key challenge to post-GWAS functional investigation is to identify plausible candidate genes for investigation to elucidate their biological underpinnings," the authors explained, noting that "integration of molecular profiling data (e.g., transcriptomics and proteomics) with GWAS results has emerged as an effective approach to identifying and prioritizing potential candidate genes and intermediate molecular phenotypes for various cancers and other diseases."
Starting with data from a GWAS meta-analysis that included 29,020 individuals with RCC and 835,670 unaffected controls, the investigators put together and trained prediction models using kidney transcriptomic data for RCC, the kidney cortex, kidney tubules, and renal papillary cell carcinoma samples from the Cancer Genome Atlas and the Genotype-Tissue Expression (GTEx) project.
In the process, they highlighted 38 gene associations including a dozen involving genes beyond loci identified by GWAS. Another 23 genes turned up by bringing in TWAS data across 48 GTEx tissue types.
Based on subsequent analyses that included published ATAC-seq and chromatin immunoprecipitation sequencing data, the team saw further ties between the kidney cancer-associated genes and gene regulatory features such as cis-regulatory binding sites and transcription factor binding sites, particularly when it came to genes flagged in the TWAS portion of the study.
"TWAS-identified genes were enriched for active enhancer and promoter regions in RCC tumors and hypoxia-inducible factor binding sites in relevant cell lines," the authors reported, adding that the work "provides additional evidence of the involvement of the [RCC-related TWAS] gene expression in RCC etiology."
The team also tracked down shared associations for the clear-cell RCC (ccRCC) and papillary RCC (papRCC) histological types by analyzing kidney-centric TWAS data.
Using published proteomic data spanning thousands of proteins in blood plasma samples from thousands of participants from the INTERVAL and ARIC studies, meanwhile, the team picked up associations involving 13 proteins that coincided with genetic loci identified by GWAS.
Finally, the researchers relied on an imputation model to explore gene expression-based relationships between RCC and several other cancer types including breast, ovarian, prostate, and bladder cancer.
For example, the authors saw signs that RCC "shares significant expression-mediated genetic correlation with breast and prostate cancers, indicating that several RCC-associated genes might have potential pleiotropic effects and can implicate shared processes across multiple cancers."