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Candidate Cancer Genes Identified From GWAS Risk SNPs, Expression Clues

NEW YORK – A team from the US and Spain used an integrative strategy to dig into potential regulatory relationships between germline risk variants and genes that may be prone to mutation in half a dozen cancer types.

By bringing expression profiles together with almost 300 cancer-related variants identified through genome-wide association studies, the researchers searched for expression quantitative trait loci related to melanoma or lung, colorectal, ovarian, prostate, and pancreatic cancers. The findings, appearing online this week in the American Journal of Human Genetics, led to eQTLs influencing the expression of 270 genes with possible cancer ties — a collection that they investigated further with functional genomic analyses.

"Together, these findings provide further insight into our understanding of how genetic risk variants might contribute to carcinogenesis through the regulation of susceptibility genes that are related to the biogenesis of somatic mutations," senior and corresponding author Xingyi Guo, an epidemiology researcher at Vanderbilt University School of Medicine, and his co-authors wrote.

At least some proposed cancer susceptibility genes have been uncovered through fine-mapping and eQTL analyses of cancer-associated SNPs identified by GWAS, the team noted, suggesting that still other candidate cancer genes might be uncovered using additional risk SNPs or cancer GWAS clues.

The authors reasoned that "the systematic characterization of previously reported index SNPs and the exploration of candidate target genes with multiple transcriptome datasets, such as The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) Project, might provide further understanding of the biological mechanisms that contribute to cancer development."

For their analyses, the investigators started with 294 SNPs uncovered in prior GWAS on individuals of European ancestry with lung squamous cell carcinoma, lung adenocarcinoma, colorectal cancer, ovarian cancer, prostate cancer, pancreatic cancer, or melanoma.

When the team considered these proposed risk variants in the context of gene expression data in TCGA, GTEx, and other databases, it identified apparent cis-QTLs near 270 candidate genes, which were analyzed in combination with 101 genes proposed from an earlier breast cancer eQTL analysis.

A series of follow-up functional analyses, which incorporated transcription factor chromatin immunoprecipitation sequence data, chromatin interaction clues, and other epigenetic insights, supported the regulatory role for variants near 180 of the genes. Some of those candidate genes were specific to one cancer type, the researchers noted, while 24 genes appeared to span two or more cancer types. 

The team noted that dozens of the potential target genes appeared to coincide with one or more mutational signatures and/or tumor mutational burden in the cancer types considered. Even so, the authors cautioned that "the biological mechanisms of how these cancer-susceptibility genes might affect mutational signatures in different cancer types remains unclear."