Nongenic cancer-risk SNPs affect oncogenes, tumour-suppressor genes, and immune function

Br J Cancer. 2020 Feb;122(4):569-577. doi: 10.1038/s41416-019-0614-3. Epub 2019 Dec 6.

Abstract

Background: Genome-wide association studies (GWASes) have identified many noncoding germline single-nucleotide polymorphisms (SNPs) that are associated with an increased risk of developing cancer. However, how these SNPs affect cancer risk is still largely unknown.

Methods: We used a systems biology approach to analyse the regulatory role of cancer-risk SNPs in thirteen tissues. By using data from the Genotype-Tissue Expression (GTEx) project, we performed an expression quantitative trait locus (eQTL) analysis. We represented both significant cis- and trans-eQTLs as edges in tissue-specific eQTL bipartite networks.

Results: Each tissue-specific eQTL network is organised into communities that group sets of SNPs and functionally related genes. When mapping cancer-risk SNPs to these networks, we find that in each tissue, these SNPs are significantly overrepresented in communities enriched for immune response processes, as well as tissue-specific functions. Moreover, cancer-risk SNPs are more likely to be 'cores' of their communities, influencing the expression of many genes within the same biological processes. Finally, cancer-risk SNPs preferentially target oncogenes and tumour-suppressor genes, suggesting that they may alter the expression of these key cancer genes.

Conclusions: This approach provides a new way of understanding genetic effects on cancer risk and provides a biological context for interpreting the results of GWAS cancer studies.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Genes, Tumor Suppressor*
  • Genetic Predisposition to Disease / genetics*
  • Humans
  • Neoplasms / genetics*
  • Neoplasms / immunology*
  • Oncogenes / genetics*
  • Polymorphism, Single Nucleotide*
  • Quantitative Trait Loci