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Cancer expression quantitative trait loci (eQTLs) can be determined from heterogeneous tumor gene expression data by modeling variation in tumor purity

  • Paul Geeleher
  • , Aritro Nath
  • , Fan Wang
  • , Zhenyu Zhang
  • , Alvaro N. Barbeira
  • , Jessica Fessler
  • , Robert L. Grossman
  • , Cathal Seoighe
  • , R. Stephanie Huang
  • University of Chicago
  • University of Minnesota Twin Cities
  • University of Chicago
  • College of Pharmacy

Research output: Contribution to a Journal (Peer & Non Peer)Articlepeer-review

26 Citations (Scopus)

Abstract

Expression quantitative trait loci (eQTLs) identified using tumor gene expression data could affect gene expression in cancer cells, tumor-associated normal cells, or both. Here, we have demonstrated a method to identify eQTLs affecting expression in cancer cells by modeling the statistical interaction between genotype and tumor purity. Only one third of breast cancer risk variants, identified as eQTLs from a conventional analysis, could be confidently attributed to cancer cells. The remaining variants could affect cells of the tumor microenvironment, such as immune cells and fibroblasts. Deconvolution of tumor eQTLs will help determine how inherited polymorphisms influence cancer risk, development, and treatment response.

Original languageEnglish
Article number130
JournalGenome Biology
Volume19
Issue number1
DOIs
Publication statusPublished - 11 Sept 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Cancer
  • Deconvolution
  • Expression quantitative trait locus (eQTL)
  • Gene regulation
  • Genome-wide association study (GWAS)

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