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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

Research output: Contribution to journalArticlepeer-review

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 (US)
Article number130
JournalGenome biology
Volume19
Issue number1
DOIs
StatePublished - Sep 11 2018

Bibliographical note

Publisher Copyright:
© 2018 The Author(s).

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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