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

doi:10.1186/s13059-018-1507-0

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

Genome Biol. 2018 Sep 11;19(1):130. doi: 10.1186/s13059-018-1507-0.

Authors

Paul Geeleher^{1

2}, Aritro Nath^{2

3}, Fan Wang^{2

4}, Zhenyu Zhang⁵, Alvaro N Barbeira¹, Jessica Fessler⁶, Robert L Grossman⁵, Cathal Seoighe⁷, R Stephanie Huang^{8

9

10}

Affiliations

¹ Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA.
² Section of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, IL, USA.
³ Department of Experimental and Clinical Pharmacology, University of Minnesota, Minneapolis, MN, USA.
⁴ Ben May Department for Cancer Research, University of Chicago, Chicago, IL, USA.
⁵ Center for Data Intensive Science, University of Chicago, Chicago, IL, USA.
⁶ Department of Pathology, University of Chicago, Chicago, IL, USA.
⁷ School of Mathematics, Statistics and Applied Mathematics, National University of Ireland, Galway, Ireland.
⁸ Section of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, IL, USA. rshuang@umn.edu.
⁹ Department of Experimental and Clinical Pharmacology, University of Minnesota, Minneapolis, MN, USA. rshuang@umn.edu.
¹⁰ Department of Experimental and Clinical Pharmacology, College of Pharmacy, Room 5-130 WDH, 1332A, 308 Harvard St SE, Minneapolis, MN, 55455, USA. rshuang@umn.edu.

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.

Keywords: Cancer; Deconvolution; Expression quantitative trait locus (eQTL); Gene regulation; Genome-wide association study (GWAS).

Publication types

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

MeSH terms

Breast Neoplasms / genetics
Breast Neoplasms / metabolism
Carcinogenesis / genetics
Computer Simulation
Female
Fibroblasts / metabolism
Gene Expression*
Genetic Variation
Genome-Wide Association Study
Genotype
Humans
Models, Statistical*
Neoplasms / genetics*
Neoplasms / metabolism
Quantitative Trait Loci*
Tumor Microenvironment

Abstract

Publication types

MeSH terms

Grants and funding