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 language | English |
|---|---|
| Article number | 130 |
| Journal | Genome Biology |
| Volume | 19 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 11 Sept 2018 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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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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