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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
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 interact...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6131897/ https://www.ncbi.nlm.nih.gov/pubmed/30205839 http://dx.doi.org/10.1186/s13059-018-1507-0 |
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author | Geeleher, Paul Nath, Aritro Wang, Fan Zhang, Zhenyu Barbeira, Alvaro N. Fessler, Jessica Grossman, Robert L. Seoighe, Cathal Stephanie Huang, R. |
author_facet | Geeleher, Paul Nath, Aritro Wang, Fan Zhang, Zhenyu Barbeira, Alvaro N. Fessler, Jessica Grossman, Robert L. Seoighe, Cathal Stephanie Huang, R. |
author_sort | Geeleher, Paul |
collection | PubMed |
description | 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-018-1507-0) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6131897 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61318972018-09-13 Cancer expression quantitative trait loci (eQTLs) can be determined from heterogeneous tumor gene expression data by modeling variation in tumor purity Geeleher, Paul Nath, Aritro Wang, Fan Zhang, Zhenyu Barbeira, Alvaro N. Fessler, Jessica Grossman, Robert L. Seoighe, Cathal Stephanie Huang, R. Genome Biol Method 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-018-1507-0) contains supplementary material, which is available to authorized users. BioMed Central 2018-09-11 /pmc/articles/PMC6131897/ /pubmed/30205839 http://dx.doi.org/10.1186/s13059-018-1507-0 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Method Geeleher, Paul Nath, Aritro Wang, Fan Zhang, Zhenyu Barbeira, Alvaro N. Fessler, Jessica Grossman, Robert L. Seoighe, Cathal Stephanie Huang, R. Cancer expression quantitative trait loci (eQTLs) can be determined from heterogeneous tumor gene expression data by modeling variation in tumor purity |
title | Cancer expression quantitative trait loci (eQTLs) can be determined from heterogeneous tumor gene expression data by modeling variation in tumor purity |
title_full | Cancer expression quantitative trait loci (eQTLs) can be determined from heterogeneous tumor gene expression data by modeling variation in tumor purity |
title_fullStr | Cancer expression quantitative trait loci (eQTLs) can be determined from heterogeneous tumor gene expression data by modeling variation in tumor purity |
title_full_unstemmed | Cancer expression quantitative trait loci (eQTLs) can be determined from heterogeneous tumor gene expression data by modeling variation in tumor purity |
title_short | Cancer expression quantitative trait loci (eQTLs) can be determined from heterogeneous tumor gene expression data by modeling variation in tumor purity |
title_sort | cancer expression quantitative trait loci (eqtls) can be determined from heterogeneous tumor gene expression data by modeling variation in tumor purity |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6131897/ https://www.ncbi.nlm.nih.gov/pubmed/30205839 http://dx.doi.org/10.1186/s13059-018-1507-0 |
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