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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.
Geeleher, Paul; Nath, Aritro; Wang, Fan; Zhang, Zhenyu; Barbeira, Alvaro N; Fessler, Jessica; Grossman, Robert L; Seoighe, Cathal; Stephanie Huang, R.
Afiliação
  • Geeleher P; Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA.
  • Nath A; Section of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, IL, USA.
  • Wang F; Section of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, IL, USA.
  • Zhang Z; Department of Experimental and Clinical Pharmacology, University of Minnesota, Minneapolis, MN, USA.
  • Barbeira AN; Section of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, IL, USA.
  • Fessler J; Ben May Department for Cancer Research, University of Chicago, Chicago, IL, USA.
  • Grossman RL; Center for Data Intensive Science, University of Chicago, Chicago, IL, USA.
  • Seoighe C; Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA.
  • Stephanie Huang R; Department of Pathology, University of Chicago, Chicago, IL, USA.
Genome Biol ; 19(1): 130, 2018 09 11.
Article em En | MEDLINE | ID: mdl-30205839
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Expressão Gênica / Modelos Estatísticos / Locos de Características Quantitativas / Neoplasias Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Female / Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Expressão Gênica / Modelos Estatísticos / Locos de Características Quantitativas / Neoplasias Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Female / Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article