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Title:
Inferring tumour purity and stromal and immune cell admixture from expression data | Nature Communications
Description:
Infiltrating stromal and immune cells form the major fraction of normal cells in tumour tissue and not only perturb the tumour signal in molecular studies but also have an important role in cancer biology. Here we describe ‘Estimation of STromal and Immune cells in MAlignant Tumours using Expression data’ (ESTIMATE)—a method that uses gene expression signatures to infer the fraction of stromal and immune cells in tumour samples. ESTIMATE scores correlate with DNA copy number-based tumour purity across samples from 11 different tumour types, profiled on Agilent, Affymetrix platforms or based on RNA sequencing and available through The Cancer Genome Atlas. The prediction accuracy is further corroborated using 3,809 transcriptional profiles available elsewhere in the public domain. The ESTIMATE method allows consideration of tumour-associated normal cells in genomic and transcriptomic studies. An R-library is available on https://sourceforge.net/projects/estimateproject/ . Tumour biopsies contain contaminating normal cells and these can influence the analysis of tumour samples. In this study, Yoshihara et al.develop an algorithm based on gene expression profiles from The Cancer Genome Atlas to estimate the number of contaminating normal cells in tumour samples.
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tumour, data, immune, stromal, cancer, cell, cells, article, expression, purity, estimate, scores, google, scholar, samples, gene, cas, genes, types, ovarian, tcga, supplementary, fig, nature, high, analysis, sets, score, signature, set, infiltrating, normal, fraction, carcinoma, tissue, affymetrix, based, breast, lung, mutation, human, number, tumours, signatures, copy, microarray, algorithm, absolute, genome, sample,
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headline:Inferring tumour purity and stromal and immune cell admixture from expression data
description:Infiltrating stromal and immune cells form the major fraction of normal cells in tumour tissue and not only perturb the tumour signal in molecular studies but also have an important role in cancer biology. Here we describe âEstimation of STromal and Immune cells in MAlignant Tumours using Expression dataâ (ESTIMATE)âa method that uses gene expression signatures to infer the fraction of stromal and immune cells in tumour samples. ESTIMATE scores correlate with DNA copy number-based tumour purity across samples from 11 different tumour types, profiled on Agilent, Affymetrix platforms or based on RNA sequencing and available through The Cancer Genome Atlas. The prediction accuracy is further corroborated using 3,809 transcriptional profiles available elsewhere in the public domain. The ESTIMATE method allows consideration of tumour-associated normal cells in genomic and transcriptomic studies. An R-library is available on
https://sourceforge.net/projects/estimateproject/
. Tumour biopsies contain contaminating normal cells and these can influence the analysis of tumour samples. In this study, Yoshihara et al.develop an algorithm based on gene expression profiles from The Cancer Genome Atlas to estimate the number of contaminating normal cells in tumour samples.
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name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Centre, Houston, USA
name:Catedra de Bioinformatica, Tecnologico de Monterrey, Campus Monterrey, Monterrey, Mexico
name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Centre, Houston, USA
name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Centre, Houston, USA
name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Centre, Houston, USA
name:Catedra de Bioinformatica, Tecnologico de Monterrey, Campus Monterrey, Monterrey, Mexico
name:USC Epigenome Centre, University of Southern California,
name:Los Angeles, USA
name:USC Epigenome Centre, University of Southern California,
name:Los Angeles, USA
name:Department of Surgery, Gynecology Service, Memorial Sloan-Kettering Cancer Centre, New York, USA
name:The Broad Institute of Harvard and MIT, Cambridge, USA
name:The Broad Institute of Harvard and MIT, Cambridge, USA
name:Department of Systems Biology, The University of Texas MD Anderson Cancer Centre, Houston, USA
name:Department of Systems Biology, The University of Texas MD Anderson Cancer Centre, Houston, USA
name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Centre, Houston, USA
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