Department of Bioinformatics and Computational Biology

Publications:24113773

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Inferring tumour purity and stromal and immune cell admixture from expression data.

Nat Commun 4 2612
2013

Yoshihara K, Shahmoradgoli M, Martínez E, Vegesna R, Kim H, Torres-Garcia W, Treviño V, Shen H, Laird P, Levine D, Carter S, Getz G, Stemke-Hale K, Mills G, Verhaak R

[[institution::1] Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Centre, Houston, Texas 77030, USA [2] Department of Obstetrics and Gynecology, Niigata University Graduate School of Medical and Dental Sciences, Niigata 951-8510, Japan.]]

Abstract

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/.