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

Kosuke Yoshihara, Maria Shahmoradgoli, Emmanuel Martínez, Rahulsimham Vegesna, Hoon Kim, Wandaliz Torres-Garcia, Victor Treviño, Hui Shen, Peter W. Laird, Douglas A. Levine, Scott L. Carter, Gad Getz, Katherine Stemke-Hale, Gordon B. Mills, Roel G.W. Verhaak

Research output: Contribution to journalArticlepeer-review

4978 Scopus citations

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/.

Original languageEnglish (US)
Article number2612
JournalNature communications
Volume4
DOIs
StatePublished - 2013
Externally publishedYes

ASJC Scopus subject areas

  • General Chemistry
  • General Biochemistry, Genetics and Molecular Biology
  • General Physics and Astronomy

Fingerprint

Dive into the research topics of 'Inferring tumour purity and stromal and immune cell admixture from expression data'. Together they form a unique fingerprint.

Cite this