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

Author

Listed:
  • Kosuke Yoshihara

    (The University of Texas MD Anderson Cancer Centre
    Niigata University Graduate School of Medical and Dental Sciences)

  • Maria Shahmoradgoli

    (The University of Texas MD Anderson Cancer Centre)

  • Emmanuel Martínez

    (The University of Texas MD Anderson Cancer Centre
    Catedra de Bioinformatica, Tecnologico de Monterrey, Campus Monterrey)

  • Rahulsimham Vegesna

    (The University of Texas MD Anderson Cancer Centre)

  • Hoon Kim

    (The University of Texas MD Anderson Cancer Centre)

  • Wandaliz Torres-Garcia

    (The University of Texas MD Anderson Cancer Centre)

  • Victor Treviño

    (Catedra de Bioinformatica, Tecnologico de Monterrey, Campus Monterrey)

  • Hui Shen

    (USC Epigenome Centre, University of Southern California
    Los Angeles)

  • Peter W. Laird

    (USC Epigenome Centre, University of Southern California
    Los Angeles)

  • Douglas A. Levine

    (Gynecology Service, Memorial Sloan-Kettering Cancer Centre)

  • Scott L. Carter

    (The Broad Institute of Harvard and MIT)

  • Gad Getz

    (The Broad Institute of Harvard and MIT)

  • Katherine Stemke-Hale

    (The University of Texas MD Anderson Cancer Centre)

  • Gordon B. Mills

    (The University of Texas MD Anderson Cancer Centre)

  • Roel G.W. Verhaak

    (The University of Texas MD Anderson Cancer Centre)

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/ .

Suggested Citation

  • 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 , 2013. "Inferring tumour purity and stromal and immune cell admixture from expression data," Nature Communications, Nature, vol. 4(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:4:y:2013:i:1:d:10.1038_ncomms3612
    DOI: 10.1038/ncomms3612
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