Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data
- University of Lausanne, Switzerland
- Lausanne University Hospital, Switzerland
Abstract
Immune cells infiltrating tumors can have important impact on tumor progression and response to therapy. We present an efficient algorithm to simultaneously estimate the fraction of cancer and immune cell types from bulk tumor gene expression data. Our method integrates novel gene expression profiles from each major non-malignant cell type found in tumors, renormalization based on cell-type specific mRNA content, and the ability to consider uncharacterized and possibly highly variable cell types. Feasibility is demonstrated by validation with flow cytometry, immunohistochemistry and single-cell RNA-Seq analyses of human melanoma and colorectal tumor specimens. Altogether, our work not only improves accuracy but also broadens the scope of absolute cell fraction predictions from tumor gene expression data, and provides a unique novel experimental benchmark for immunogenomics analyses in cancer research.
Data availability
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Simultaneous enumeration of cancer and immune cell types from tumor gene expression dataPublicly available at the NCBI Gene Expression Omnibus (accession no: GSE93722).
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Bioinformatics Approach to 2010-2011 TIV Influenza A/H1N1 Vaccine Immune ProfilingAvailable at ImmPort (accession no: SDY67).
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A Cell-based Systems Biology Assessment of Human Blood to Monitor Immune Responses After Influenza VaccinationPublicly available at the NCBI Gene Expression Omnibus (accession no: GSE64655).
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Next generation sequencing of human immune cell subsets across diseasesPublicly available at the NCBI Gene Expression Omnibus (accession no: GSE60424).
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RNA-Seq analysis of human adult peripheral blood populationsPublicly available at the NCBI Gene Expression Omnibus (accession no: GSE51984).
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Gene expression Classification of Colon Cancer defines six molecular subtypes with distinct clinical, molecular and survival characteristics [Expression]Publicly available at the NCBI Gene Expression Omnibus (accession no: GSE39582).
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Single cell RNA-seq analysis of melanomaPublicly available at the NCBI Gene Expression Omnibus (accession no: GSE72056).
Article and author information
Author details
Funding
Center for Advanced Modelling Science
- Julien Racle
- David Gfeller
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Project grant 31003A_173156)
- Julien Racle
- David Gfeller
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Alfonso Valencia, Barcelona Supercomputing Center - BSC, Spain
Ethics
Human subjects: Patients involved in this study agreed to donate metastatic tissues upon informed consent, based on dedicated clinical investigation protocols established according to the relevant regulatory standards. The protocols were approved by the local IRB, i.e. the Commission cantonale d'éthique de la recherche sur l'être humain du Canton de Vaud.
Version history
- Received: March 2, 2017
- Accepted: November 10, 2017
- Accepted Manuscript published: November 13, 2017 (version 1)
- Version of Record published: December 6, 2017 (version 2)
Copyright
© 2017, Racle et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data
eLife 6:e26476.
https://doi.org/10.7554/eLife.26476
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