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Computational Deconvolution of Tumor-Infiltrating Immune Components with Bulk Tumor Gene Expression Data

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Bioinformatics for Cancer Immunotherapy

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2120))

Abstract

Tumor-infiltrating immune cells play critical roles in immune-mediated tumor rejection and/or progression, and are key targets of immunotherapies. Estimation of different immune subsets becomes increasingly important with the decreased cost of high-throughput molecular profiling and the rapidly growing amount of cancer genomics data. Here, we present Tumor IMmune Estimation Resource (TIMER), an in silico deconvolution method for inference of tumor-infiltrating immune components. TIMER takes bulk tissue gene expression profiles measured with RNA-seq or microarray to evaluate the abundance of six immune cell types in the tumor microenvironment: B cell, CD4+ T cell, CD8+ T cell, neutrophil, macrophage, and dendritic cell. We further introduce its associated webserver for convenient, user-friendly analysis of tumor immune infiltrates across multiple cancer types.

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Author information

Authors and Affiliations

  1. Lyda Hill Department of Bioinformatics, Department of Immunology, UT Southwestern Medical Center, Dallas, TX, USA

    Bo Li, Taiwen Li, Jun S. Liu & X. Shirley Liu

Authors
  1. Bo Li
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  2. Taiwen Li
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  3. Jun S. Liu
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  4. X. Shirley Liu
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Corresponding author

Correspondence to Bo Li .

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Editors and Affiliations

  1. Mainz, Germany

    Sebastian Boegel

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© 2020 Springer Science+Business Media, LLC, part of Springer Nature

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Li, B., Li, T., Liu, J.S., Liu, X.S. (2020). Computational Deconvolution of Tumor-Infiltrating Immune Components with Bulk Tumor Gene Expression Data. In: Boegel, S. (eds) Bioinformatics for Cancer Immunotherapy. Methods in Molecular Biology, vol 2120. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0327-7_18

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  • DOI: https://doi.org/10.1007/978-1-0716-0327-7_18

  • Published:

  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-0326-0

  • Online ISBN: 978-1-0716-0327-7

  • eBook Packages: Springer Protocols

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