In silico cell-type deconvolution methods in cancer immunotherapy

Gregor Sturm, Francesca Finotello, Markus List

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Scopus citations

Abstract

Several computational methods have been proposed to infer the cellular composition from bulk RNA-seq data of a tumor biopsy sample. Elucidating interactions in the tumor microenvironment can yield unique insights into the status of the immune system. In immuno-oncology, this information can be crucial for deciding whether the immune system of a patient can be stimulated to target the tumor. Here, we shed a light on the working principles, capabilities, and limitations of the most commonly used methods for cell-type deconvolution in immuno-oncology and offer guidelines for method selection.

Original languageEnglish
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Pages213-222
Number of pages10
DOIs
StatePublished - 2020

Publication series

NameMethods in Molecular Biology
Volume2120
ISSN (Print)1064-3745
ISSN (Electronic)1940-6029

Keywords

  • Cell-type deconvolution
  • Gene signatures
  • Immuno-oncology
  • Spillover

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