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Estimation of immune cell content in tumour tissue using single-cell RNA-seq data
As interactions between the immune system and tumour cells are governed by a complex network of cell–cell interactions, knowing the specific immune cell composition of a solid tumour may be essential to predict a patient’s response to immunotherapy. Here, we analyse in depth how to derive the cellul...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5725570/ https://www.ncbi.nlm.nih.gov/pubmed/29230012 http://dx.doi.org/10.1038/s41467-017-02289-3 |
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author | Schelker, Max Feau, Sonia Du, Jinyan Ranu, Nav Klipp, Edda MacBeath, Gavin Schoeberl, Birgit Raue, Andreas |
author_facet | Schelker, Max Feau, Sonia Du, Jinyan Ranu, Nav Klipp, Edda MacBeath, Gavin Schoeberl, Birgit Raue, Andreas |
author_sort | Schelker, Max |
collection | PubMed |
description | As interactions between the immune system and tumour cells are governed by a complex network of cell–cell interactions, knowing the specific immune cell composition of a solid tumour may be essential to predict a patient’s response to immunotherapy. Here, we analyse in depth how to derive the cellular composition of a solid tumour from bulk gene expression data by mathematical deconvolution, using indication-specific and cell type-specific reference gene expression profiles (RGEPs) from tumour-derived single-cell RNA sequencing data. We demonstrate that tumour-derived RGEPs are essential for the successful deconvolution and that RGEPs from peripheral blood are insufficient. We distinguish nine major cell types, as well as three T cell subtypes. Using the tumour-derived RGEPs, we can estimate the content of many tumours associated immune and stromal cell types, their therapeutically relevant ratios, as well as an improved gene expression profile of the malignant cells. |
format | Online Article Text |
id | pubmed-5725570 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-57255702017-12-14 Estimation of immune cell content in tumour tissue using single-cell RNA-seq data Schelker, Max Feau, Sonia Du, Jinyan Ranu, Nav Klipp, Edda MacBeath, Gavin Schoeberl, Birgit Raue, Andreas Nat Commun Article As interactions between the immune system and tumour cells are governed by a complex network of cell–cell interactions, knowing the specific immune cell composition of a solid tumour may be essential to predict a patient’s response to immunotherapy. Here, we analyse in depth how to derive the cellular composition of a solid tumour from bulk gene expression data by mathematical deconvolution, using indication-specific and cell type-specific reference gene expression profiles (RGEPs) from tumour-derived single-cell RNA sequencing data. We demonstrate that tumour-derived RGEPs are essential for the successful deconvolution and that RGEPs from peripheral blood are insufficient. We distinguish nine major cell types, as well as three T cell subtypes. Using the tumour-derived RGEPs, we can estimate the content of many tumours associated immune and stromal cell types, their therapeutically relevant ratios, as well as an improved gene expression profile of the malignant cells. Nature Publishing Group UK 2017-12-11 /pmc/articles/PMC5725570/ /pubmed/29230012 http://dx.doi.org/10.1038/s41467-017-02289-3 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Schelker, Max Feau, Sonia Du, Jinyan Ranu, Nav Klipp, Edda MacBeath, Gavin Schoeberl, Birgit Raue, Andreas Estimation of immune cell content in tumour tissue using single-cell RNA-seq data |
title | Estimation of immune cell content in tumour tissue using single-cell RNA-seq data |
title_full | Estimation of immune cell content in tumour tissue using single-cell RNA-seq data |
title_fullStr | Estimation of immune cell content in tumour tissue using single-cell RNA-seq data |
title_full_unstemmed | Estimation of immune cell content in tumour tissue using single-cell RNA-seq data |
title_short | Estimation of immune cell content in tumour tissue using single-cell RNA-seq data |
title_sort | estimation of immune cell content in tumour tissue using single-cell rna-seq data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5725570/ https://www.ncbi.nlm.nih.gov/pubmed/29230012 http://dx.doi.org/10.1038/s41467-017-02289-3 |
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