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Comprehensive analyses of tumor immunity: implications for cancer immunotherapy
BACKGROUND: Understanding the interactions between tumor and the host immune system is critical to finding prognostic biomarkers, reducing drug resistance, and developing new therapies. Novel computational methods are needed to estimate tumor-infiltrating immune cells and understand tumor–immune int...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4993001/ https://www.ncbi.nlm.nih.gov/pubmed/27549193 http://dx.doi.org/10.1186/s13059-016-1028-7 |
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author | Li, Bo Severson, Eric Pignon, Jean-Christophe Zhao, Haoquan Li, Taiwen Novak, Jesse Jiang, Peng Shen, Hui Aster, Jon C. Rodig, Scott Signoretti, Sabina Liu, Jun S. Liu, X. Shirley |
author_facet | Li, Bo Severson, Eric Pignon, Jean-Christophe Zhao, Haoquan Li, Taiwen Novak, Jesse Jiang, Peng Shen, Hui Aster, Jon C. Rodig, Scott Signoretti, Sabina Liu, Jun S. Liu, X. Shirley |
author_sort | Li, Bo |
collection | PubMed |
description | BACKGROUND: Understanding the interactions between tumor and the host immune system is critical to finding prognostic biomarkers, reducing drug resistance, and developing new therapies. Novel computational methods are needed to estimate tumor-infiltrating immune cells and understand tumor–immune interactions in cancers. RESULTS: We analyze tumor-infiltrating immune cells in over 10,000 RNA-seq samples across 23 cancer types from The Cancer Genome Atlas (TCGA). Our computationally inferred immune infiltrates associate much more strongly with patient clinical features, viral infection status, and cancer genetic alterations than other computational approaches. Analysis of cancer/testis antigen expression and CD8 T-cell abundance suggests that MAGEA3 is a potential immune target in melanoma, but not in non-small cell lung cancer, and implicates SPAG5 as an alternative cancer vaccine target in multiple cancers. We find that melanomas expressing high levels of CTLA4 separate into two distinct groups with respect to CD8 T-cell infiltration, which might influence clinical responses to anti-CTLA4 agents. We observe similar dichotomy of TIM3 expression with respect to CD8 T cells in kidney cancer and validate it experimentally. The abundance of immune infiltration, together with our downstream analyses and findings, are accessible through TIMER, a public resource at http://cistrome.org/TIMER. CONCLUSIONS: We develop a computational approach to study tumor-infiltrating immune cells and their interactions with cancer cells. Our resource of immune-infiltrate levels, clinical associations, as well as predicted therapeutic markers may inform effective cancer vaccine and checkpoint blockade therapies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-016-1028-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4993001 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-49930012016-08-23 Comprehensive analyses of tumor immunity: implications for cancer immunotherapy Li, Bo Severson, Eric Pignon, Jean-Christophe Zhao, Haoquan Li, Taiwen Novak, Jesse Jiang, Peng Shen, Hui Aster, Jon C. Rodig, Scott Signoretti, Sabina Liu, Jun S. Liu, X. Shirley Genome Biol Research BACKGROUND: Understanding the interactions between tumor and the host immune system is critical to finding prognostic biomarkers, reducing drug resistance, and developing new therapies. Novel computational methods are needed to estimate tumor-infiltrating immune cells and understand tumor–immune interactions in cancers. RESULTS: We analyze tumor-infiltrating immune cells in over 10,000 RNA-seq samples across 23 cancer types from The Cancer Genome Atlas (TCGA). Our computationally inferred immune infiltrates associate much more strongly with patient clinical features, viral infection status, and cancer genetic alterations than other computational approaches. Analysis of cancer/testis antigen expression and CD8 T-cell abundance suggests that MAGEA3 is a potential immune target in melanoma, but not in non-small cell lung cancer, and implicates SPAG5 as an alternative cancer vaccine target in multiple cancers. We find that melanomas expressing high levels of CTLA4 separate into two distinct groups with respect to CD8 T-cell infiltration, which might influence clinical responses to anti-CTLA4 agents. We observe similar dichotomy of TIM3 expression with respect to CD8 T cells in kidney cancer and validate it experimentally. The abundance of immune infiltration, together with our downstream analyses and findings, are accessible through TIMER, a public resource at http://cistrome.org/TIMER. CONCLUSIONS: We develop a computational approach to study tumor-infiltrating immune cells and their interactions with cancer cells. Our resource of immune-infiltrate levels, clinical associations, as well as predicted therapeutic markers may inform effective cancer vaccine and checkpoint blockade therapies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-016-1028-7) contains supplementary material, which is available to authorized users. BioMed Central 2016-08-22 /pmc/articles/PMC4993001/ /pubmed/27549193 http://dx.doi.org/10.1186/s13059-016-1028-7 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Li, Bo Severson, Eric Pignon, Jean-Christophe Zhao, Haoquan Li, Taiwen Novak, Jesse Jiang, Peng Shen, Hui Aster, Jon C. Rodig, Scott Signoretti, Sabina Liu, Jun S. Liu, X. Shirley Comprehensive analyses of tumor immunity: implications for cancer immunotherapy |
title | Comprehensive analyses of tumor immunity: implications for cancer immunotherapy |
title_full | Comprehensive analyses of tumor immunity: implications for cancer immunotherapy |
title_fullStr | Comprehensive analyses of tumor immunity: implications for cancer immunotherapy |
title_full_unstemmed | Comprehensive analyses of tumor immunity: implications for cancer immunotherapy |
title_short | Comprehensive analyses of tumor immunity: implications for cancer immunotherapy |
title_sort | comprehensive analyses of tumor immunity: implications for cancer immunotherapy |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4993001/ https://www.ncbi.nlm.nih.gov/pubmed/27549193 http://dx.doi.org/10.1186/s13059-016-1028-7 |
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