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A Computational Approach Identifies Immunogenic Features of Prognosis in Human Cancers
A large number of tumor intrinsic and extrinsic factors determine long-term survival in human cancers. In this study, we stratified 9120 tumors from 33 cancers with respect to their immune cell content and identified immunogenomic features associated with long-term survival. Our analysis demonstrate...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308325/ https://www.ncbi.nlm.nih.gov/pubmed/30622534 http://dx.doi.org/10.3389/fimmu.2018.03017 |
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author | Manoharan, Malini Mandloi, Nitin Priyadarshini, Sushri Patil, Ashwini Gupta, Rohit Iyer, Laxman Gupta, Ravi Chaudhuri, Amitabha |
author_facet | Manoharan, Malini Mandloi, Nitin Priyadarshini, Sushri Patil, Ashwini Gupta, Rohit Iyer, Laxman Gupta, Ravi Chaudhuri, Amitabha |
author_sort | Manoharan, Malini |
collection | PubMed |
description | A large number of tumor intrinsic and extrinsic factors determine long-term survival in human cancers. In this study, we stratified 9120 tumors from 33 cancers with respect to their immune cell content and identified immunogenomic features associated with long-term survival. Our analysis demonstrates that tumors infiltrated by CD8(+) T cells expressing higher levels of activation marker (PD1(hi)) along with TCR signaling genes and cytolytic T cell markers (IL2(hi)/TNF-α(hi)/IFN-γ(hi)/GZMA-B(hi)) extend survival, whereas survival benefit was absent for tumors infiltrated by anergic and hyperexhausted CD8(+) T cells characterized by high expression of CTLA-4, TIM3, LAG3, and genes linked to PI3K signaling pathway. The computational approach of using robust and highly specific gene expression signatures to deconvolute the tumor microenvironment has important clinical applications, such as selecting patients who will benefit from checkpoint inhibitor treatment. |
format | Online Article Text |
id | pubmed-6308325 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-63083252019-01-08 A Computational Approach Identifies Immunogenic Features of Prognosis in Human Cancers Manoharan, Malini Mandloi, Nitin Priyadarshini, Sushri Patil, Ashwini Gupta, Rohit Iyer, Laxman Gupta, Ravi Chaudhuri, Amitabha Front Immunol Immunology A large number of tumor intrinsic and extrinsic factors determine long-term survival in human cancers. In this study, we stratified 9120 tumors from 33 cancers with respect to their immune cell content and identified immunogenomic features associated with long-term survival. Our analysis demonstrates that tumors infiltrated by CD8(+) T cells expressing higher levels of activation marker (PD1(hi)) along with TCR signaling genes and cytolytic T cell markers (IL2(hi)/TNF-α(hi)/IFN-γ(hi)/GZMA-B(hi)) extend survival, whereas survival benefit was absent for tumors infiltrated by anergic and hyperexhausted CD8(+) T cells characterized by high expression of CTLA-4, TIM3, LAG3, and genes linked to PI3K signaling pathway. The computational approach of using robust and highly specific gene expression signatures to deconvolute the tumor microenvironment has important clinical applications, such as selecting patients who will benefit from checkpoint inhibitor treatment. Frontiers Media S.A. 2018-12-21 /pmc/articles/PMC6308325/ /pubmed/30622534 http://dx.doi.org/10.3389/fimmu.2018.03017 Text en Copyright © 2018 Manoharan, Mandloi, Priyadarshini, Patil, Gupta, Iyer, Gupta and Chaudhuri. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Immunology Manoharan, Malini Mandloi, Nitin Priyadarshini, Sushri Patil, Ashwini Gupta, Rohit Iyer, Laxman Gupta, Ravi Chaudhuri, Amitabha A Computational Approach Identifies Immunogenic Features of Prognosis in Human Cancers |
title | A Computational Approach Identifies Immunogenic Features of Prognosis in Human Cancers |
title_full | A Computational Approach Identifies Immunogenic Features of Prognosis in Human Cancers |
title_fullStr | A Computational Approach Identifies Immunogenic Features of Prognosis in Human Cancers |
title_full_unstemmed | A Computational Approach Identifies Immunogenic Features of Prognosis in Human Cancers |
title_short | A Computational Approach Identifies Immunogenic Features of Prognosis in Human Cancers |
title_sort | computational approach identifies immunogenic features of prognosis in human cancers |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308325/ https://www.ncbi.nlm.nih.gov/pubmed/30622534 http://dx.doi.org/10.3389/fimmu.2018.03017 |
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