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Tumor immunity landscape in non-small cell lung cancer
Even with the great advances in immunotherapy in recent years, the response rate to immune checkpoint inhibitor therapy for non-small cell lung cancer is only about 20%. We aimed to identify new features that would better predict which patients can benefit from an immune checkpoint blocker. This stu...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5868477/ https://www.ncbi.nlm.nih.gov/pubmed/29593943 http://dx.doi.org/10.7717/peerj.4546 |
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author | Yu, Xiaoqing Wang, Xuefeng |
author_facet | Yu, Xiaoqing Wang, Xuefeng |
author_sort | Yu, Xiaoqing |
collection | PubMed |
description | Even with the great advances in immunotherapy in recent years, the response rate to immune checkpoint inhibitor therapy for non-small cell lung cancer is only about 20%. We aimed to identify new features that would better predict which patients can benefit from an immune checkpoint blocker. This study is based on the publicly available gene expression data from The Cancer Genome Atlas lung cancer samples and the newly released mutation annotation data. We performed a comprehensive analysis by correlating patient cytolytic activity index, mutational signatures, and other immune characteristics in four stratified patient groups. The results cytolytic activity index are highly correlated with immune infiltration scores, T cell infiltration scores and TCR clonality scores in lung cancer. In addition, we observed that the mutational event signatures might play a more important role in predicting immunotherapy response in squamous cell carcinoma and two subgroups of adenocarcinomas. Our analysis illustrates the utility of integrating both tumor immune and genomic landscape for a better understanding of immune response in lung cancer. |
format | Online Article Text |
id | pubmed-5868477 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-58684772018-03-28 Tumor immunity landscape in non-small cell lung cancer Yu, Xiaoqing Wang, Xuefeng PeerJ Bioinformatics Even with the great advances in immunotherapy in recent years, the response rate to immune checkpoint inhibitor therapy for non-small cell lung cancer is only about 20%. We aimed to identify new features that would better predict which patients can benefit from an immune checkpoint blocker. This study is based on the publicly available gene expression data from The Cancer Genome Atlas lung cancer samples and the newly released mutation annotation data. We performed a comprehensive analysis by correlating patient cytolytic activity index, mutational signatures, and other immune characteristics in four stratified patient groups. The results cytolytic activity index are highly correlated with immune infiltration scores, T cell infiltration scores and TCR clonality scores in lung cancer. In addition, we observed that the mutational event signatures might play a more important role in predicting immunotherapy response in squamous cell carcinoma and two subgroups of adenocarcinomas. Our analysis illustrates the utility of integrating both tumor immune and genomic landscape for a better understanding of immune response in lung cancer. PeerJ Inc. 2018-03-23 /pmc/articles/PMC5868477/ /pubmed/29593943 http://dx.doi.org/10.7717/peerj.4546 Text en ©2018 Yu and Wang http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Yu, Xiaoqing Wang, Xuefeng Tumor immunity landscape in non-small cell lung cancer |
title | Tumor immunity landscape in non-small cell lung cancer |
title_full | Tumor immunity landscape in non-small cell lung cancer |
title_fullStr | Tumor immunity landscape in non-small cell lung cancer |
title_full_unstemmed | Tumor immunity landscape in non-small cell lung cancer |
title_short | Tumor immunity landscape in non-small cell lung cancer |
title_sort | tumor immunity landscape in non-small cell lung cancer |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5868477/ https://www.ncbi.nlm.nih.gov/pubmed/29593943 http://dx.doi.org/10.7717/peerj.4546 |
work_keys_str_mv | AT yuxiaoqing tumorimmunitylandscapeinnonsmallcelllungcancer AT wangxuefeng tumorimmunitylandscapeinnonsmallcelllungcancer |