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...

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Main Authors: Xiaoqing Yu, Xuefeng Wang
Format: Article
Language:English
Published: PeerJ Inc. 2018-03-01
Series:PeerJ
Subjects:
Online Access:https://peerj.com/articles/4546.pdf
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spelling doaj-8da3a1afacb94fb6b3b64b8b07bd3b6d2020-11-24T22:24:43ZengPeerJ Inc.PeerJ2167-83592018-03-016e454610.7717/peerj.4546Tumor immunity landscape in non-small cell lung cancerXiaoqing Yu0Xuefeng Wang1Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USADepartment of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USAEven 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.https://peerj.com/articles/4546.pdfTumor immunityMutational signatureNon-small cell lung cancerCytolytic activityTCR clonalityImmunotherapy
collection DOAJ
language English
format Article
sources DOAJ
author Xiaoqing Yu
Xuefeng Wang
spellingShingle Xiaoqing Yu
Xuefeng Wang
Tumor immunity landscape in non-small cell lung cancer
PeerJ
Tumor immunity
Mutational signature
Non-small cell lung cancer
Cytolytic activity
TCR clonality
Immunotherapy
author_facet Xiaoqing Yu
Xuefeng Wang
author_sort Xiaoqing Yu
title Tumor immunity landscape in non-small cell lung cancer
title_short 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_sort tumor immunity landscape in non-small cell lung cancer
publisher PeerJ Inc.
series PeerJ
issn 2167-8359
publishDate 2018-03-01
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.
topic Tumor immunity
Mutational signature
Non-small cell lung cancer
Cytolytic activity
TCR clonality
Immunotherapy
url https://peerj.com/articles/4546.pdf
work_keys_str_mv AT xiaoqingyu tumorimmunitylandscapeinnonsmallcelllungcancer
AT xuefengwang tumorimmunitylandscapeinnonsmallcelllungcancer
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