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Identification and Validation of the Immune Subtypes of Lung Adenocarcinoma: Implications for Immunotherapy
Lung adenocarcinoma (LUAD) is a devastating disease with poor patient survival. Cancer immunotherapy has revolutionized the treatment of LUAD, but only a limited number of patients effectively respond to this treatment. Thus, the work to elucidate the LUAD immune heterogeneity could be crucial in de...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7348081/ https://www.ncbi.nlm.nih.gov/pubmed/32719796 http://dx.doi.org/10.3389/fcell.2020.00550 |
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author | Song, Yang Yan, Shi Fan, Weina Zhang, Mengyan Liu, Wei Lu, Hailing Cao, Mengru Hao, Chenguang Chen, Lin Tian, Fanglin Zhan, Yuning Cai, Li Xing, Ying |
author_facet | Song, Yang Yan, Shi Fan, Weina Zhang, Mengyan Liu, Wei Lu, Hailing Cao, Mengru Hao, Chenguang Chen, Lin Tian, Fanglin Zhan, Yuning Cai, Li Xing, Ying |
author_sort | Song, Yang |
collection | PubMed |
description | Lung adenocarcinoma (LUAD) is a devastating disease with poor patient survival. Cancer immunotherapy has revolutionized the treatment of LUAD, but only a limited number of patients effectively respond to this treatment. Thus, the work to elucidate the LUAD immune heterogeneity could be crucial in developing new immunotherapeutic strategies with better efficacy. Non-negative matrix factorization-based deconvolution was performed to identify robust clusters of 489 LUAD patients in The Cancer Genome Atlas (TCGA) and verify their reproducibility and stability in an independent LUAD cohort of 439 patients from the Gene Expression Omnibus (GEO). We used the graph learning-based dimensionality reduction to visualize the distribution of individual patients. In this study, four reproducible immune subtypes, Clusters 1–4 (C1–C4) associated with distinct gene module signatures, clinicopathological features, molecular and cellular characteristics were identified and validated. The immune-cold subtype, C3, was associated with the Dead event, the most advanced T stage, N stage, TNM stage and the worst prognosis for LUAD patients. Moreover, C3 exhibited the lowest infiltrating levels of B cells, T cell receptor (TCR) repertoire diversity and the highest level of neoantigen and mutation rate among C1–C4. On the other hand, the immune-hot subtype (C4) exhibited the highest infiltration of six types of infiltrating immune cells as well as the greatest leukocyte fraction, TCR and B cell receptor (BCR) repertoire diversity. C1 and C2 subtypes showed diverse clinicopathological and immunological features. Finally, our investigations discovered a complex immune landscape with a scattered immune subtype profile. This work may help inform immunotherapeutic decision-making and design advanced immunotherapy strategies for the treatment of lung cancer. |
format | Online Article Text |
id | pubmed-7348081 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73480812020-07-26 Identification and Validation of the Immune Subtypes of Lung Adenocarcinoma: Implications for Immunotherapy Song, Yang Yan, Shi Fan, Weina Zhang, Mengyan Liu, Wei Lu, Hailing Cao, Mengru Hao, Chenguang Chen, Lin Tian, Fanglin Zhan, Yuning Cai, Li Xing, Ying Front Cell Dev Biol Cell and Developmental Biology Lung adenocarcinoma (LUAD) is a devastating disease with poor patient survival. Cancer immunotherapy has revolutionized the treatment of LUAD, but only a limited number of patients effectively respond to this treatment. Thus, the work to elucidate the LUAD immune heterogeneity could be crucial in developing new immunotherapeutic strategies with better efficacy. Non-negative matrix factorization-based deconvolution was performed to identify robust clusters of 489 LUAD patients in The Cancer Genome Atlas (TCGA) and verify their reproducibility and stability in an independent LUAD cohort of 439 patients from the Gene Expression Omnibus (GEO). We used the graph learning-based dimensionality reduction to visualize the distribution of individual patients. In this study, four reproducible immune subtypes, Clusters 1–4 (C1–C4) associated with distinct gene module signatures, clinicopathological features, molecular and cellular characteristics were identified and validated. The immune-cold subtype, C3, was associated with the Dead event, the most advanced T stage, N stage, TNM stage and the worst prognosis for LUAD patients. Moreover, C3 exhibited the lowest infiltrating levels of B cells, T cell receptor (TCR) repertoire diversity and the highest level of neoantigen and mutation rate among C1–C4. On the other hand, the immune-hot subtype (C4) exhibited the highest infiltration of six types of infiltrating immune cells as well as the greatest leukocyte fraction, TCR and B cell receptor (BCR) repertoire diversity. C1 and C2 subtypes showed diverse clinicopathological and immunological features. Finally, our investigations discovered a complex immune landscape with a scattered immune subtype profile. This work may help inform immunotherapeutic decision-making and design advanced immunotherapy strategies for the treatment of lung cancer. Frontiers Media S.A. 2020-07-03 /pmc/articles/PMC7348081/ /pubmed/32719796 http://dx.doi.org/10.3389/fcell.2020.00550 Text en Copyright © 2020 Song, Yan, Fan, Zhang, Liu, Lu, Cao, Hao, Chen, Tian, Zhan, Cai and Xing. 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 | Cell and Developmental Biology Song, Yang Yan, Shi Fan, Weina Zhang, Mengyan Liu, Wei Lu, Hailing Cao, Mengru Hao, Chenguang Chen, Lin Tian, Fanglin Zhan, Yuning Cai, Li Xing, Ying Identification and Validation of the Immune Subtypes of Lung Adenocarcinoma: Implications for Immunotherapy |
title | Identification and Validation of the Immune Subtypes of Lung Adenocarcinoma: Implications for Immunotherapy |
title_full | Identification and Validation of the Immune Subtypes of Lung Adenocarcinoma: Implications for Immunotherapy |
title_fullStr | Identification and Validation of the Immune Subtypes of Lung Adenocarcinoma: Implications for Immunotherapy |
title_full_unstemmed | Identification and Validation of the Immune Subtypes of Lung Adenocarcinoma: Implications for Immunotherapy |
title_short | Identification and Validation of the Immune Subtypes of Lung Adenocarcinoma: Implications for Immunotherapy |
title_sort | identification and validation of the immune subtypes of lung adenocarcinoma: implications for immunotherapy |
topic | Cell and Developmental Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7348081/ https://www.ncbi.nlm.nih.gov/pubmed/32719796 http://dx.doi.org/10.3389/fcell.2020.00550 |
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