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Comprehensive Analysis of the Immune Microenvironment in Checkpoint Inhibitor Pneumonitis
BACKGROUND: While immune checkpoint inhibitors (ICIs) are a beacon of hope for non-small cell lung cancer (NSCLC) patients, they can also cause adverse events, including checkpoint inhibitor pneumonitis (CIP). Research shows that the inflammatory immune microenvironment plays a vital role in the dev...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8790088/ https://www.ncbi.nlm.nih.gov/pubmed/35095920 http://dx.doi.org/10.3389/fimmu.2021.818492 |
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author | Lin, Xinqing Deng, Jiaxi Deng, Haiyi Yang, Yilin Sun, Ni Zhou, Maolin Qin, Yinyin Xie, Xiaohong Li, Shiyue Zhong, Nanshan Song, Yong Zhou, Chengzhi |
author_facet | Lin, Xinqing Deng, Jiaxi Deng, Haiyi Yang, Yilin Sun, Ni Zhou, Maolin Qin, Yinyin Xie, Xiaohong Li, Shiyue Zhong, Nanshan Song, Yong Zhou, Chengzhi |
author_sort | Lin, Xinqing |
collection | PubMed |
description | BACKGROUND: While immune checkpoint inhibitors (ICIs) are a beacon of hope for non-small cell lung cancer (NSCLC) patients, they can also cause adverse events, including checkpoint inhibitor pneumonitis (CIP). Research shows that the inflammatory immune microenvironment plays a vital role in the development of CIP. However, the role of the immune microenvironment (IME) in CIP is still unclear. METHODS: We collected a cohort of NSCLC patients treated with ICIs that included eight individuals with CIP (CIP group) and 29 individuals without CIP (Control group). CIBERSORT and the xCell algorithm were used to evaluate the proportion of immune cells. Gene set enrichment analysis (GSEA) and single-sample GSEA (ssGSEA) were used to evaluate pathway activity. The ridge regression algorithm was used to analyze drug sensitivity. RESULTS: CIBERSORT showed significantly upregulated memory B cells, CD8+ T cells, and M1 Macrophages in the CIP group. The number of memory resting CD4+ T cells and resting NK cells in the CIP group was also significantly lower than in the Control group. The XCell analysis showed a higher proportion of Class-switched memory B-cells and M1 Macrophages in the CIP group. Pathway analysis showed that the CIP group had high activity in their immune and inflammatory response pathways and low activity in their immune exhaustion related pathway. CONCLUSIONS: In this study, we researched CIP patients who after ICIs treatment developed an inflammatory IME, which is characterized by significantly increased activated immune cells and expression of inflammatory molecules, as well as downregulated immunosuppressive lymphocytes and signaling pathways. The goal was to develop theoretical guidance for clinical guidelines for the treatment of CIP in the future. |
format | Online Article Text |
id | pubmed-8790088 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87900882022-01-27 Comprehensive Analysis of the Immune Microenvironment in Checkpoint Inhibitor Pneumonitis Lin, Xinqing Deng, Jiaxi Deng, Haiyi Yang, Yilin Sun, Ni Zhou, Maolin Qin, Yinyin Xie, Xiaohong Li, Shiyue Zhong, Nanshan Song, Yong Zhou, Chengzhi Front Immunol Immunology BACKGROUND: While immune checkpoint inhibitors (ICIs) are a beacon of hope for non-small cell lung cancer (NSCLC) patients, they can also cause adverse events, including checkpoint inhibitor pneumonitis (CIP). Research shows that the inflammatory immune microenvironment plays a vital role in the development of CIP. However, the role of the immune microenvironment (IME) in CIP is still unclear. METHODS: We collected a cohort of NSCLC patients treated with ICIs that included eight individuals with CIP (CIP group) and 29 individuals without CIP (Control group). CIBERSORT and the xCell algorithm were used to evaluate the proportion of immune cells. Gene set enrichment analysis (GSEA) and single-sample GSEA (ssGSEA) were used to evaluate pathway activity. The ridge regression algorithm was used to analyze drug sensitivity. RESULTS: CIBERSORT showed significantly upregulated memory B cells, CD8+ T cells, and M1 Macrophages in the CIP group. The number of memory resting CD4+ T cells and resting NK cells in the CIP group was also significantly lower than in the Control group. The XCell analysis showed a higher proportion of Class-switched memory B-cells and M1 Macrophages in the CIP group. Pathway analysis showed that the CIP group had high activity in their immune and inflammatory response pathways and low activity in their immune exhaustion related pathway. CONCLUSIONS: In this study, we researched CIP patients who after ICIs treatment developed an inflammatory IME, which is characterized by significantly increased activated immune cells and expression of inflammatory molecules, as well as downregulated immunosuppressive lymphocytes and signaling pathways. The goal was to develop theoretical guidance for clinical guidelines for the treatment of CIP in the future. Frontiers Media S.A. 2022-01-12 /pmc/articles/PMC8790088/ /pubmed/35095920 http://dx.doi.org/10.3389/fimmu.2021.818492 Text en Copyright © 2022 Lin, Deng, Deng, Yang, Sun, Zhou, Qin, Xie, Li, Zhong, Song and Zhou https://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 Lin, Xinqing Deng, Jiaxi Deng, Haiyi Yang, Yilin Sun, Ni Zhou, Maolin Qin, Yinyin Xie, Xiaohong Li, Shiyue Zhong, Nanshan Song, Yong Zhou, Chengzhi Comprehensive Analysis of the Immune Microenvironment in Checkpoint Inhibitor Pneumonitis |
title | Comprehensive Analysis of the Immune Microenvironment in Checkpoint Inhibitor Pneumonitis |
title_full | Comprehensive Analysis of the Immune Microenvironment in Checkpoint Inhibitor Pneumonitis |
title_fullStr | Comprehensive Analysis of the Immune Microenvironment in Checkpoint Inhibitor Pneumonitis |
title_full_unstemmed | Comprehensive Analysis of the Immune Microenvironment in Checkpoint Inhibitor Pneumonitis |
title_short | Comprehensive Analysis of the Immune Microenvironment in Checkpoint Inhibitor Pneumonitis |
title_sort | comprehensive analysis of the immune microenvironment in checkpoint inhibitor pneumonitis |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8790088/ https://www.ncbi.nlm.nih.gov/pubmed/35095920 http://dx.doi.org/10.3389/fimmu.2021.818492 |
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