Cargando…
A new immune signature for survival prediction and immune checkpoint molecules in non-small cell lung cancer
BACKGROUND: Immune checkpoint blockade (ICB) therapy has brought remarkable clinical benefits to patients with advanced non-small cell lung carcinoma (NSCLC). However, the prognosis remains largely variable. METHODS: The profiles of immune-related genes for patients with NSCLC were extracted from TC...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9924230/ https://www.ncbi.nlm.nih.gov/pubmed/36793597 http://dx.doi.org/10.3389/fonc.2023.1095313 |
_version_ | 1784887853967212544 |
---|---|
author | Han, Shuai Jiang, Dongjie Zhang, Feng Li, Kun Jiao, Kun Hu, Jingyun Song, Haihan Ma, Qin-Yun Wang, Jian |
author_facet | Han, Shuai Jiang, Dongjie Zhang, Feng Li, Kun Jiao, Kun Hu, Jingyun Song, Haihan Ma, Qin-Yun Wang, Jian |
author_sort | Han, Shuai |
collection | PubMed |
description | BACKGROUND: Immune checkpoint blockade (ICB) therapy has brought remarkable clinical benefits to patients with advanced non-small cell lung carcinoma (NSCLC). However, the prognosis remains largely variable. METHODS: The profiles of immune-related genes for patients with NSCLC were extracted from TCGA database, ImmPort dataset, and IMGT/GENE-DB database. Coexpression modules were constructed using WGCNA and 4 modules were identified. The hub genes of the module with the highest correlations with tumor samples were identified. Then integrative bioinformatics analyses were performed to unveil the hub genes participating in tumor progression and cancer-associated immunology of NSCLC. Cox regression and Lasso regression analyses were conducted to screen prognostic signature and to develop a risk model. RESULTS: Functional analysis showed that immune-related hub genes were involved in the migration, activation, response, and cytokine-cytokine receptor interaction of immune cells. Most of the hub genes had a high frequency of gene amplifications. MASP1 and SEMA5A presented the highest mutation rate. The ratio of M2 macrophages and naïve B cells revealed a strong negative association while the ratio of CD8 T cells and activated CD4 memory T cells showed a strong positive association. Resting mast cells predicted superior overall survival. Interactions including protein–protein, lncRNA and transcription factor interactions were analyzed and 9 genes were selected by LASSO regression analysis to construct and verify a prognostic signature. Unsupervised hub genes clustering resulted in 2 distinct NSCLC subgroups. The TIDE score and the drug sensitivity of gemcitabine, cisplatin, docetaxel, erlotinib and paclitaxel were significantly different between the 2 immune-related hub gene subgroups. CONCLUSIONS: These findings suggested that our immune-related genes can provide clinical guidance for the diagnosis and prognosis of different immunophenotypes and facilitate the management of immunotherapy in NSCLC. |
format | Online Article Text |
id | pubmed-9924230 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-99242302023-02-14 A new immune signature for survival prediction and immune checkpoint molecules in non-small cell lung cancer Han, Shuai Jiang, Dongjie Zhang, Feng Li, Kun Jiao, Kun Hu, Jingyun Song, Haihan Ma, Qin-Yun Wang, Jian Front Oncol Oncology BACKGROUND: Immune checkpoint blockade (ICB) therapy has brought remarkable clinical benefits to patients with advanced non-small cell lung carcinoma (NSCLC). However, the prognosis remains largely variable. METHODS: The profiles of immune-related genes for patients with NSCLC were extracted from TCGA database, ImmPort dataset, and IMGT/GENE-DB database. Coexpression modules were constructed using WGCNA and 4 modules were identified. The hub genes of the module with the highest correlations with tumor samples were identified. Then integrative bioinformatics analyses were performed to unveil the hub genes participating in tumor progression and cancer-associated immunology of NSCLC. Cox regression and Lasso regression analyses were conducted to screen prognostic signature and to develop a risk model. RESULTS: Functional analysis showed that immune-related hub genes were involved in the migration, activation, response, and cytokine-cytokine receptor interaction of immune cells. Most of the hub genes had a high frequency of gene amplifications. MASP1 and SEMA5A presented the highest mutation rate. The ratio of M2 macrophages and naïve B cells revealed a strong negative association while the ratio of CD8 T cells and activated CD4 memory T cells showed a strong positive association. Resting mast cells predicted superior overall survival. Interactions including protein–protein, lncRNA and transcription factor interactions were analyzed and 9 genes were selected by LASSO regression analysis to construct and verify a prognostic signature. Unsupervised hub genes clustering resulted in 2 distinct NSCLC subgroups. The TIDE score and the drug sensitivity of gemcitabine, cisplatin, docetaxel, erlotinib and paclitaxel were significantly different between the 2 immune-related hub gene subgroups. CONCLUSIONS: These findings suggested that our immune-related genes can provide clinical guidance for the diagnosis and prognosis of different immunophenotypes and facilitate the management of immunotherapy in NSCLC. Frontiers Media S.A. 2023-01-30 /pmc/articles/PMC9924230/ /pubmed/36793597 http://dx.doi.org/10.3389/fonc.2023.1095313 Text en Copyright © 2023 Han, Jiang, Zhang, Li, Jiao, Hu, Song, Ma and Wang 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 | Oncology Han, Shuai Jiang, Dongjie Zhang, Feng Li, Kun Jiao, Kun Hu, Jingyun Song, Haihan Ma, Qin-Yun Wang, Jian A new immune signature for survival prediction and immune checkpoint molecules in non-small cell lung cancer |
title | A new immune signature for survival prediction and immune checkpoint molecules in non-small cell lung cancer |
title_full | A new immune signature for survival prediction and immune checkpoint molecules in non-small cell lung cancer |
title_fullStr | A new immune signature for survival prediction and immune checkpoint molecules in non-small cell lung cancer |
title_full_unstemmed | A new immune signature for survival prediction and immune checkpoint molecules in non-small cell lung cancer |
title_short | A new immune signature for survival prediction and immune checkpoint molecules in non-small cell lung cancer |
title_sort | new immune signature for survival prediction and immune checkpoint molecules in non-small cell lung cancer |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9924230/ https://www.ncbi.nlm.nih.gov/pubmed/36793597 http://dx.doi.org/10.3389/fonc.2023.1095313 |
work_keys_str_mv | AT hanshuai anewimmunesignatureforsurvivalpredictionandimmunecheckpointmoleculesinnonsmallcelllungcancer AT jiangdongjie anewimmunesignatureforsurvivalpredictionandimmunecheckpointmoleculesinnonsmallcelllungcancer AT zhangfeng anewimmunesignatureforsurvivalpredictionandimmunecheckpointmoleculesinnonsmallcelllungcancer AT likun anewimmunesignatureforsurvivalpredictionandimmunecheckpointmoleculesinnonsmallcelllungcancer AT jiaokun anewimmunesignatureforsurvivalpredictionandimmunecheckpointmoleculesinnonsmallcelllungcancer AT hujingyun anewimmunesignatureforsurvivalpredictionandimmunecheckpointmoleculesinnonsmallcelllungcancer AT songhaihan anewimmunesignatureforsurvivalpredictionandimmunecheckpointmoleculesinnonsmallcelllungcancer AT maqinyun anewimmunesignatureforsurvivalpredictionandimmunecheckpointmoleculesinnonsmallcelllungcancer AT wangjian anewimmunesignatureforsurvivalpredictionandimmunecheckpointmoleculesinnonsmallcelllungcancer AT hanshuai newimmunesignatureforsurvivalpredictionandimmunecheckpointmoleculesinnonsmallcelllungcancer AT jiangdongjie newimmunesignatureforsurvivalpredictionandimmunecheckpointmoleculesinnonsmallcelllungcancer AT zhangfeng newimmunesignatureforsurvivalpredictionandimmunecheckpointmoleculesinnonsmallcelllungcancer AT likun newimmunesignatureforsurvivalpredictionandimmunecheckpointmoleculesinnonsmallcelllungcancer AT jiaokun newimmunesignatureforsurvivalpredictionandimmunecheckpointmoleculesinnonsmallcelllungcancer AT hujingyun newimmunesignatureforsurvivalpredictionandimmunecheckpointmoleculesinnonsmallcelllungcancer AT songhaihan newimmunesignatureforsurvivalpredictionandimmunecheckpointmoleculesinnonsmallcelllungcancer AT maqinyun newimmunesignatureforsurvivalpredictionandimmunecheckpointmoleculesinnonsmallcelllungcancer AT wangjian newimmunesignatureforsurvivalpredictionandimmunecheckpointmoleculesinnonsmallcelllungcancer |