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Clinical M2 Macrophage-Related Genes Can Serve as a Reliable Predictor of Lung Adenocarcinoma

BACKGROUND: Numerous studies have found that infiltrating M2 macrophages play an important role in the tumor progression of lung adenocarcinoma (LUAD). However, the roles of M2 macrophage infiltration and M2 macrophage-related genes in immunotherapy and clinical outcomes remain obscure. METHODS: Sam...

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Autores principales: Xu, Chaojie, Song, Lishan, Yang, Yubin, Liu, Yi, Pei, Dongchen, Liu, Jiabang, Guo, Jianhua, Liu, Nan, Li, Xiaoyong, Liu, Yuchen, Li, Xuesong, Yao, Lin, Kang, Zhengjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9352953/
https://www.ncbi.nlm.nih.gov/pubmed/35936688
http://dx.doi.org/10.3389/fonc.2022.919899
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author Xu, Chaojie
Song, Lishan
Yang, Yubin
Liu, Yi
Pei, Dongchen
Liu, Jiabang
Guo, Jianhua
Liu, Nan
Li, Xiaoyong
Liu, Yuchen
Li, Xuesong
Yao, Lin
Kang, Zhengjun
author_facet Xu, Chaojie
Song, Lishan
Yang, Yubin
Liu, Yi
Pei, Dongchen
Liu, Jiabang
Guo, Jianhua
Liu, Nan
Li, Xiaoyong
Liu, Yuchen
Li, Xuesong
Yao, Lin
Kang, Zhengjun
author_sort Xu, Chaojie
collection PubMed
description BACKGROUND: Numerous studies have found that infiltrating M2 macrophages play an important role in the tumor progression of lung adenocarcinoma (LUAD). However, the roles of M2 macrophage infiltration and M2 macrophage-related genes in immunotherapy and clinical outcomes remain obscure. METHODS: Sample information was extracted from TCGA and GEO databases. The TIME landscape was revealed using the CIBERSORT algorithm. Weighted gene co-expression network analysis (WGCNA) was used to find M2 macrophage-related gene modules. Through univariate Cox regression, lasso regression analysis, and multivariate Cox regression, the genes strongly associated with the prognosis of LUAD were screened out. Risk score (RS) was calculated, and all samples were divided into high-risk group (HRG) and low-risk group (LRG) according to the median RS. External validation of RS was performed using GSE68571 data information. Prognostic nomogram based on risk signatures and other clinical information were constructed and validated with calibration curves. Potential associations of tumor mutational burden (TMB) and risk signatures were analyzed. Finally, the potential association of risk signatures with chemotherapy efficacy was investigated using the pRRophetic algorithm. RESULTS: Based on 504 samples extracted from TCGA database, 183 core genes were identified using WGCNA. Through a series of screening, two M2 macrophage-related genes (GRIA1 and CLEC3B) strongly correlated with LUAD prognosis were finally selected. RS was calculated, and prognostic risk nomogram including gender, age, T, N, M stage, clinical stage, and RS were constructed. The calibration curve shows that our constructed model has good performance. HRG patients were suitable for new ICI immunotherapy, while LRG was more suitable for CTLA4-immunosuppressive therapy alone. The half-maximal inhibitory concentrations (IC50) of the four chemotherapeutic drugs (metformin, cisplatin, paclitaxel, and gemcitabine) showed significant differences in HRG/LRG. CONCLUSIONS: In conclusion, a comprehensive analysis of the role of M2 macrophages in tumor progression will help predict prognosis and facilitate the advancement of therapeutic techniques.
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spelling pubmed-93529532022-08-06 Clinical M2 Macrophage-Related Genes Can Serve as a Reliable Predictor of Lung Adenocarcinoma Xu, Chaojie Song, Lishan Yang, Yubin Liu, Yi Pei, Dongchen Liu, Jiabang Guo, Jianhua Liu, Nan Li, Xiaoyong Liu, Yuchen Li, Xuesong Yao, Lin Kang, Zhengjun Front Oncol Oncology BACKGROUND: Numerous studies have found that infiltrating M2 macrophages play an important role in the tumor progression of lung adenocarcinoma (LUAD). However, the roles of M2 macrophage infiltration and M2 macrophage-related genes in immunotherapy and clinical outcomes remain obscure. METHODS: Sample information was extracted from TCGA and GEO databases. The TIME landscape was revealed using the CIBERSORT algorithm. Weighted gene co-expression network analysis (WGCNA) was used to find M2 macrophage-related gene modules. Through univariate Cox regression, lasso regression analysis, and multivariate Cox regression, the genes strongly associated with the prognosis of LUAD were screened out. Risk score (RS) was calculated, and all samples were divided into high-risk group (HRG) and low-risk group (LRG) according to the median RS. External validation of RS was performed using GSE68571 data information. Prognostic nomogram based on risk signatures and other clinical information were constructed and validated with calibration curves. Potential associations of tumor mutational burden (TMB) and risk signatures were analyzed. Finally, the potential association of risk signatures with chemotherapy efficacy was investigated using the pRRophetic algorithm. RESULTS: Based on 504 samples extracted from TCGA database, 183 core genes were identified using WGCNA. Through a series of screening, two M2 macrophage-related genes (GRIA1 and CLEC3B) strongly correlated with LUAD prognosis were finally selected. RS was calculated, and prognostic risk nomogram including gender, age, T, N, M stage, clinical stage, and RS were constructed. The calibration curve shows that our constructed model has good performance. HRG patients were suitable for new ICI immunotherapy, while LRG was more suitable for CTLA4-immunosuppressive therapy alone. The half-maximal inhibitory concentrations (IC50) of the four chemotherapeutic drugs (metformin, cisplatin, paclitaxel, and gemcitabine) showed significant differences in HRG/LRG. CONCLUSIONS: In conclusion, a comprehensive analysis of the role of M2 macrophages in tumor progression will help predict prognosis and facilitate the advancement of therapeutic techniques. Frontiers Media S.A. 2022-07-22 /pmc/articles/PMC9352953/ /pubmed/35936688 http://dx.doi.org/10.3389/fonc.2022.919899 Text en Copyright © 2022 Xu, Song, Yang, Liu, Pei, Liu, Guo, Liu, Li, Liu, Li, Yao and Kang 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
Xu, Chaojie
Song, Lishan
Yang, Yubin
Liu, Yi
Pei, Dongchen
Liu, Jiabang
Guo, Jianhua
Liu, Nan
Li, Xiaoyong
Liu, Yuchen
Li, Xuesong
Yao, Lin
Kang, Zhengjun
Clinical M2 Macrophage-Related Genes Can Serve as a Reliable Predictor of Lung Adenocarcinoma
title Clinical M2 Macrophage-Related Genes Can Serve as a Reliable Predictor of Lung Adenocarcinoma
title_full Clinical M2 Macrophage-Related Genes Can Serve as a Reliable Predictor of Lung Adenocarcinoma
title_fullStr Clinical M2 Macrophage-Related Genes Can Serve as a Reliable Predictor of Lung Adenocarcinoma
title_full_unstemmed Clinical M2 Macrophage-Related Genes Can Serve as a Reliable Predictor of Lung Adenocarcinoma
title_short Clinical M2 Macrophage-Related Genes Can Serve as a Reliable Predictor of Lung Adenocarcinoma
title_sort clinical m2 macrophage-related genes can serve as a reliable predictor of lung adenocarcinoma
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9352953/
https://www.ncbi.nlm.nih.gov/pubmed/35936688
http://dx.doi.org/10.3389/fonc.2022.919899
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