Cargando…

Analysis of prognostic genes in the tumor microenvironment of lung adenocarcinoma

BACKGROUND: Prognostic genes in the tumor microenvironment play an important role in immune biological processes and the response of cancer to immunotherapy. Thus, we aimed to assess new biomarkers that are associated with immune/stromal cells in lung adenocarcinomas (LUAD) using the ESTIMATE algori...

Descripción completa

Detalles Bibliográficos
Autores principales: Xu, Zhan-yu, Zhao, Mengli, Chen, Wenjie, Li, Kun, Qin, Fanglu, Xiang, Wei-wei, Sun, Yu, Wei, Jiangbo, Yuan, Li-qiang, Li, Shi-kang, Lin, Sheng-hua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7382940/
https://www.ncbi.nlm.nih.gov/pubmed/32775050
http://dx.doi.org/10.7717/peerj.9530
_version_ 1783563348634238976
author Xu, Zhan-yu
Zhao, Mengli
Chen, Wenjie
Li, Kun
Qin, Fanglu
Xiang, Wei-wei
Sun, Yu
Wei, Jiangbo
Yuan, Li-qiang
Li, Shi-kang
Lin, Sheng-hua
author_facet Xu, Zhan-yu
Zhao, Mengli
Chen, Wenjie
Li, Kun
Qin, Fanglu
Xiang, Wei-wei
Sun, Yu
Wei, Jiangbo
Yuan, Li-qiang
Li, Shi-kang
Lin, Sheng-hua
author_sort Xu, Zhan-yu
collection PubMed
description BACKGROUND: Prognostic genes in the tumor microenvironment play an important role in immune biological processes and the response of cancer to immunotherapy. Thus, we aimed to assess new biomarkers that are associated with immune/stromal cells in lung adenocarcinomas (LUAD) using the ESTIMATE algorithm, which also significantly affects the prognosis of cancer. METHODS: The RNA sequencing (RNA-Seq) and clinical data of LUAD were downloaded from the the Cancer Genome Atlas (TCGA ). The immune and stromal scores were calculated for each sample using the ESTIMATE algorithm. The LUAD gene chip expression profile data and the clinical data (GSE37745, GSE11969, and GSE50081) were downloaded from the Gene Expression Omnibus (GEO) for subsequent validation analysis. Differentially expressed genes were calculated between high and low score groups. Univariate Cox regression analysis was performed on differentially expressed genes (DEGs) between the two groups to obtain initial prognosis genes. These were verified by three independent LUAD cohorts from the GEO database. Multivariate Cox regression was used to identify overall survival-related DEGs. UALCAN and the Human Protein Atlas were used to analyze the mRNA /protein expression levels of the target genes. Immune cell infiltration was evaluated using the Tumor Immune Estimation Resource (TIMER) and CIBERSORT methods, and stromal cell infiltration was assessed using xCell. RESULTS: In this study, immune scores and stromal scores are significantly associated with the clinical characteristics of LUAD, including T stage, M stage, pathological stage, and overall survival time. 530 DEGs (18 upregulated and 512 downregulated) were found to coexist in the difference analysis with the immune scores and stromal scores subgroup. Univariate Cox regression analysis showed that 286 of the 530 DEGs were survival-related genes (p < 0.05). Of the 286 genes initially identified, nine prognosis-related genes (CSF2RB, ITK, FLT3, CD79A, CCR4, CCR6, DOK2, AMPD1, and IGJ) were validated from three separate LUAD cohorts. In addition, functional analysis of DEGs also showed that various immunoregulatory molecular pathways, including regulation of immune response and the chemokine signaling pathways, were involved. Five genes (CCR6, ITK, CCR4, DOK2, and AMPD1) were identified as independent prognostic indicators of LUAD in specific data sets. The relationship between the expression levels of these genes and immune genes was assessed. We found that CCR6 mRNA and protein expression levels of LUAD were greater than in normal tissues. We evaluated the infiltration of immune cells and stromal cells in groups with high and low levels of expression of CCR6 in the TCGA LUAD cohort. In summary, we found a series of prognosis-related genes that were associated with the LUAD tumor microenvironment.
format Online
Article
Text
id pubmed-7382940
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher PeerJ Inc.
record_format MEDLINE/PubMed
spelling pubmed-73829402020-08-07 Analysis of prognostic genes in the tumor microenvironment of lung adenocarcinoma Xu, Zhan-yu Zhao, Mengli Chen, Wenjie Li, Kun Qin, Fanglu Xiang, Wei-wei Sun, Yu Wei, Jiangbo Yuan, Li-qiang Li, Shi-kang Lin, Sheng-hua PeerJ Bioinformatics BACKGROUND: Prognostic genes in the tumor microenvironment play an important role in immune biological processes and the response of cancer to immunotherapy. Thus, we aimed to assess new biomarkers that are associated with immune/stromal cells in lung adenocarcinomas (LUAD) using the ESTIMATE algorithm, which also significantly affects the prognosis of cancer. METHODS: The RNA sequencing (RNA-Seq) and clinical data of LUAD were downloaded from the the Cancer Genome Atlas (TCGA ). The immune and stromal scores were calculated for each sample using the ESTIMATE algorithm. The LUAD gene chip expression profile data and the clinical data (GSE37745, GSE11969, and GSE50081) were downloaded from the Gene Expression Omnibus (GEO) for subsequent validation analysis. Differentially expressed genes were calculated between high and low score groups. Univariate Cox regression analysis was performed on differentially expressed genes (DEGs) between the two groups to obtain initial prognosis genes. These were verified by three independent LUAD cohorts from the GEO database. Multivariate Cox regression was used to identify overall survival-related DEGs. UALCAN and the Human Protein Atlas were used to analyze the mRNA /protein expression levels of the target genes. Immune cell infiltration was evaluated using the Tumor Immune Estimation Resource (TIMER) and CIBERSORT methods, and stromal cell infiltration was assessed using xCell. RESULTS: In this study, immune scores and stromal scores are significantly associated with the clinical characteristics of LUAD, including T stage, M stage, pathological stage, and overall survival time. 530 DEGs (18 upregulated and 512 downregulated) were found to coexist in the difference analysis with the immune scores and stromal scores subgroup. Univariate Cox regression analysis showed that 286 of the 530 DEGs were survival-related genes (p < 0.05). Of the 286 genes initially identified, nine prognosis-related genes (CSF2RB, ITK, FLT3, CD79A, CCR4, CCR6, DOK2, AMPD1, and IGJ) were validated from three separate LUAD cohorts. In addition, functional analysis of DEGs also showed that various immunoregulatory molecular pathways, including regulation of immune response and the chemokine signaling pathways, were involved. Five genes (CCR6, ITK, CCR4, DOK2, and AMPD1) were identified as independent prognostic indicators of LUAD in specific data sets. The relationship between the expression levels of these genes and immune genes was assessed. We found that CCR6 mRNA and protein expression levels of LUAD were greater than in normal tissues. We evaluated the infiltration of immune cells and stromal cells in groups with high and low levels of expression of CCR6 in the TCGA LUAD cohort. In summary, we found a series of prognosis-related genes that were associated with the LUAD tumor microenvironment. PeerJ Inc. 2020-07-23 /pmc/articles/PMC7382940/ /pubmed/32775050 http://dx.doi.org/10.7717/peerj.9530 Text en ©2020 Xu et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Xu, Zhan-yu
Zhao, Mengli
Chen, Wenjie
Li, Kun
Qin, Fanglu
Xiang, Wei-wei
Sun, Yu
Wei, Jiangbo
Yuan, Li-qiang
Li, Shi-kang
Lin, Sheng-hua
Analysis of prognostic genes in the tumor microenvironment of lung adenocarcinoma
title Analysis of prognostic genes in the tumor microenvironment of lung adenocarcinoma
title_full Analysis of prognostic genes in the tumor microenvironment of lung adenocarcinoma
title_fullStr Analysis of prognostic genes in the tumor microenvironment of lung adenocarcinoma
title_full_unstemmed Analysis of prognostic genes in the tumor microenvironment of lung adenocarcinoma
title_short Analysis of prognostic genes in the tumor microenvironment of lung adenocarcinoma
title_sort analysis of prognostic genes in the tumor microenvironment of lung adenocarcinoma
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7382940/
https://www.ncbi.nlm.nih.gov/pubmed/32775050
http://dx.doi.org/10.7717/peerj.9530
work_keys_str_mv AT xuzhanyu analysisofprognosticgenesinthetumormicroenvironmentoflungadenocarcinoma
AT zhaomengli analysisofprognosticgenesinthetumormicroenvironmentoflungadenocarcinoma
AT chenwenjie analysisofprognosticgenesinthetumormicroenvironmentoflungadenocarcinoma
AT likun analysisofprognosticgenesinthetumormicroenvironmentoflungadenocarcinoma
AT qinfanglu analysisofprognosticgenesinthetumormicroenvironmentoflungadenocarcinoma
AT xiangweiwei analysisofprognosticgenesinthetumormicroenvironmentoflungadenocarcinoma
AT sunyu analysisofprognosticgenesinthetumormicroenvironmentoflungadenocarcinoma
AT weijiangbo analysisofprognosticgenesinthetumormicroenvironmentoflungadenocarcinoma
AT yuanliqiang analysisofprognosticgenesinthetumormicroenvironmentoflungadenocarcinoma
AT lishikang analysisofprognosticgenesinthetumormicroenvironmentoflungadenocarcinoma
AT linshenghua analysisofprognosticgenesinthetumormicroenvironmentoflungadenocarcinoma