Integrative Analysis of Single-Cell and Bulk RNA Sequencing Reveals Prognostic Characteristics of Macrophage Polarization-Related Genes in Lung Adenocarcinoma

Ke Mi, Lizhong Zeng, Yang Chen, Shuanying Yang Department of Respiratory and Critical Care Medicine, the Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of ChinaCorrespondence: Shuanying Yang, Department of Respiratory Medicine, the Second Affiliated Hospit...

Full description

Bibliographic Details
Main Authors: Mi K, Zeng L, Chen Y, Yang S
Format: Article
Language:English
Published: Dove Medical Press 2023-11-01
Series:International Journal of General Medicine
Subjects:
Online Access:https://www.dovepress.com/integrative-analysis-of-single-cell-and-bulk-rna-sequencing-reveals-pr-peer-reviewed-fulltext-article-IJGM
_version_ 1797636596396195840
author Mi K
Zeng L
Chen Y
Yang S
author_facet Mi K
Zeng L
Chen Y
Yang S
author_sort Mi K
collection DOAJ
description Ke Mi, Lizhong Zeng, Yang Chen, Shuanying Yang Department of Respiratory and Critical Care Medicine, the Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of ChinaCorrespondence: Shuanying Yang, Department of Respiratory Medicine, the Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China, Email yangshuanying66@163.comBackground: Lung adenocarcinoma (LUAD) is a group of cancers with poor prognosis. The combination of single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (RNA-seq) can identify important genes involved in cancer development and progression from a broader perspective.Methods: The scRNA-seq data and bulk RNA-seq data of LUAD were downloaded from the Gene Expression Omnibus (GEO) database and the Cancer Genome Atlas (TCGA) database. Analyzing scRNA-seq for core cells in the GSE131907 dataset, and the uniform manifold approximation and projection (UMAP) was used for dimensionality reduction and cluster identification. Macrophage polarization-associated subtypes were acquired from the TCGA-LUAD dataset after analysis, followed by further identification of differentially expressed genes (DEGs) in the TCGA-LUAD dataset (normal/LUAD tissue samples, two subtypes). Venn diagrams were utilized to visualize differentially expressed and highly variable macrophage polarization-related genes. Subsequently, a prognostic risk model for LUAD patients was constructed by univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO), and the model was investigated for stability in the external data GSE72094. After analyzing the correlation between the trait genes and significantly mutated genes, the immune infiltration between the high/low-risk groups was then examined. The Monocle package was applied to analyze the pseudo-temporal trajectory analysis of different cell clusters in macrophage clusters. Subsequently, cell clusters of data macrophages were selected as key cell clusters to explore the role of characteristic genes in different cell populations and to identify transcription factors (TFs) that affect signature genes. Finally, qPCR were employed to validate the expression levels of prognosis signature genes in LUAD.Results: 424 macrophage highly variable genes, 3920 DEGs, and 9561 DEGs were obtained from macrophage clusters, the macrophage polarization-related subtypes, and normal/LUAD tissue samples, respectively. Twenty-eight differentially expressed and highly mutated MPRGs were obtained. A prognostic risk model with 7 DE-MPRGs (RGS13, ADRB2, DDIT4, MS4A2, ALDH2, CTSH, and PKM) was constructed. This prognostic model still has a good prediction effect in the GSE72094 dataset. ZNF536 and DNAH9 were mutated in the low-risk group, while COL11A1 was mutated in the high-risk group, and they were highly correlated with the characteristic genes. A total of 11 immune cells were significantly different in the high/low-risk groups. Five cell types were again identified in the macrophage cluster, and then NK cells: CD56hiCD62L+ differentiated earlier and were present mainly on 2 branches. While macrophages were present on 2 branches and differentiated later. It was found that the expression levels of BCLAF1 and MAX were higher in cluster 1, which might be the TFs affecting the expression of the characteristic genes. Moreover, qPCR confirmed that the expression of the prognosis genes was generally consistent with the results of the bioinformatic analysis.Conclusion: Seven MPRGs (RGS13, ADRB2, DDIT4, MS4A2, ALDH2, CTSH, and PKM) were identified as prognostic genes for LUAD and revealed the mechanisms of MPRGs at the single-cell level.Keywords: lung adenocarcinoma, macrophage polarization-related genes, prognostic risk model, single-cell RNA sequencing, regulation mechanism
first_indexed 2024-03-11T12:36:21Z
format Article
id doaj.art-25dc07d56ead4850b74e33b72465e1e9
institution Directory Open Access Journal
issn 1178-7074
language English
last_indexed 2024-03-11T12:36:21Z
publishDate 2023-11-01
publisher Dove Medical Press
record_format Article
series International Journal of General Medicine
spelling doaj.art-25dc07d56ead4850b74e33b72465e1e92023-11-05T18:06:31ZengDove Medical PressInternational Journal of General Medicine1178-70742023-11-01Volume 165031505087864Integrative Analysis of Single-Cell and Bulk RNA Sequencing Reveals Prognostic Characteristics of Macrophage Polarization-Related Genes in Lung AdenocarcinomaMi KZeng LChen YYang SKe Mi, Lizhong Zeng, Yang Chen, Shuanying Yang Department of Respiratory and Critical Care Medicine, the Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of ChinaCorrespondence: Shuanying Yang, Department of Respiratory Medicine, the Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China, Email yangshuanying66@163.comBackground: Lung adenocarcinoma (LUAD) is a group of cancers with poor prognosis. The combination of single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (RNA-seq) can identify important genes involved in cancer development and progression from a broader perspective.Methods: The scRNA-seq data and bulk RNA-seq data of LUAD were downloaded from the Gene Expression Omnibus (GEO) database and the Cancer Genome Atlas (TCGA) database. Analyzing scRNA-seq for core cells in the GSE131907 dataset, and the uniform manifold approximation and projection (UMAP) was used for dimensionality reduction and cluster identification. Macrophage polarization-associated subtypes were acquired from the TCGA-LUAD dataset after analysis, followed by further identification of differentially expressed genes (DEGs) in the TCGA-LUAD dataset (normal/LUAD tissue samples, two subtypes). Venn diagrams were utilized to visualize differentially expressed and highly variable macrophage polarization-related genes. Subsequently, a prognostic risk model for LUAD patients was constructed by univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO), and the model was investigated for stability in the external data GSE72094. After analyzing the correlation between the trait genes and significantly mutated genes, the immune infiltration between the high/low-risk groups was then examined. The Monocle package was applied to analyze the pseudo-temporal trajectory analysis of different cell clusters in macrophage clusters. Subsequently, cell clusters of data macrophages were selected as key cell clusters to explore the role of characteristic genes in different cell populations and to identify transcription factors (TFs) that affect signature genes. Finally, qPCR were employed to validate the expression levels of prognosis signature genes in LUAD.Results: 424 macrophage highly variable genes, 3920 DEGs, and 9561 DEGs were obtained from macrophage clusters, the macrophage polarization-related subtypes, and normal/LUAD tissue samples, respectively. Twenty-eight differentially expressed and highly mutated MPRGs were obtained. A prognostic risk model with 7 DE-MPRGs (RGS13, ADRB2, DDIT4, MS4A2, ALDH2, CTSH, and PKM) was constructed. This prognostic model still has a good prediction effect in the GSE72094 dataset. ZNF536 and DNAH9 were mutated in the low-risk group, while COL11A1 was mutated in the high-risk group, and they were highly correlated with the characteristic genes. A total of 11 immune cells were significantly different in the high/low-risk groups. Five cell types were again identified in the macrophage cluster, and then NK cells: CD56hiCD62L+ differentiated earlier and were present mainly on 2 branches. While macrophages were present on 2 branches and differentiated later. It was found that the expression levels of BCLAF1 and MAX were higher in cluster 1, which might be the TFs affecting the expression of the characteristic genes. Moreover, qPCR confirmed that the expression of the prognosis genes was generally consistent with the results of the bioinformatic analysis.Conclusion: Seven MPRGs (RGS13, ADRB2, DDIT4, MS4A2, ALDH2, CTSH, and PKM) were identified as prognostic genes for LUAD and revealed the mechanisms of MPRGs at the single-cell level.Keywords: lung adenocarcinoma, macrophage polarization-related genes, prognostic risk model, single-cell RNA sequencing, regulation mechanismhttps://www.dovepress.com/integrative-analysis-of-single-cell-and-bulk-rna-sequencing-reveals-pr-peer-reviewed-fulltext-article-IJGMlung adenocarcinomamacrophage polarization-related genesprognostic risk modelsingle-cell rna sequencingregulation mechanism
spellingShingle Mi K
Zeng L
Chen Y
Yang S
Integrative Analysis of Single-Cell and Bulk RNA Sequencing Reveals Prognostic Characteristics of Macrophage Polarization-Related Genes in Lung Adenocarcinoma
International Journal of General Medicine
lung adenocarcinoma
macrophage polarization-related genes
prognostic risk model
single-cell rna sequencing
regulation mechanism
title Integrative Analysis of Single-Cell and Bulk RNA Sequencing Reveals Prognostic Characteristics of Macrophage Polarization-Related Genes in Lung Adenocarcinoma
title_full Integrative Analysis of Single-Cell and Bulk RNA Sequencing Reveals Prognostic Characteristics of Macrophage Polarization-Related Genes in Lung Adenocarcinoma
title_fullStr Integrative Analysis of Single-Cell and Bulk RNA Sequencing Reveals Prognostic Characteristics of Macrophage Polarization-Related Genes in Lung Adenocarcinoma
title_full_unstemmed Integrative Analysis of Single-Cell and Bulk RNA Sequencing Reveals Prognostic Characteristics of Macrophage Polarization-Related Genes in Lung Adenocarcinoma
title_short Integrative Analysis of Single-Cell and Bulk RNA Sequencing Reveals Prognostic Characteristics of Macrophage Polarization-Related Genes in Lung Adenocarcinoma
title_sort integrative analysis of single cell and bulk rna sequencing reveals prognostic characteristics of macrophage polarization related genes in lung adenocarcinoma
topic lung adenocarcinoma
macrophage polarization-related genes
prognostic risk model
single-cell rna sequencing
regulation mechanism
url https://www.dovepress.com/integrative-analysis-of-single-cell-and-bulk-rna-sequencing-reveals-pr-peer-reviewed-fulltext-article-IJGM
work_keys_str_mv AT mik integrativeanalysisofsinglecellandbulkrnasequencingrevealsprognosticcharacteristicsofmacrophagepolarizationrelatedgenesinlungadenocarcinoma
AT zengl integrativeanalysisofsinglecellandbulkrnasequencingrevealsprognosticcharacteristicsofmacrophagepolarizationrelatedgenesinlungadenocarcinoma
AT cheny integrativeanalysisofsinglecellandbulkrnasequencingrevealsprognosticcharacteristicsofmacrophagepolarizationrelatedgenesinlungadenocarcinoma
AT yangs integrativeanalysisofsinglecellandbulkrnasequencingrevealsprognosticcharacteristicsofmacrophagepolarizationrelatedgenesinlungadenocarcinoma