Exploration of M2 macrophage-related biomarkers and a candidate drug for glioblastoma using high-dimensional weighted gene co-expression network analysis
BackgroundMacrophages exhibit diverse activation states. Notably, M2 macrophages, alternatively activated cells, are notably increased within glioblastoma (GBM). Herein, our current study aimed to identify gene biomarkers relevant to M2 macrophages using high-dimensional weighted gene co-expression...
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Frontiers Media S.A.
2025-06-01
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| Series: | Frontiers in Pharmacology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphar.2025.1587258/full |
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| author | Suyin Feng Suyin Feng Suyin Feng Long Zhu Long Zhu Long Zhu Jinyuan Gu Kun Kou Yongtai Liu Guangmin Zhang Hua Lu Honglai Zhang Runfeng Sun Runfeng Sun |
| author_facet | Suyin Feng Suyin Feng Suyin Feng Long Zhu Long Zhu Long Zhu Jinyuan Gu Kun Kou Yongtai Liu Guangmin Zhang Hua Lu Honglai Zhang Runfeng Sun Runfeng Sun |
| author_sort | Suyin Feng |
| collection | DOAJ |
| description | BackgroundMacrophages exhibit diverse activation states. Notably, M2 macrophages, alternatively activated cells, are notably increased within glioblastoma (GBM). Herein, our current study aimed to identify gene biomarkers relevant to M2 macrophages using high-dimensional weighted gene co-expression network analysis (hdWGCNA) and predict a candidate drug for GBM.MethodsSingle-cell RNA sequencing (scRNA-seq) data (GSE162631) and expression data (GSE4290) for GBM were obtained from the Gene Expression Omnibus (GEO) database. The Seurat package was used for quality control, processing of scRNA-seq data, and identification of different GBM cell types. Subsequently, the clusterProfiler package was employed to functionally annotate the genes specifically highly expressed in the cells. Notably, genes related to the M2 macrophages were screened by differential expression analysis, and the gene modules were classified by hdWGCNA. Thereafter, a diagnostic model was constructed, and its robustness was tested. Moreover, drug candidates that could bind to the specific genes identified in this study were predicted and further confirmed via molecular docking.ResultsTen cell clusters were classified, with macrophages showing a higher proportion in GBM samples. Moreover, highly expressed genes specific to the M2 macrophages were mainly enriched in neutrophil migration, myeloid leukocyte migration, and chemokine production. A total of 11 gene modules (module 1–11) specific to M2 macrophages were also determined; notably, module 7 showed a relatively high expression of genes. Three key genes, namely, nuclear factor-kappa-B-inhibitor alpha (NFKBIA), nuclear receptor 4A2 (NR4A2), and FosB Proto-Oncogene, AP-1 Transcription Factor Subunit (FOSB), were obtained by intersecting 3,257 differentially expressed genes (DEGs) with the hub genes screened by hdWGCNA. These three genes were applied to establish a robust and reliable diagnostic model, and they were found to bind to the candidate drug thalidomide.ConclusionThe current study revealed the potential gene biomarkers and drug candidate for GBM based on genes related to M2 macrophages, contributing to the understanding of the underlying mechanism of GBM. |
| format | Article |
| id | doaj-art-bf511059d497494fa7ec3eb8657d6285 |
| institution | Kabale University |
| issn | 1663-9812 |
| language | English |
| publishDate | 2025-06-01 |
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| series | Frontiers in Pharmacology |
| spelling | doaj-art-bf511059d497494fa7ec3eb8657d62852025-08-20T03:28:09ZengFrontiers Media S.A.Frontiers in Pharmacology1663-98122025-06-011610.3389/fphar.2025.15872581587258Exploration of M2 macrophage-related biomarkers and a candidate drug for glioblastoma using high-dimensional weighted gene co-expression network analysisSuyin Feng0Suyin Feng1Suyin Feng2Long Zhu3Long Zhu4Long Zhu5Jinyuan Gu6Kun Kou7Yongtai Liu8Guangmin Zhang9Hua Lu10Honglai Zhang11Runfeng Sun12Runfeng Sun13Department of Neurosurgery, Affiliated Hospital of Jiangnan University, Wuxi, ChinaDepartment of Neurosurgery, Donghai County People’s Hospital, Donghai, ChinaJiangnan University Smart Healthcare Joint Laboratory, Donghai County People’s Hospital, Donghai, ChinaDepartment of Neurosurgery, Donghai County People’s Hospital, Donghai, ChinaJiangnan University Smart Healthcare Joint Laboratory, Donghai County People’s Hospital, Donghai, ChinaCardio-Cerebral Vascular Disease Prevention and Treatment Innovation Center, Donghai County People’s Hospital, Donghai, ChinaDonghai Intelligent Medical Innovation Center, Kangda College of Nanjing Medical University, Lianyungang, ChinaDepartment of Neurosurgery, Donghai County People’s Hospital, Donghai, ChinaDepartment of Neurosurgery, Donghai County People’s Hospital, Donghai, ChinaDepartment of Neurosurgery, Donghai County People’s Hospital, Donghai, ChinaDepartment of Neurosurgery, Affiliated Hospital of Jiangnan University, Wuxi, ChinaDonghai Intelligent Medical Innovation Center, Kangda College of Nanjing Medical University, Lianyungang, ChinaJiangnan University Smart Healthcare Joint Laboratory, Donghai County People’s Hospital, Donghai, ChinaDonghai Intelligent Medical Innovation Center, Kangda College of Nanjing Medical University, Lianyungang, ChinaBackgroundMacrophages exhibit diverse activation states. Notably, M2 macrophages, alternatively activated cells, are notably increased within glioblastoma (GBM). Herein, our current study aimed to identify gene biomarkers relevant to M2 macrophages using high-dimensional weighted gene co-expression network analysis (hdWGCNA) and predict a candidate drug for GBM.MethodsSingle-cell RNA sequencing (scRNA-seq) data (GSE162631) and expression data (GSE4290) for GBM were obtained from the Gene Expression Omnibus (GEO) database. The Seurat package was used for quality control, processing of scRNA-seq data, and identification of different GBM cell types. Subsequently, the clusterProfiler package was employed to functionally annotate the genes specifically highly expressed in the cells. Notably, genes related to the M2 macrophages were screened by differential expression analysis, and the gene modules were classified by hdWGCNA. Thereafter, a diagnostic model was constructed, and its robustness was tested. Moreover, drug candidates that could bind to the specific genes identified in this study were predicted and further confirmed via molecular docking.ResultsTen cell clusters were classified, with macrophages showing a higher proportion in GBM samples. Moreover, highly expressed genes specific to the M2 macrophages were mainly enriched in neutrophil migration, myeloid leukocyte migration, and chemokine production. A total of 11 gene modules (module 1–11) specific to M2 macrophages were also determined; notably, module 7 showed a relatively high expression of genes. Three key genes, namely, nuclear factor-kappa-B-inhibitor alpha (NFKBIA), nuclear receptor 4A2 (NR4A2), and FosB Proto-Oncogene, AP-1 Transcription Factor Subunit (FOSB), were obtained by intersecting 3,257 differentially expressed genes (DEGs) with the hub genes screened by hdWGCNA. These three genes were applied to establish a robust and reliable diagnostic model, and they were found to bind to the candidate drug thalidomide.ConclusionThe current study revealed the potential gene biomarkers and drug candidate for GBM based on genes related to M2 macrophages, contributing to the understanding of the underlying mechanism of GBM.https://www.frontiersin.org/articles/10.3389/fphar.2025.1587258/fulltumor-associated macrophagesM2 macrophagesglioblastomahigh-dimensional weighted gene co-expression network analysisthalidomide |
| spellingShingle | Suyin Feng Suyin Feng Suyin Feng Long Zhu Long Zhu Long Zhu Jinyuan Gu Kun Kou Yongtai Liu Guangmin Zhang Hua Lu Honglai Zhang Runfeng Sun Runfeng Sun Exploration of M2 macrophage-related biomarkers and a candidate drug for glioblastoma using high-dimensional weighted gene co-expression network analysis Frontiers in Pharmacology tumor-associated macrophages M2 macrophages glioblastoma high-dimensional weighted gene co-expression network analysis thalidomide |
| title | Exploration of M2 macrophage-related biomarkers and a candidate drug for glioblastoma using high-dimensional weighted gene co-expression network analysis |
| title_full | Exploration of M2 macrophage-related biomarkers and a candidate drug for glioblastoma using high-dimensional weighted gene co-expression network analysis |
| title_fullStr | Exploration of M2 macrophage-related biomarkers and a candidate drug for glioblastoma using high-dimensional weighted gene co-expression network analysis |
| title_full_unstemmed | Exploration of M2 macrophage-related biomarkers and a candidate drug for glioblastoma using high-dimensional weighted gene co-expression network analysis |
| title_short | Exploration of M2 macrophage-related biomarkers and a candidate drug for glioblastoma using high-dimensional weighted gene co-expression network analysis |
| title_sort | exploration of m2 macrophage related biomarkers and a candidate drug for glioblastoma using high dimensional weighted gene co expression network analysis |
| topic | tumor-associated macrophages M2 macrophages glioblastoma high-dimensional weighted gene co-expression network analysis thalidomide |
| url | https://www.frontiersin.org/articles/10.3389/fphar.2025.1587258/full |
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