Comprehensive analysis of plasma cell heterogeneity and immune interactions in multiple myeloma
This study focused on the role of plasma cells in multiple myeloma (MM) and the associated potential mechanisms. Transcriptomic data of MM and various gene sets from several public databases were downloaded for subsequent analyses. Through single-cell sequencing, 10 major cell types were identified...
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Frontiers Media S.A.
2025-04-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1549742/full |
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| author | Shuang Qu Zhihai Zheng Xiaoling Guo Jiaqi Mei Sicong Jiang Biyun Chen |
| author_facet | Shuang Qu Zhihai Zheng Xiaoling Guo Jiaqi Mei Sicong Jiang Biyun Chen |
| author_sort | Shuang Qu |
| collection | DOAJ |
| description | This study focused on the role of plasma cells in multiple myeloma (MM) and the associated potential mechanisms. Transcriptomic data of MM and various gene sets from several public databases were downloaded for subsequent analyses. Through single-cell sequencing, 10 major cell types were identified and annotated. The differential gene expression and pathway enrichment between different plasma cell subtypes as well as cell communication analysis, transcriptional regulation analysis, and enrichment analysis in conjunction with the malignant subpopulation were performed. Next, the samples were clustered into two groups by applying non-negative matrix factorization (NMF). Additional analysis revealed notable disparities in survival between the two clusters, correlation with genes involved in classical metabolic pathways and pathway dysregulation, thus confirming the stability and validity of the clustering. Subsequently, Weighted Gene Co-expression Network Analysis was performed and hub genes from the modules most strongly associated with the clustering groups were extracted. We then constructed a prognostic prediction model using Least Absolute Shrinkage and Selection Operator and multiCox regression analysis. The predictive accuracy of the model was evaluated and robustness were confirmed in a separate validation cohort. The gene and pathway dysregulation for the two risk groups was analyzed. Ultimately, an investigation was conducted into the association between the risk model and various immunological features, in terms of antitumor immunotherapy, the tumor microenvironment, and immune checkpoints. This study provides an in-depth investigation into the potential mechanisms underlying MM development and offers new directions to improve therapeutic approaches and enhance patient outcomes. |
| format | Article |
| id | doaj-art-6850f239502d4fdfbedbb1b5b57c4c6e |
| institution | OA Journals |
| issn | 1664-3224 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Immunology |
| spelling | doaj-art-6850f239502d4fdfbedbb1b5b57c4c6e2025-08-20T02:18:43ZengFrontiers Media S.A.Frontiers in Immunology1664-32242025-04-011610.3389/fimmu.2025.15497421549742Comprehensive analysis of plasma cell heterogeneity and immune interactions in multiple myelomaShuang Qu0Zhihai Zheng1Xiaoling Guo2Jiaqi Mei3Sicong Jiang4Biyun Chen5Department of Hematology, Shengli Clinical Medical College of Fujian Medical University, Fuzhou University Affiliated Provincial Hospital, Fuzhou, ChinaDepartment of Hematology, Shengli Clinical Medical College of Fujian Medical University, Fuzhou University Affiliated Provincial Hospital, Fuzhou, ChinaTranslational Medicine Centre, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, ChinaDepartment of Hematology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, ChinaDepartment of Hematology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, ChinaDepartment of Hematology, Shengli Clinical Medical College of Fujian Medical University, Fuzhou University Affiliated Provincial Hospital, Fuzhou, ChinaThis study focused on the role of plasma cells in multiple myeloma (MM) and the associated potential mechanisms. Transcriptomic data of MM and various gene sets from several public databases were downloaded for subsequent analyses. Through single-cell sequencing, 10 major cell types were identified and annotated. The differential gene expression and pathway enrichment between different plasma cell subtypes as well as cell communication analysis, transcriptional regulation analysis, and enrichment analysis in conjunction with the malignant subpopulation were performed. Next, the samples were clustered into two groups by applying non-negative matrix factorization (NMF). Additional analysis revealed notable disparities in survival between the two clusters, correlation with genes involved in classical metabolic pathways and pathway dysregulation, thus confirming the stability and validity of the clustering. Subsequently, Weighted Gene Co-expression Network Analysis was performed and hub genes from the modules most strongly associated with the clustering groups were extracted. We then constructed a prognostic prediction model using Least Absolute Shrinkage and Selection Operator and multiCox regression analysis. The predictive accuracy of the model was evaluated and robustness were confirmed in a separate validation cohort. The gene and pathway dysregulation for the two risk groups was analyzed. Ultimately, an investigation was conducted into the association between the risk model and various immunological features, in terms of antitumor immunotherapy, the tumor microenvironment, and immune checkpoints. This study provides an in-depth investigation into the potential mechanisms underlying MM development and offers new directions to improve therapeutic approaches and enhance patient outcomes.https://www.frontiersin.org/articles/10.3389/fimmu.2025.1549742/fullmultiple myelomaplasma cellssingle-cell sequencingweighted gene coexpression network analysistumor microenvironment |
| spellingShingle | Shuang Qu Zhihai Zheng Xiaoling Guo Jiaqi Mei Sicong Jiang Biyun Chen Comprehensive analysis of plasma cell heterogeneity and immune interactions in multiple myeloma Frontiers in Immunology multiple myeloma plasma cells single-cell sequencing weighted gene coexpression network analysis tumor microenvironment |
| title | Comprehensive analysis of plasma cell heterogeneity and immune interactions in multiple myeloma |
| title_full | Comprehensive analysis of plasma cell heterogeneity and immune interactions in multiple myeloma |
| title_fullStr | Comprehensive analysis of plasma cell heterogeneity and immune interactions in multiple myeloma |
| title_full_unstemmed | Comprehensive analysis of plasma cell heterogeneity and immune interactions in multiple myeloma |
| title_short | Comprehensive analysis of plasma cell heterogeneity and immune interactions in multiple myeloma |
| title_sort | comprehensive analysis of plasma cell heterogeneity and immune interactions in multiple myeloma |
| topic | multiple myeloma plasma cells single-cell sequencing weighted gene coexpression network analysis tumor microenvironment |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1549742/full |
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