Bioinformatics analysis of intrinsic drivers of immune dysregulation in multiple myeloma to elucidate immune phenotypes and discover prognostic gene signatures
Abstract Multiple myeloma (MM) progression is driven by immune dysregulation within the tumor microenvironment (TME). However, myeloma-intrinsic mechanisms underlying immune dysfunction remain poorly defined, and current immunotherapies show limited efficacy. Using RNA-seq data from 859 MM patients...
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Nature Portfolio
2025-05-01
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| Online Access: | https://doi.org/10.1038/s41598-025-00074-7 |
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| author | Chuan-Feng Fang Yan Li Chun Yang Hua Fang Chen Li |
| author_facet | Chuan-Feng Fang Yan Li Chun Yang Hua Fang Chen Li |
| author_sort | Chuan-Feng Fang |
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| description | Abstract Multiple myeloma (MM) progression is driven by immune dysregulation within the tumor microenvironment (TME). However, myeloma-intrinsic mechanisms underlying immune dysfunction remain poorly defined, and current immunotherapies show limited efficacy. Using RNA-seq data from 859 MM patients (MMRF-CoMMpass), we integrated xCELL, CIBERSORT, and ESTIMATE algorithms to deconvolute immune-stromal dynamics. Consensus clustering identified immune subtypes, followed by differential gene analysis and LASSO-Cox regression to construct a prognostic model validated in an independent cohort (GSE19784, N = 328). Immune Subtype Classification: Two subgroups emerged: Multiple myeloma-associated immune-related cluster 1 (N = 482): Immune-dysfunctional TME with Th2 cell enrichment, preadipocyte accumulation, and CXCL family suppression, linked to poor survival (P < 0.001). Multiple myeloma-associated immune-related cluster 2 (N = 377): Immune-active TME with cytotoxic CD8 + T/NK cell infiltration and favorable outcomes. Prognostic Gene Signature: Ten immune-related genes (UBE2T, E2F2, EXO1, SH2D2A, DRP2, WNT9A, SHROOM3, TMC8, CDCA7, and GPR132) predicted survival (The One-year AUC = 0.682 and The Over 5-years AUC = 0.714). We define a myeloma-intrinsic immune classification system and a 10-gene prognostic index, offering a framework for risk-stratified immunotherapy. Integration with flow cytometry could optimize precision treatment in MM. |
| format | Article |
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| spelling | doaj-art-31efe610b29242d6afc3346cc66fefd32025-08-20T01:49:48ZengNature PortfolioScientific Reports2045-23222025-05-0115111910.1038/s41598-025-00074-7Bioinformatics analysis of intrinsic drivers of immune dysregulation in multiple myeloma to elucidate immune phenotypes and discover prognostic gene signaturesChuan-Feng Fang0Yan Li1Chun Yang2Hua Fang3Chen Li4Department of Clinical Laboratory, The Fourth Affiliated Hospital of Harbin Medical UniversityDepartment of Anesthesia, The Fourth Affiliated Hospital of Harbin Medical UniversityDepartment of Clinical Laboratory, The Fourth Affiliated Hospital of Harbin Medical UniversityDepartment of Medical Oncology, Fuxing Hospital of the Capital Medical UniversityDepartment of Bioengineering, the Hebei Agriculture UniversityAbstract Multiple myeloma (MM) progression is driven by immune dysregulation within the tumor microenvironment (TME). However, myeloma-intrinsic mechanisms underlying immune dysfunction remain poorly defined, and current immunotherapies show limited efficacy. Using RNA-seq data from 859 MM patients (MMRF-CoMMpass), we integrated xCELL, CIBERSORT, and ESTIMATE algorithms to deconvolute immune-stromal dynamics. Consensus clustering identified immune subtypes, followed by differential gene analysis and LASSO-Cox regression to construct a prognostic model validated in an independent cohort (GSE19784, N = 328). Immune Subtype Classification: Two subgroups emerged: Multiple myeloma-associated immune-related cluster 1 (N = 482): Immune-dysfunctional TME with Th2 cell enrichment, preadipocyte accumulation, and CXCL family suppression, linked to poor survival (P < 0.001). Multiple myeloma-associated immune-related cluster 2 (N = 377): Immune-active TME with cytotoxic CD8 + T/NK cell infiltration and favorable outcomes. Prognostic Gene Signature: Ten immune-related genes (UBE2T, E2F2, EXO1, SH2D2A, DRP2, WNT9A, SHROOM3, TMC8, CDCA7, and GPR132) predicted survival (The One-year AUC = 0.682 and The Over 5-years AUC = 0.714). We define a myeloma-intrinsic immune classification system and a 10-gene prognostic index, offering a framework for risk-stratified immunotherapy. Integration with flow cytometry could optimize precision treatment in MM.https://doi.org/10.1038/s41598-025-00074-7Multiple myelomaImmune dysfunctionImmunosuppressTumor microenvironmentPrognostic signature |
| spellingShingle | Chuan-Feng Fang Yan Li Chun Yang Hua Fang Chen Li Bioinformatics analysis of intrinsic drivers of immune dysregulation in multiple myeloma to elucidate immune phenotypes and discover prognostic gene signatures Scientific Reports Multiple myeloma Immune dysfunction Immunosuppress Tumor microenvironment Prognostic signature |
| title | Bioinformatics analysis of intrinsic drivers of immune dysregulation in multiple myeloma to elucidate immune phenotypes and discover prognostic gene signatures |
| title_full | Bioinformatics analysis of intrinsic drivers of immune dysregulation in multiple myeloma to elucidate immune phenotypes and discover prognostic gene signatures |
| title_fullStr | Bioinformatics analysis of intrinsic drivers of immune dysregulation in multiple myeloma to elucidate immune phenotypes and discover prognostic gene signatures |
| title_full_unstemmed | Bioinformatics analysis of intrinsic drivers of immune dysregulation in multiple myeloma to elucidate immune phenotypes and discover prognostic gene signatures |
| title_short | Bioinformatics analysis of intrinsic drivers of immune dysregulation in multiple myeloma to elucidate immune phenotypes and discover prognostic gene signatures |
| title_sort | bioinformatics analysis of intrinsic drivers of immune dysregulation in multiple myeloma to elucidate immune phenotypes and discover prognostic gene signatures |
| topic | Multiple myeloma Immune dysfunction Immunosuppress Tumor microenvironment Prognostic signature |
| url | https://doi.org/10.1038/s41598-025-00074-7 |
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