Comprehensive analysis of exosome-related gene signature in multiple myeloma prognosis and immune microenvironment evaluation
Abstract Multiple myeloma (MM) is a genetically complicated plasma cell malignancy characterized by malignant plasma cell proliferation and monoclonal immunoglobulin synthesis. As a disease that remains incurable, enhancing prognostic accuracy is of paramount importance. Tumor-derived exosomes (TDEs...
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2025-07-01
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| Series: | Cancer Immunology, Immunotherapy |
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| Online Access: | https://doi.org/10.1007/s00262-025-04097-x |
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| author | Dong Zheng Bingxin Zhang Quanqiang Wang Sisi Zheng Yibo Xia Ziwei Zheng Zhili Lin Shuxia Zhu Xinyi Zhang Luning Cui Hansen Ying Tianyu Zhang Shujuan Zhou Zixing Chen Enqing Lan Yu Zhang Xuanru Lin Jingjing Chen Honglan Qian Xudong Hu Yan Zhuang Zuoting Xie Xiangjing Zhou Zhouxiang Jin Songfu Jiang Yongyong Ma |
| author_facet | Dong Zheng Bingxin Zhang Quanqiang Wang Sisi Zheng Yibo Xia Ziwei Zheng Zhili Lin Shuxia Zhu Xinyi Zhang Luning Cui Hansen Ying Tianyu Zhang Shujuan Zhou Zixing Chen Enqing Lan Yu Zhang Xuanru Lin Jingjing Chen Honglan Qian Xudong Hu Yan Zhuang Zuoting Xie Xiangjing Zhou Zhouxiang Jin Songfu Jiang Yongyong Ma |
| author_sort | Dong Zheng |
| collection | DOAJ |
| description | Abstract Multiple myeloma (MM) is a genetically complicated plasma cell malignancy characterized by malignant plasma cell proliferation and monoclonal immunoglobulin synthesis. As a disease that remains incurable, enhancing prognostic accuracy is of paramount importance. Tumor-derived exosomes (TDEs) play key roles in modulating the tumor microenvironment, angiogenesis and immune system. Exosomes are involved in multiple processes contributing to cancer progression, including in MM. However, the connection between myeloma and exosome-related genes (ERGs) has not been explored. Therefore, we aim to establish a more accurate model to evaluate the prognosis of MM patients based on the exosome-related genes. This study established an ERG-based prognostic model for MM and investigated its association with the immune microenvironment. Using transcriptomic data from GSE136337 (training set) and GSE24080 (validation set), we identified six prognostic ERGs (BIRC5, LDHA, MRPS30, MRPL15, RPL26L1, and S1PR2) through Cox and LASSO regression analyses, constructing a risk-scoring model. The model demonstrated robust predictive performance for 3-year survival (AUC = 0.74 in training set; AUC = 0.69 in both validation sets). A nomogram integrating age, ISS stage, and risk score significantly improved prognostic accuracy (3-year survival AUC = 0.77). Functional enrichment analysis revealed that high-risk patients exhibited activation of oncogenic pathways, including cell cycle regulation and DNA replication (P < 0.01). Immune profiling identified an immunosuppressive microenvironment in the high-risk group, characterized by reduced CD8 + T cell infiltration (P = 0.004) and elevated TIDE scores (P = 0.012), indicating increased resistance to immunotherapy. TCGA database validation and in vitro experiments confirmed the critical role of these ERGs in tumor microenvironment remodeling. To our knowledge, this represents the first ERG-based prognostic system for MM, providing a biologically insightful and clinically applicable tool for personalized treatment strategies. |
| format | Article |
| id | doaj-art-9d20442acbc540e79f5fcaed406c2f1c |
| institution | Kabale University |
| issn | 1432-0851 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Springer |
| record_format | Article |
| series | Cancer Immunology, Immunotherapy |
| spelling | doaj-art-9d20442acbc540e79f5fcaed406c2f1c2025-08-20T03:45:56ZengSpringerCancer Immunology, Immunotherapy1432-08512025-07-0174811910.1007/s00262-025-04097-xComprehensive analysis of exosome-related gene signature in multiple myeloma prognosis and immune microenvironment evaluationDong Zheng0Bingxin Zhang1Quanqiang Wang2Sisi Zheng3Yibo Xia4Ziwei Zheng5Zhili Lin6Shuxia Zhu7Xinyi Zhang8Luning Cui9Hansen Ying10Tianyu Zhang11Shujuan Zhou12Zixing Chen13Enqing Lan14Yu Zhang15Xuanru Lin16Jingjing Chen17Honglan Qian18Xudong Hu19Yan Zhuang20Zuoting Xie21Xiangjing Zhou22Zhouxiang Jin23Songfu Jiang24Yongyong Ma25Department of Hematology, The First Affiliated Hospital of Wenzhou Medical UniversityDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical UniversityDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical UniversityDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical UniversityDepartment of Medical Laboratory Technology, School of Laboratory Medicine and Life Science, Wenzhou Medical UniversityDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical UniversityDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical UniversityDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical UniversityDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical UniversityDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical UniversityDepartment of Hepatobiliary Surgery, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical UniversityDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical UniversityDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical UniversityDepartment of Hepatobiliary Surgery, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical UniversityDepartment of Hepatobiliary Surgery, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical UniversityDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical UniversityDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical UniversityDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical UniversityDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical UniversityDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical UniversityDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical UniversityDepartment of Blood Transfusion, The First Hospital, Wenzhou Medical CollegeDepartment of Blood Transfusion, The First Hospital, Wenzhou Medical CollegeDepartment of Hepatobiliary Surgery, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical UniversityDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical UniversityDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical UniversityAbstract Multiple myeloma (MM) is a genetically complicated plasma cell malignancy characterized by malignant plasma cell proliferation and monoclonal immunoglobulin synthesis. As a disease that remains incurable, enhancing prognostic accuracy is of paramount importance. Tumor-derived exosomes (TDEs) play key roles in modulating the tumor microenvironment, angiogenesis and immune system. Exosomes are involved in multiple processes contributing to cancer progression, including in MM. However, the connection between myeloma and exosome-related genes (ERGs) has not been explored. Therefore, we aim to establish a more accurate model to evaluate the prognosis of MM patients based on the exosome-related genes. This study established an ERG-based prognostic model for MM and investigated its association with the immune microenvironment. Using transcriptomic data from GSE136337 (training set) and GSE24080 (validation set), we identified six prognostic ERGs (BIRC5, LDHA, MRPS30, MRPL15, RPL26L1, and S1PR2) through Cox and LASSO regression analyses, constructing a risk-scoring model. The model demonstrated robust predictive performance for 3-year survival (AUC = 0.74 in training set; AUC = 0.69 in both validation sets). A nomogram integrating age, ISS stage, and risk score significantly improved prognostic accuracy (3-year survival AUC = 0.77). Functional enrichment analysis revealed that high-risk patients exhibited activation of oncogenic pathways, including cell cycle regulation and DNA replication (P < 0.01). Immune profiling identified an immunosuppressive microenvironment in the high-risk group, characterized by reduced CD8 + T cell infiltration (P = 0.004) and elevated TIDE scores (P = 0.012), indicating increased resistance to immunotherapy. TCGA database validation and in vitro experiments confirmed the critical role of these ERGs in tumor microenvironment remodeling. To our knowledge, this represents the first ERG-based prognostic system for MM, providing a biologically insightful and clinically applicable tool for personalized treatment strategies.https://doi.org/10.1007/s00262-025-04097-xMultiple myelomaExosomePrognosisImmune microenvironment |
| spellingShingle | Dong Zheng Bingxin Zhang Quanqiang Wang Sisi Zheng Yibo Xia Ziwei Zheng Zhili Lin Shuxia Zhu Xinyi Zhang Luning Cui Hansen Ying Tianyu Zhang Shujuan Zhou Zixing Chen Enqing Lan Yu Zhang Xuanru Lin Jingjing Chen Honglan Qian Xudong Hu Yan Zhuang Zuoting Xie Xiangjing Zhou Zhouxiang Jin Songfu Jiang Yongyong Ma Comprehensive analysis of exosome-related gene signature in multiple myeloma prognosis and immune microenvironment evaluation Cancer Immunology, Immunotherapy Multiple myeloma Exosome Prognosis Immune microenvironment |
| title | Comprehensive analysis of exosome-related gene signature in multiple myeloma prognosis and immune microenvironment evaluation |
| title_full | Comprehensive analysis of exosome-related gene signature in multiple myeloma prognosis and immune microenvironment evaluation |
| title_fullStr | Comprehensive analysis of exosome-related gene signature in multiple myeloma prognosis and immune microenvironment evaluation |
| title_full_unstemmed | Comprehensive analysis of exosome-related gene signature in multiple myeloma prognosis and immune microenvironment evaluation |
| title_short | Comprehensive analysis of exosome-related gene signature in multiple myeloma prognosis and immune microenvironment evaluation |
| title_sort | comprehensive analysis of exosome related gene signature in multiple myeloma prognosis and immune microenvironment evaluation |
| topic | Multiple myeloma Exosome Prognosis Immune microenvironment |
| url | https://doi.org/10.1007/s00262-025-04097-x |
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