Leveraging a disulfidptosis-based signature to characterize heterogeneity and optimize treatment in multiple myeloma
BackgroundDisulfidptosis is an emerging type of programmed cell death related to ROS accumulation and aberrant disulfide bond formation. Multiple myeloma (MM) is the second most prevalent hematologic malignancy characterized by a high synthesis rate of disulfide bond-rich proteins and chronic oxidat...
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Frontiers Media S.A.
2025-04-01
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| author | Bingxin Zhang Dong Zheng Shuxia Zhu Xinyi Zhang Quanqiang Wang Zhili Lin Ziwei Zheng Shujuan Zhou Zixing Chen Sisi Zheng Enqing Lan Luning Cui Hansen Ying Yu Zhang Xuanru Lin Qiang Zhuang Honglan Qian Xudong Hu Yan Zhuang Qianying Zhang Zhouxiang Jin Songfu Jiang Yongyong Ma Yongyong Ma Yongyong Ma |
| author_facet | Bingxin Zhang Dong Zheng Shuxia Zhu Xinyi Zhang Quanqiang Wang Zhili Lin Ziwei Zheng Shujuan Zhou Zixing Chen Sisi Zheng Enqing Lan Luning Cui Hansen Ying Yu Zhang Xuanru Lin Qiang Zhuang Honglan Qian Xudong Hu Yan Zhuang Qianying Zhang Zhouxiang Jin Songfu Jiang Yongyong Ma Yongyong Ma Yongyong Ma |
| author_sort | Bingxin Zhang |
| collection | DOAJ |
| description | BackgroundDisulfidptosis is an emerging type of programmed cell death related to ROS accumulation and aberrant disulfide bond formation. Multiple myeloma (MM) is the second most prevalent hematologic malignancy characterized by a high synthesis rate of disulfide bond-rich proteins and chronic oxidative stress. However, the relationship between disulfidptosis and MM is still unclear.MethodsUsing the non-negative matrix factorization and lasso algorithm, we constructed the disulfidptosis-associated subtypes and the prognostic model on the GEO dataset. We further explored genetic mutation mapping, protein-protein interactions, functional enrichment, drug sensitivity, drug prediction, and immune infiltration analysis among subtypes and risk subgroups. To improve the clinical benefits, we combined risk scores and clinical metrics to build a nomogram. Finally, in vitro experiments examined the expression patterns of disulfidptosis-related genes (DRGs) in MM.ResultsBy cluster analysis, we obtained three subtypes with C2 having a worse prognosis than C3. Consistently, C2 exhibited significantly lower sensitivity to doxorubicin and lenalidomide, as well as a higher propensity for T-cell depletion and a non-responsive state to immunotherapy. Similarly, in the subsequent prognostic model, the high-scoring group had a worse prognosis and a higher probability of T-cell dysfunction, immunotherapy resistance, and cancer cell self-renewal. DRGs and risk genes were widely mutated in cancers. Subtypes and risk subgroups differed in ROS metabolism and the p53 signaling pathway. We further identified eight genes differentially expressed in risk subgroups as drug targets against MM. Then 27 drugs targeting the high-risk group were predicted. Based on the DRGs and risk genes, we constructed the miRNA and TF regulatory networks. The nomogram of combined ISS, age, and risk score showed good predictive performance. qRT-PCR of cell lines and clinical specimens provided further support for prognostic modeling.ConclusionOur research reveals the prognostic value of disulfidptosis in MM and provides new perspectives for identifying heterogeneity and therapeutic targets. |
| format | Article |
| id | doaj-art-4b131f689d1d4ba7baacfe88531fe68e |
| institution | DOAJ |
| 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-4b131f689d1d4ba7baacfe88531fe68e2025-08-20T03:10:24ZengFrontiers Media S.A.Frontiers in Immunology1664-32242025-04-011610.3389/fimmu.2025.15593171559317Leveraging a disulfidptosis-based signature to characterize heterogeneity and optimize treatment in multiple myelomaBingxin Zhang0Dong Zheng1Shuxia Zhu2Xinyi Zhang3Quanqiang Wang4Zhili Lin5Ziwei Zheng6Shujuan Zhou7Zixing Chen8Sisi Zheng9Enqing Lan10Luning Cui11Hansen Ying12Yu Zhang13Xuanru Lin14Qiang Zhuang15Honglan Qian16Xudong Hu17Yan Zhuang18Qianying Zhang19Zhouxiang Jin20Songfu Jiang21Yongyong Ma22Yongyong Ma23Yongyong Ma24Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Hepatobiliary Surgery, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Hepatobiliary Surgery, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Hepatobiliary Surgery, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Hepatobiliary Surgery, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaKey Laboratory of Intelligent Treatment and Life Support for Critical Diseases of Zhejiang, Wenzhou, Zhejiang, ChinaZhejiang Engineering Research Center for Hospital Emergency and Process Digitization, Wenzhou, Zhejiang, ChinaBackgroundDisulfidptosis is an emerging type of programmed cell death related to ROS accumulation and aberrant disulfide bond formation. Multiple myeloma (MM) is the second most prevalent hematologic malignancy characterized by a high synthesis rate of disulfide bond-rich proteins and chronic oxidative stress. However, the relationship between disulfidptosis and MM is still unclear.MethodsUsing the non-negative matrix factorization and lasso algorithm, we constructed the disulfidptosis-associated subtypes and the prognostic model on the GEO dataset. We further explored genetic mutation mapping, protein-protein interactions, functional enrichment, drug sensitivity, drug prediction, and immune infiltration analysis among subtypes and risk subgroups. To improve the clinical benefits, we combined risk scores and clinical metrics to build a nomogram. Finally, in vitro experiments examined the expression patterns of disulfidptosis-related genes (DRGs) in MM.ResultsBy cluster analysis, we obtained three subtypes with C2 having a worse prognosis than C3. Consistently, C2 exhibited significantly lower sensitivity to doxorubicin and lenalidomide, as well as a higher propensity for T-cell depletion and a non-responsive state to immunotherapy. Similarly, in the subsequent prognostic model, the high-scoring group had a worse prognosis and a higher probability of T-cell dysfunction, immunotherapy resistance, and cancer cell self-renewal. DRGs and risk genes were widely mutated in cancers. Subtypes and risk subgroups differed in ROS metabolism and the p53 signaling pathway. We further identified eight genes differentially expressed in risk subgroups as drug targets against MM. Then 27 drugs targeting the high-risk group were predicted. Based on the DRGs and risk genes, we constructed the miRNA and TF regulatory networks. The nomogram of combined ISS, age, and risk score showed good predictive performance. qRT-PCR of cell lines and clinical specimens provided further support for prognostic modeling.ConclusionOur research reveals the prognostic value of disulfidptosis in MM and provides new perspectives for identifying heterogeneity and therapeutic targets.https://www.frontiersin.org/articles/10.3389/fimmu.2025.1559317/fullmultiple myelomadisulfidptosisprognostic gene signaturetumor microenvironmentoxidative stressimmunotherapy |
| spellingShingle | Bingxin Zhang Dong Zheng Shuxia Zhu Xinyi Zhang Quanqiang Wang Zhili Lin Ziwei Zheng Shujuan Zhou Zixing Chen Sisi Zheng Enqing Lan Luning Cui Hansen Ying Yu Zhang Xuanru Lin Qiang Zhuang Honglan Qian Xudong Hu Yan Zhuang Qianying Zhang Zhouxiang Jin Songfu Jiang Yongyong Ma Yongyong Ma Yongyong Ma Leveraging a disulfidptosis-based signature to characterize heterogeneity and optimize treatment in multiple myeloma Frontiers in Immunology multiple myeloma disulfidptosis prognostic gene signature tumor microenvironment oxidative stress immunotherapy |
| title | Leveraging a disulfidptosis-based signature to characterize heterogeneity and optimize treatment in multiple myeloma |
| title_full | Leveraging a disulfidptosis-based signature to characterize heterogeneity and optimize treatment in multiple myeloma |
| title_fullStr | Leveraging a disulfidptosis-based signature to characterize heterogeneity and optimize treatment in multiple myeloma |
| title_full_unstemmed | Leveraging a disulfidptosis-based signature to characterize heterogeneity and optimize treatment in multiple myeloma |
| title_short | Leveraging a disulfidptosis-based signature to characterize heterogeneity and optimize treatment in multiple myeloma |
| title_sort | leveraging a disulfidptosis based signature to characterize heterogeneity and optimize treatment in multiple myeloma |
| topic | multiple myeloma disulfidptosis prognostic gene signature tumor microenvironment oxidative stress immunotherapy |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1559317/full |
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