ORIGINAL RESEARCH article
Front. Immunol.
Sec. Cancer Immunity and Immunotherapy
This article is part of the Research TopicMolecular Pathways and Signaling Molecules in Cancer Therapy: Advances and InnovationsView all 15 articles
Prognostic and Therapeutic Implications of Disulfidptosis-Related Genes in Multiple Myeloma
Provisionally accepted
Yunke Zang1Peipei Zhou1Haotian Dong1Jingfei Wang1Rongxuan Cao2Guimao Yang3Qianqian Wu3Yanhua Sun2*
Yanli Sun1*- 1School of Medical Laboratory, Shandong Second Medical University, Weifang, China
- 2Department of Hematology, Weifang People's Hospital, Weifang, China
- 3Department of Laboratory Medicine, Affiliated Hospital of Shandong Second Medical University, Weifang, China
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Background: Multiple myeloma (MM), a malignancy of plasma cells in the bone marrow, urgently requires novel prognostic biomarkers. However, the prognostic significance of disulfidptosis-related genes and their association with treatment response in MM remain unclear. Methods: Transcriptomic data from MM samples were obtained from the Gene Expression Omnibus (GEO) database. A disulfidptosis-related prognostic model was constructed using LASSO-Cox regression analysis. The performance of the model was evaluated, and its clinical relevance to treatment response was subsequently assessed. Finally, the expression of the identified genes was validated by qRT-PCR and Western blotting. Results: Unsupervised cluster analysis identified a total of 121 differentially expressed genes. LASSO-Cox regression subsequently revealed a nine-gene prognostic signature comprising TPST2, HIF1A, KIF21B, MCPH1, MAST4, ANXA2, ALG14, PQLC3, and RANGAP1, which were used to establish and validate a robust risk stratification model. Partial validation demonstrated that ALG14, MCPH1, and PQLC3 were significantly downregulated, whereas TPST2 was markedly upregulated in MM cells. Conclusion: We established and validated a novel disulfidptosis-related prognostic model for MM, providing a potential biomarker for risk stratification and guidance for personalized therapeutic decisions.
Keywords: disulfidptosis, Multiple Myeloma, Prognostic signature, gene, riskstratification model
Received: 23 Jun 2025; Accepted: 14 Nov 2025.
Copyright: © 2025 Zang, Zhou, Dong, Wang, Cao, Yang, Wu, Sun and Sun. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Yanhua Sun, sunyh1207@163.com
Yanli Sun, zbxzhg320@163.com
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