Abstract
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.