Leveraging a disulfidptosis-based signature to characterize heterogeneity and optimize treatment in multiple myeloma DOI Creative Commons
Bingxin Zhang, Dong Zheng,

Shuxia Zhu

et al.

Frontiers in Immunology, Journal Year: 2025, Volume and Issue: 16

Published: April 16, 2025

Background Disulfidptosis is an emerging type of programmed cell death related to ROS accumulation and aberrant disulfide bond formation. Multiple myeloma (MM) the second most prevalent hematologic malignancy characterized by a high synthesis rate bond-rich proteins chronic oxidative stress. However, relationship between disulfidptosis MM still unclear. Methods Using non-negative matrix factorization lasso algorithm, we constructed disulfidptosis-associated subtypes prognostic model on GEO dataset. We further explored genetic mutation mapping, protein-protein interactions, functional enrichment, drug sensitivity, prediction, immune infiltration analysis among risk subgroups. To improve clinical benefits, combined scores metrics build nomogram. Finally, in vitro experiments examined expression patterns disulfidptosis-related genes (DRGs) MM. Results By cluster analysis, obtained three with C2 having worse prognosis than C3. Consistently, exhibited significantly lower sensitivity doxorubicin lenalidomide, as well higher propensity for T-cell depletion non-responsive state immunotherapy. Similarly, subsequent model, high-scoring group had probability dysfunction, immunotherapy resistance, cancer self-renewal. DRGs were widely mutated cancers. Subtypes subgroups differed metabolism p53 signaling pathway. identified eight differentially expressed targets against Then 27 drugs targeting high-risk predicted. Based genes, miRNA TF regulatory networks. The nomogram ISS, age, score showed good predictive performance. qRT-PCR lines specimens provided support modeling. Conclusion Our research reveals value provides new perspectives identifying heterogeneity therapeutic targets.

Language: Английский

Leveraging a disulfidptosis-based signature to characterize heterogeneity and optimize treatment in multiple myeloma DOI Creative Commons
Bingxin Zhang, Dong Zheng,

Shuxia Zhu

et al.

Frontiers in Immunology, Journal Year: 2025, Volume and Issue: 16

Published: April 16, 2025

Background Disulfidptosis is an emerging type of programmed cell death related to ROS accumulation and aberrant disulfide bond formation. Multiple myeloma (MM) the second most prevalent hematologic malignancy characterized by a high synthesis rate bond-rich proteins chronic oxidative stress. However, relationship between disulfidptosis MM still unclear. Methods Using non-negative matrix factorization lasso algorithm, we constructed disulfidptosis-associated subtypes prognostic model on GEO dataset. We further explored genetic mutation mapping, protein-protein interactions, functional enrichment, drug sensitivity, prediction, immune infiltration analysis among risk subgroups. To improve clinical benefits, combined scores metrics build nomogram. Finally, in vitro experiments examined expression patterns disulfidptosis-related genes (DRGs) MM. Results By cluster analysis, obtained three with C2 having worse prognosis than C3. Consistently, exhibited significantly lower sensitivity doxorubicin lenalidomide, as well higher propensity for T-cell depletion non-responsive state immunotherapy. Similarly, subsequent model, high-scoring group had probability dysfunction, immunotherapy resistance, cancer self-renewal. DRGs were widely mutated cancers. Subtypes subgroups differed metabolism p53 signaling pathway. identified eight differentially expressed targets against Then 27 drugs targeting high-risk predicted. Based genes, miRNA TF regulatory networks. The nomogram ISS, age, score showed good predictive performance. qRT-PCR lines specimens provided support modeling. Conclusion Our research reveals value provides new perspectives identifying heterogeneity therapeutic targets.

Language: Английский

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