ArticleFrontiers in immunology2024
Mitochondria-associated programmed cell death: elucidating prognostic biomarkers, immune checkpoints, and therapeutic avenues in multiple myeloma.
Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Machine learning-based prognostic signature integrating mitochondrial function and programmed cell death patterns in pancreatic adenocarcinoma.Scientific reports · 2026Article
- Comprehensive bioinformatics analysis and clinical validation of PPP1R13L in rectal adenocarcinoma.BMC cancer · 2026Article
- Activation of the cGAS-STING pathway by clofoctol through mitochondrial damage in triple-negative breast cancer.Journal of translational medicine · 2025Article
- Lactylation-related multigene signature in multiple myeloma: integrated prognostic stratification, immune landscape profiling, and therapeutic guidance.Immunologic research · 2025Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Multiple myeloma (MM) is a hematological malignancy characterized by the abnormal proliferation of plasma cells. Mitochondrial dysfunction and dysregulated programmed cell death (PCD) pathways have been implicated in MM pathogenesis. However, the precise roles of mitochondria-related genes (MRGs) and PCD-related genes (PCDRGs) in MM prognosis remain unclear. Methods: Transcriptomic data from MM patients and healthy controls were analyzed to identify differentially expressed genes (DEGs). Candidate genes were selected by intersecting DEGs with curated lists of MRGs and PCDRGs. Univariate Cox, least absolute shrinkage and selection operator (LASSO), multivariate Cox, and stepwise regression analyses identified prognostic genes among the candidates. A risk model was constructed from these genes, and patients were stratified into high- and low-risk groups for survival analysis. Independent prognostic factors were incorporated into a nomogram to predict MM patient outcomes. Model performance was evaluated using calibration curves, receiver operating characteristic (ROC) analysis, and decision curve analysis (DCA). Finally, associations between prognostic genes and immune cell infiltration/drug responses were explored. Results: 2,192 DEGs were detected between MM and control samples. 30 candidate genes were identified at the intersection of DEGs, 1,136 MRGs, and 1,548 PCDRGs. Conclusion: Seven genes (
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