ArticleGeroScience2025
Prognostic impact of a senescence gene signature in multiple myeloma.
Article in GeroScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- A Comparative Analysis of Multiple Myeloma Disease Burden in China and Globally From 1990 to 2023 and Future Trend Projections.Cancer medicine · 2026Article
- IDEAL-Age: an interpretable deep learning framework for single-cell resolution profiling of immunological aging.Genome biology · 2026Article
- Article
- Senescence-associated gene signatures predict survival in lung cancer: a multi-cohort analysis.GeroScience · 2026Article
- Cellular Senescence as a Risk Factor in Head and Neck Cancer-Diagnostic and Therapeutic Perspective.Cancers · 2025Review
- Subtype-specific genetic drivers of immune evasion in breast cancer.Immuno-oncology technology · 2025Article
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8 authors.
Funding
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Abstract
Multiple myeloma (MM), an incurable malignancy of plasma cells, is predominantly an age-related disease, with the majority of cases occurring in patients over the age of 60. Cellular senescence, a fundamental biological process underlying aging, has been increasingly recognized for its critical role in developing age-related malignancies. In this study, we aimed to investigate the prognostic significance of genes implicated in the molecular mechanisms of senescence within a large cohort of MM patients. Gene expression and clinical data from 1416 MM patients were obtained from four GEO datasets (GSE24080, GSE4204, GSE57317, and GSE9782) and integrated into a unified database. The raw data were processed using MAS5 normalization, scaling adjustments, and JetSet probe selection to ensure cross-platform comparability. A curated set of senescence-associated genes, the SenMayo gene signature, was employed for subsequent analyses. The final gene signature was computed as a weighted mean expression of 122 senescence-associated genes, with weights derived from univariate hazard ratios. Prognostic significance was evaluated using Cox regression, Kaplan-Meier survival analysis, and multivariate models incorporating clinical parameters such as gender, isotype, and molecular subtypes. False discovery rate (FDR) correction was applied to ensure the statistical robustness of findings. The weighted SenMayo gene signature strongly correlated with overall survival in MM patients (HR = 0.6, 95% CI = 0.47-0.76, p = 1.7e-05). The 75th percent probability of survival was reached at 36.1 months in the low-expression patient group, compared to 57 months in the high-expression group. Independent validation in datasets with sufficient patient numbers confirmed the prognostic value of the SenMayo signature (GSE4204: HR = 0.58, 95% CI = 0.39-0.88, p = 0.0089; GSE24080: HR = 0.61, 95% CI = 0.45-0.83, p = 0.0012; GSE57317: HR = 0.25, 95% CI = 0.08-0.77, p = 0.0095). Multivariate analyses further established the SenMayo signature as an independent prognostic factor, even when accounting for established clinical parameters such as sex and isotype. These findings underscore the robustness and independence of the SenMayo gene signature as a predictor of overall survival in multiple myeloma. This signature provides clinically valuable insights into the role of cellular senescence in disease progression.
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