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Publications

Journal Article Ppublish

PubMed: 40133591 DOI: 10.1007/s11357-025-01622-9

Prognostic impact of a senescence gene signature in multiple myeloma.

Geroscience 47(3):5025-5037

Authors: Andrea Lehoczki, Otilia Menyhart, Hajnalka Andrikovics, Monika Fekete, Csaba Kiss, Gabor Mikala, Zoltan Ungvari, Balázs Győrffy

Affiliations

  • Doctoral College, Health Sciences Division, Semmelweis University, Budapest, Hungary.
  • Department of Bioinformatics, Semmelweis University, 1094, Budapest, Hungary.
  • Department of Bioinformatics, Semmelweis University, 1094, Budapest, Hungary.
  • Cancer Biomarker Research Group, Institute of Molecular Life Sciences, Hungarian Research Network, Magyar Tudósok Körútja 2, 1117, Budapest, Hungary.
  • National Laboratory for Drug Research and Development, Magyar Tudósok Körútja. 2. 1117, Budapest, Hungary.
  • Healthy Aging Program, Institute of Preventive Medicine and Public Health, Semmelweis University, Budapest, Hungary.
  • Laboratory of Molecular Genetics, Central Hospital of Southern Pest, National Institute for Hematology and Infectious Diseases, Budapest, Hungary.
  • Doctoral College, Health Sciences Division, Semmelweis University, Budapest, Hungary.
  • Department of Hematology and Stem Cell Transplantation, Central Hospital of Southern Pest, National Institute for Hematology and Infectious Diseases, Budapest, Hungary.
  • Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
  • Stephenson Cancer Center, University of Oklahoma, Oklahoma City, OK, USA.
  • Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
  • Department of Health Promotion Sciences, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
  • International Training Program in Geroscience, Doctoral College, Health Sciences Division/Institute of Preventive Medicine and Public Health, Semmelweis University, Budapest, Hungary.
  • Department of Biophysics, Medical School, University of Pecs, Pecs, 7624, Hungary.

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.

MeSH

Genes, Aging, Aged, Multiple Myeloma