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Updated: May 5, 2026

Techniques to Induce and Quantify Cellular Senescence
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A transcriptomic analysis reveals shared and inducer-specific expression patterns of cellular senescence.

Jacob E Bridge1,2, Chen Zheng1,3, Paul D Robbins1,3

  • 1Masonic Institute on the Biology of Aging and Metabolism, University of Minnesota, Twin Cities, Minneapolis, MN 55455, USA.

Biorxiv : the Preprint Server for Biology
|May 4, 2026
PubMed
Summary
This summary is machine-generated.

Cellular senescence is a complex process. Diverse stressors induce shared pathway changes but maintain gene-level differences, offering new ways to identify senescence biomarkers.

Keywords:
Cellular senescencegene expression heterogeneitypathway analysistranscriptomics

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Area of Science:

  • Cellular and Molecular Biology
  • Aging Research
  • Genomics

Background:

  • Cellular senescence is a state of irreversible cell cycle arrest.
  • Senescence can be triggered by various stressors like DNA damage and oxidative stress.
  • Identifying universal biomarkers for senescence remains a challenge.

Purpose of the Study:

  • To investigate whether different senescence-inducing stimuli converge on shared molecular processes or individual genes.
  • To analyze transcriptomic changes in human fibroblasts under various senescence-inducing conditions.
  • To understand the hierarchical organization of the senescent transcriptome.

Main Methods:

  • Transcriptomic profiling of human lung fibroblasts (IMR-90).
  • Induction of senescence via replicative exhaustion, bleomycin, hydrogen peroxide (H2O2), and ionizing radiation.
  • Analysis of global transcriptomic variation, individual gene overlap, and pathway enrichment.

Main Results:

  • Global transcriptomic variation aligned along a shared senescence progression axis across all inducers.
  • Limited overlap was observed at the individual gene level; responses were largely inducer-specific.
  • Pathway analysis revealed consistent enrichment of stress-related and pro-inflammatory pathways, with downregulation of proliferation pathways.

Conclusions:

  • Cellular senescence exhibits a hierarchical transcriptomic organization.
  • Diverse senescence inducers converge on shared pathway-level features, not just individual genes.
  • These findings support the development of more robust transcriptome-based senescence markers for aging and disease.