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Updated: May 5, 2026

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Techniques to Induce and Quantify Cellular Senescence
Published on: May 1, 2017
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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
Summary
Cellular senescence is a complex process. Diverse stressors induce shared pathway changes but maintain gene-level differences, offering new ways to identify senescence biomarkers.
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.
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