Critical pathways in cellular senescence and immortalization revealed by gene expression profiling
Open accessAbstract
Bypassing cellular senescence and becoming immortal is a prerequisite step in the tumorigenic transformation of a cell. It has long been known that loss of a key tumor suppressor gene, such as p53, is necessary, but not sufficient, for spontaneous cellular immortalization. Therefore, there must be additional mutations and/or epigenetic alterations required for immortalization to occur. Early work on these processes included somatic cell genetic studies to estimate the number of senescence genes, and microcell-mediated transfer of chromosomes into immortalized cells to identify putative senescence-inducing genetic loci. These principal studies laid the foundation for the field of senescence/immortalization, but were labor intensive and the results were somewhat limited. The advent of gene expression profiling and bioinformatics analysis greatly facilitated the identification of genes and pathways that regulate cellular senescence/immortalization. In this review, we present the findings of several gene expression profiling studies and supporting functional data, where available. We identified universal genes regulating senescence/immortalization and found that the key regulator genes represented six pathways: the cell cycle pRB/p53, cytoskeletal, interferon-related, insulin growth factor-related, MAP kinase and oxidative stress pathway. The identification of the genes and pathways regulating senescence/immortalization could provide novel molecular targets for the treatment and/or prevention of cancer.
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SenMayo performed better than six existing senescence/SASP gene panels.
“Using publicly available RNA-seq data, we demonstrated applicability across tissues and species and also found that SenMayo performed better than six existing senescence/SASP gene panels14,42–46.”
From A new gene set identifies senescent cells and predicts senescence-associated pathways across tissues (2022) · cites this paper as [45]
All three PS hepatocyte groups demonstrated increased activity of SenMayo, Fridman senescence genes, and TP53 target pathways.
“All three groups demonstrated increased activity of SenMayo,40 Fridman senescence genes,42 and TP53 target pathways (Figure 2D).”
From Cellular senescence in human liver under normal aging and cancer (2026) · cites this paper as [42]
A senescence transcriptional signature is significantly upregulated during paracrine senescence.
“a transcriptional signature associated with senescence 18 was significantly upregulated during paracrine senescence (Fig 3d).”
From A complex secretory program orchestrated by the inflammasome controls paracrine senescence (2013) · cites this paper as [18]
SenMayo consistently outperformed six additional senescence/SASP gene sets in identifying senescent cells with aging across tissues and species and in demonstrating responses to senescent cell clearance.
“SenMayo consistently outperformed these gene sets (based on normalized enrichment scores [NES] and p values) both in the ability to identify senescent cells with aging across tissues and species and in demonstrating responses to senescent cell clearance.”
From A new gene set identifies senescent cells and predicts senescence-associated pathways across tissues (2022) · cites this paper as [45]
The Genomic approaches and Replicative senescence sections discuss senescence genes, profiling, and cell markers, but do not evaluate SenMayo. Searches for SenMayo, comparative gene-set performance, and senescent-cell clearance found no passage addressing the claimed results. Page numbers were not available in our copy. (LLM, conf=0.78)
Experimental — accuracy not yet measuredIn mouse retinas with proliferative retinopathies, certain cell types including astrocytes, pericytes, endothelial cells, and glial cells showed expression of senescence-related genes from two published senescence-related gene-sets.
“Another study leveraged gene set variation analysis (GSVA) to analyze single-cell RNA-seq datasets of mouse retinas with proliferative retinopathies; it revealed that certain cell types, including astrocytes, pericytes, endothelial cells, and glial cells, showed expression of senescence-related genes from two published senescence-related gene-sets [39,40].”
From The heterogeneity of cellular senescence: insights at the single-cell level (2023) · cites this paper as [39]
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- Authors
- Fridman, A. L., & Tainsky, M. A.
- Affiliations
- Wayne State University (US)
- Corresponding author
- Tainsky, M A
- ORCID
- Tainsky, M A
- Venue
- Oncogene
- Published
- 2008-08-18
- Volume
- 27
- Issue
- 46
- Pages
- 5975-5987
- ISSN
- 0950-9232 (ISSN-L)
- 1476-5594
- PMC
- PMC3843241
- OpenAlex
- W1984936995
- Cited by
- 385
- References
- 132
- Citations by year
- 2026: 42 · 2025: 54 · 2024: 48 · 2023: 33 · 2022: 25 · 2021: 25 · 2020: 9 · 2019: 14 · 2018: 5 · 2017: 10 · 2016: 14 · 2015: 11 · 2014: 11 · 2013: 18 · 2012: 8
- FWCI
- 2.06
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Oncogene (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Barbara Ann Karmanos Cancer Institute
- National Cancer Institute (P30CA022453)
- Topics
- Health Sciences › Medicine › Physiology › Telomeres, Telomerase, and Senescence
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Health Sciences › Medicine › Oncology › Cancer-related Molecular Pathways
- Keywords
- cellular senescence, cell immortalization, tumorigenic transformation, senescence genes, p53, retinoblastoma protein, cell cycle regulation, cytoskeletal genes, interferon pathway, MAPK signaling, oxidative stress, gene expression profiling, cancer prevention, cancer therapy targets
- MeSH terms
- Aging, Animals, Cell Division, Cell Transformation, Neoplastic, Epithelial Cells, Fibroblasts, Humans, Longevity, Models, Biological, Precancerous Conditions, Signal Transduction, Cellular Senescence, CpG Islands, DNA Methylation, Gene Expression Profiling
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