Biomarkers to identify and isolate senescent cells
Open accessAbstract
Aging is the main risk factor for many degenerative diseases and declining health. Senescent cells are part of the underlying mechanism for time-dependent tissue dysfunction. These cells can negatively affect neighbouring cells through an altered secretory phenotype: the senescence-associated secretory phenotype (SASP). The SASP induces senescence in healthy cells, promotes tumour formation and progression, and contributes to other age-related diseases such as atherosclerosis, immune-senescence and neurodegeneration. Removal of senescent cells was recently demonstrated to delay age-related degeneration and extend lifespan. To better understand cell aging and to reap the benefits of senescent cell removal, it is necessary to have a reliable biomarker to identify these cells. Following an introduction to cellular senescence, we discuss several classes of biomarkers in the context of their utility in identifying and/or removing senescent cells from tissues. Although senescence can be induced by a variety of stimuli, senescent cells share some characteristics that enable their identification both in vitro and in vivo. Nevertheless, it may prove difficult to identify a single biomarker capable of distinguishing senescence in all cell types. Therefore, this will not be a comprehensive review of all senescence biomarkers but rather an outlook on technologies and markers that are most suitable to identify and isolate senescent cells.
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No one marker alone is sufficient to identify senescence; most researchers use a panel of biomarkers, such as senescence-associated β-galactosidase, p21, and p16INK4A, combined with a marker of cellular proliferation.
“No one marker alone is sufficient to identify senescence and most researchers use a panel of biomarkers, such as senescence-associated β-galactosidase, p21, and p16INK4A, as well as a number of other biomarkers, such as heterochromatin and proliferation markers (Table 1) combined [24] with a marker of cellular proliferation (Ki-67, for instance).”
From Senescence and Cancer: A Review of Clinical Implications of Senescence and Senotherapies (2020) · cites this paper as [24]
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Senescence in Health and Disease
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Clearance of senescent decidual cells by uterine natural killer cells in cycling human endometrium
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“No one marker alone is sufficient to identify senescence and most researchers use a panel of biomarkers, such as senescence-associated β-galactosidase, p21, and p16INK4A, as well as a number of other biomarkers, such as heterochromatin and proliferation markers (Table 1) combined [24] with a marker of cellular prolife…”
BackgroundNuclear morphology is a deep learning biomarker of cellular senescence
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- Authors
- Matjusaitis, M., Chin, G., Sarnoski, E. A., & Stolzing, A.
- Affiliations
- University of Edinburgh (GB)
- Yale University (US)
- Loughborough University (GB)
- Corresponding author
- Stolzing, Alexandra
- Venue
- Ageing Research Reviews
- Publisher
- Elsevier BV
- Published
- 2016-08
- Volume
- 29
- Pages
- 1-12
- ISSN
- 1568-1637 (ISSN-L)
- OpenAlex
- W2397706209
- Cited by
- 144
- References
- 177
- Citations by year
- 2026: 8 · 2025: 8 · 2024: 9 · 2023: 7 · 2022: 18 · 2021: 24 · 2020: 24 · 2019: 22 · 2018: 9 · 2017: 12 · 2016: 3
- FWCI
- 1.80
- Type
- journal article
- Language
- en
- Open access
- green
- dspace.lboro.ac.uk
- Licence
- cc-by-nc-nd
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- Locations
- Ageing Research Reviews (publishedVersion)
- PubMed (publishedVersion)
- Loughborough University Institutional Repository (Loughborough University) (submittedVersion, cc-by-nc-nd)
- Loughborough University Research Repository (Loughborough University) (submittedVersion, cc-by-nc-nd)
- Funders
- Bundesministerium für Bildung und Forschung (BMBF1315883)
- Topics
- Health Sciences › Medicine › Physiology › Telomeres, Telomerase, and Senescence
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Keywords
- cellular senescence, senescence-associated secretory phenotype, senolytics, senolytic therapy, aging, age-related diseases, tissue dysfunction, immunosenescence, neurodegeneration, atherosclerosis
- MeSH terms
- Aging, Animals, Cell Separation, Humans, Neoplasms, Phenotype, Biomarkers, Cellular Senescence, Atherosclerosis, Cell- and Tissue-Based Therapy
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