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Cited by 94Telomeres, Telomerase, and SenescenceGenetics, Aging, and Longevity in Model OrganismsSingle-cell and spatial transcriptomics

Cellular senescence in cancer: clinical detection and prognostic implications

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Domen, Andreas, Deben, Christophe, Verswyvel, Jasper, Flieswasser, Tal, Prenen, Hans, Peeters, Marc, Lardon, Filip, Wouters, An·2022·Journal of Experimental & Clinical Cancer Research
DOI 10.1186/s13046-022-02555-3PMC PMC9793681
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Abstract

Cellular senescence is a state of stable cell-cycle arrest with secretory features in response to cellular stress. Historically, it has been considered as an endogenous evolutionary homeostatic mechanism to eliminate damaged cells, including damaged cells which are at risk of malignant transformation, thereby protecting against cancer. However, accumulation of senescent cells can cause long-term detrimental effects, mainly through the senescence-associated secretory phenotype, and paradoxically contribute to age-related diseases including cancer. Besides its role as tumor suppressor, cellular senescence is increasingly being recognized as an in vivo response in cancer patients to various anticancer therapies. Its role in cancer is ambiguous and even controversial, and senescence has recently been promoted as an emerging hallmark of cancer because of its hallmark-promoting capabilities. In addition, the prognostic implications of cellular senescence have been underappreciated due to the challenging detection and sparse in and ex vivo evidence of cellular senescence in cancer patients, which is only now catching up. In this review, we highlight the approaches and current challenges of in and ex vivo detection of cellular senescence in cancer patients, and we discuss the prognostic implications of cellular senescence based on in and ex vivo evidence in cancer patients.

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  • Over the past decade, senescent cells have been shown to promote tumor growth and malignancy through a variety of mechanisms under certain circumstances.

    “However, paradoxically, over the past decade, senescent cells have been shown to promote tumor growth and malignancy through a variety of mechanisms under certain circumstances.229–231”

    From Drug repurposing for cancer therapy (2024) · cites this paper as [230]

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Authors
Domen, A., Deben, C., Verswyvel, J., Flieswasser, T., Prenen, H., Peeters, M., Lardon, F., & Wouters, A.
Affiliations
University of Antwerp (BE)
Corresponding author
Domen, Andreas
ORCID
Venue
Journal of Experimental & Clinical Cancer Research
Publisher
Springer Science and Business Media LLC
Published
2022-12-27
Volume
41
Issue
1
Pages
360-360
ISSN
  • 0392-9078 (ISSN-L)
  • 1756-9966
DOI
10.1186/s13046-022-02555-3
PMC
PMC9793681
OpenAlex
W4313250083
Cited by
94
References
279
Citations by year
2026: 12 · 2025: 37 · 2024: 33 · 2023: 11 · 2022: 1
FWCI
2.82
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of Experimental & Clinical Cancer Research (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
Universiteit Antwerpen (University Research Fund (BOF) of the University of Antwerp, Antwerp, Belgium (FFB180188 to AD))
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, cancer, senescence-associated secretory phenotype, prognostic factors, tumor suppressor, age-related diseases, cancer hallmarks
MeSH terms
Cell Transformation, Neoplastic, Humans, Neoplasms, Prognosis, Cellular Senescence, Cell Cycle Checkpoints

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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