DNA Methylation Patterns Separate Senescence from Transformation Potential and Indicate Cancer Risk
Open accessAbstract
Overall shared DNA methylation patterns between senescence (Sen) and cancers have led to the model that tumor-promoting epigenetic patterns arise through senescence. We show that transformation-associated methylation changes arise stochastically and independently of programmatic changes during senescence. Promoter hypermethylation events in transformation involve primarily pro-survival and developmental genes, similarly modified in primary tumors. Senescence-associated hypermethylation mainly involves metabolic regulators and appears early in proliferating "near-senescent" cells, which can be immortalized but are refractory to transformation. Importantly, a subset of transformation-associated hypermethylated developmental genes exhibits highest methylation gains at all age-associated cancer risk states across tissue types. These epigenetic changes favoring cell self-renewal and survival, arising during tissue aging, are fundamentally important for stratifying cancer risk and concepts for cancer prevention.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Cells with oncogene-induced senescence show only limited methylation changes compared with cells that bypassed OIS, suggesting tumour-associated methylome changes may arise stochastically and independently of senescence.
“cells with OIS display only limited changes in methylation patterns compared with cells that have bypassed OIS, indicating that tumour-associated methy-lome changes may arise stochastically and independently of the senescence state65”
From Cellular senescence in ageing: from mechanisms to therapeutic opportunities (2021) · cites this paper as [65]
Cells undergoing oncogene-induced senescence fail to show such alterations in DNA methylation.
“Cells undergoing OIS fail to show such alterations in DNA methylation (Xie et al., 2018), reinforcing the diverse nature of epigenetic alterations during senescence.”
From Cellular Senescence: Defining a Path Forward (2019) · cites this paper as Xie et al., 2018
The DNA methylation profile of senescence somewhat resembles cancer- and aging-associated methylome patterns.
“Interestingly, this DNA methylation profile somewhat resembles the cancer- and aging-associated methylome patterns (Cruickshanks et al., 2013; Xie et al., 2018).”
From Cellular Senescence: Defining a Path Forward (2019) · cites this paper as Xie et al., 2018
Alterations in DNA methylation are observed during replicative senescence, whereas cells undergoing oncogene induced senescence do not show such alterations in DNA methylation.
“Alterations in DNA methylation are observed during replicative senescence whereas cells undergoing oncogene induced senescence do not show any such alterations in DNA methylation (Cruickshanks et al., 2013; Cheng et al., 2017; Xie et al., 2018).”
From Mechanisms of Cellular Senescence: Cell Cycle Arrest and Senescence Associated Secretory Phenotype (2021) · cites this paper as Xie et al., 2018
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 75 · Cited by 122
Research works printed but not linked: 1
- Berman BP Weisenberger DJ Aman JF Hinoue T Ramjan Z Liu Y Noushmehr H Lange CP van Dijk CM Tollenaar RA 2012 Regions of focal DNA hypermethylation and long-range hypomethylation in colorectal cancer coincide with nuclear lamina-associated domains Nat Genet 44 40 46 PMC4309644 22120008
- Authors
- Xie, W., Kagiampakis, I., Pan, L., Zhang, Y. W., Murphy, L., Tao, Y., Kong, X., Kang, B., Xia, L., Carvalho, F. L. F., Sen, S., Chiu Yen, R.-W., Zahnow, C. A., Ahuja, N., Baylin, S. B., & Easwaran, H.
- Affiliations
- Johns Hopkins University (US)
- National Institutes of Health (US)
- University of Mumbai (IN)
- Corresponding author
- Baylin, Stephen B.
- Easwaran, Hariharan
- ORCID
- Venue
- Cancer Cell
- Publisher
- Elsevier BV
- Published
- 2018-02
- Volume
- 33
- Issue
- 2
- Pages
- 309-321.e5
- ISSN
- 1535-6108 (ISSN-L)
- PMC
- PMC5813821
- OpenAlex
- W2785550069
- Cited by
- 122
- References
- 75
- Citations by year
- 2026: 9 · 2025: 16 · 2024: 13 · 2023: 16 · 2022: 17 · 2021: 17 · 2020: 13 · 2019: 16 · 2018: 4 · 2013: 1
- FWCI
- 4.45
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cancer Cell (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Cancer Institute (R01CA185357, R21CA212495, R01CA170550)
- The Hodson Trust
- Johns Hopkins SKCCC Microarray Core
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Health Sciences › Medicine › Physiology › Telomeres, Telomerase, and Senescence
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Keywords
- DNA methylation, cellular senescence, cancer transformation, promoter hypermethylation, cancer risk, tissue aging, self-renewal, developmental genes, metabolic modulators, cancer prevention, epigenetic modifications
- MeSH terms
- Animals, Cell Transformation, Neoplastic, Humans, Neoplasms, Promoter Regions, Genetic, Risk, Mice, SCID, Cellular Senescence, CpG Islands, DNA Methylation, Epigenesis, Genetic, Mice
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 ›
Are you an author, or do you see a problem with this page? Request a review
