The DOI matches its Crossref record; 43 of the 45 references it cites were found in a registry or an index; 17 of the 23 sources its claims cite were checked for support.
Unmasking Transcriptional Heterogeneity in Senescent Cells
Open accessAbstract
Cellular senescence is a state of irreversibly arrested proliferation, often induced by genotoxic stress [1]. Senescent cells participate in a variety of physiological and pathological conditions, including tumor suppression [2], embryonic development [3, 4], tissue repair [5-8], and organismal aging [9]. The senescence program is variably characterized by several non-exclusive markers, including constitutive DNA damage response (DDR) signaling, senescence-associated β-galactosidase (SA-βgal) activity, increased expression of the cyclin-dependent kinase (CDK) inhibitors p16INK4A (CDKN2A) and p21CIP1 (CDKN1A), increased secretion of many bio-active factors (the senescence-associated secretory phenotype, or SASP), and reduced expression of the nuclear lamina protein LaminB1 (LMNB1) [1]. Many senescence-associated markers result from altered transcription, but the senescent phenotype is variable, and methods for clearly identifying senescent cells are lacking [10]. Here, we characterize the heterogeneity of the senescence program using numerous whole-transcriptome datasets generated by us or publicly available. We identify transcriptome signatures associated with specific senescence-inducing stresses or senescent cell types and identify and validate genes that are commonly differentially regulated. We also show that the senescent phenotype is dynamic, changing at varying intervals after senescence induction. Identifying novel transcriptome signatures to detect any type of senescent cell or to discriminate among diverse senescence programs is an attractive strategy for determining the diverse biological roles of senescent cells and developing specific drug targets.
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Claims the paper makes
17 of 23 cited sources checked · 9 supported · 0 flagged · accuracy not yet measured
The cited sources that could be checked couldn’t confirm or dispute this claim.
In the paper
“Among the main gene ontology (GO) pathways [19, 20] showing altered in senescent cells, “chromatin organization,” “DNA repair,” “membrane trafficking,” and “activation of NF-kappaB” were notable for their known links to senescence and aging (Figure 1C) (Figure 1C) [1, 10, 21, 22].”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
What the sources say
- Could not verifycites [19] Kamburov, 2009, ConsensusPathDB--a database for integrating human functional interaction networks, Nucleic Acids Res. sourceExperimental — accuracy not yet measured
The Results (Web interface; page unavailable) describe a tool for pathway over-representation analysis, not an analysis of senescent cells. Searches for senescence and the named pathways found no passage in our copy reporting that chromatin organization, DNA repair, membrane trafficking, or NF-kappaB activation was altered in senescent cells. (LLM, conf=0.76)
- Could not verifycites [20] Kamburov, 2011, ConsensusPathDB: toward a more complete picture of cell biology, Nucleic Acids Res. sourceExperimental — accuracy not yet measured
The 'Use case: functional network-based analysis of gene expression data' section describes Gene Ontology findings from a comparison of primary and metastatic prostate cancer, not senescent cells. Searches for senescence, membrane trafficking, and NF-kappaB found no passage reporting the four claimed altered pathways in senescent cells. (LLM, conf=0.75)
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes- Could not verify
Every source the paper cites for this claim was checked and supports it.
In the paper
“Nevertheless, within the senescence core signature, we found genes that had been previously linked to senescence: BCL2L2 (also known as Bcl-w), a negative regulator of apoptosis [26]; PATZ1, a transcriptional repressor whose expression inhibits senescence in endothelial cells [27]; SMO, a component of the Hedgehog pathway [28]; and CCND1, a regulatory subunit of CDK4 or CDK6, whose activity is req”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
What the sources say
- Supportedcites [26] Yosef, 2016, Directed elimination of senescent cells by inhibition of BCL-W and BCL-XL, Nat. Commun. source
Citation [26] is attached to BCL2L2 (Bcl-w), not to PATZ1 or SMO, which have separate citations. The Results section identifies BCL-W as an anti-apoptotic protein and reports increased expression in senescent cells; no page number is provided in our copy. (LLM, conf=0.94)
- Supportedcites [27] Cho, 2012, POZ/BTB and AT-hook-containing zinc finger protein 1 (PATZ1) inhibits endothelial cell senescence through a p53 dependent pathway, Cell Death Differ. source
The citation [27] is attached to the PATZ1 description, not the claims about BCL2L2 or SMO. The Abstract describes PATZ1 as a potential transcriptional repressor, and the Discussion reports that increasing its expression in old endothelial cells reversed senescence phenotypes. (LLM, conf=0.93)
- Supportedcites [28] Breslin, 2014, Ciliary abnormalities in senescent human fibroblasts impair proliferative capacity, Cell Cycle source
The Results identify SMO as a Hedgehog-pathway component and report reduced SMO expression in senescent human fibroblasts. The citation is attached to the statement about SMO; the paper does not need to establish which genes the citing authors included in their core signature. (LLM, conf=0.92)
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“These findings suggest that even in whole tissues where the number of senescent cells is small (most aged or diseased tissues contained 1%–3% senescent cells [33]), some of the genes of our core signature can be identified as differentially regulated.”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
What the sources say
- Partly supportedcites [33] Childs, 2015, Cellular senescence in aging and age-related disease: from mechanisms to therapy, Nat. Med. sourceExperimental — accuracy not yet measured
The citation is attached to the parenthetical claim about the proportion of senescent cells, not to the citing authors’ finding about core-signature genes. The source’s “Senescence in normal aging” section (page unavailable) describes senescent cells as rare in aged tissues, but our copy does not give the claimed 1%–3% figure for most aged or diseased tissues. (LLM, conf=0.84)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Partly supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“Strikingly, ten genes in our core signature (DGKA, GBE1, GDNF, KCTD3, MEIS1, PDLIM4, RAI4, SPIN4, TAF13, and TRDMT1) were also present in this dataset (adjusted p ≤ 0.01; data not shown).”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
What the sources say
- Supportedcites [32] Schafer, 2017, Cellular senescence mediates fibrotic pulmonary disease, Nat. Commun. source
The citation identifies the IPF lung-expression dataset used for the citing authors’ comparison. The Methods (Human samples and transcriptome data sets; Data availability, page unavailable) confirm that this paper analysed lung microarray data from patients with IPF and controls and makes the dataset available. The citing sentence labels the ten-gene comparison as its own ‘data not shown’ result. (LLM, conf=0.87)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“Indeed, one of the studies used here [14] showed that p16INK4A mRNA levels are not always significantly changed in senescence in some fibroblast strains.”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
What the sources say
- Supportedcites [14] Marthandan, 2016, Conserved senescence associated genes and pathways in primary human fibroblasts detected by RNA-seq, PLoS ONE source
In Results, under “Common DEG with age across the five fibroblast strains,” the paper reports that p16 (CDKN2A) was not among the genes significantly differentially regulated with age across the strains. It also says mRNA and protein levels correlated only in some strains, supporting the claim that p16 mRNA does not always change significantly during fibroblast senescence. (LLM, conf=0.92)
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Only one gene in our signature (PLK3) was reported differentially expressed in a radiosensitive lymphoblast line 4 hr after exposure to 2 Gy ionizing radiation (false discovery rate [FDR] ≤ 0.05), a dose that causes damage without pervasive permanent cell-cycle arrest.”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
What the sources say
- Partly supportedcites [31] Borràs-Fresneda, 2016, Differences in DNA repair capacity, cell death and transcriptional response after irradiation between a radiosensitive and a radioresistant cell line, Sci. Rep. sourceExperimental — accuracy not yet measured
The Results (page unavailable) report differential expression in a radiosensitive lymphoblastoid cell line 4 hours after 2 Gy irradiation, and the Methods specify a 0.05 FDR cutoff. Our copy does not identify PLK3 among those genes or establish that it was the only gene from the citing authors’ signature to meet the cutoff; the Results refer to gene lists in supplementary datasets not reproduced in the passages searched. (LLM, conf=0.84)
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Partly supported
The cited sources that could be checked couldn’t confirm or dispute this claim.
In the paper
“However, most studies analyze senescent phenotypes 7–10 days after applying the senescence inducers [36, 37].”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
What the sources say
- Could not verifycites [36] Velarde, 2016, Targeting senescent cells: possible implications for delaying skin aging: a mini-review, Gerontology sourceExperimental — accuracy not yet measured
The Introduction describes senescence inducers and markers, but gives no timing for when studies analyze senescent phenotypes. Searches for “7–10 days after applying senescence inducers” and for analysis timing after induction found no passage addressing the claimed 7–10-day practice. (LLM, conf=0.73)
- Could not verifycites [37] van Deursen, 2014, The role of senescent cells in ageing, Nature sourceExperimental — accuracy not yet measured
The section ‘Senescence is a multi-step evolving process’ says cultured cells usually reach senescence within several weeks of exposure to stressors, but does not say when studies analyze their phenotypes. Searches for 7–10 days and assessment timing found no passage establishing the claimed practice. (LLM, conf=0.73)
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Could not verify
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Intermediate senescence was characterized by metabolic changes (the citric acid cycle and respiratory electron transport), p53-associated pathways, and signaling mediated by p38-gamma and p38-delta, two isoforms of p38-MAPK (mitogen-activated protein kinase) known to have an important role in senescence and the SASP [38].”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
What the sources say
- Partly supportedcites [38] Xu, 2014, Emerging roles of the p38 MAPK and PI3K/AKT/mTOR pathways in oncogene-induced senescence, Trends Biochem. Sci. sourceExperimental — accuracy not yet measured
The citation is attached to the statement about p38γ and p38δ, not the citing authors’ characterization of intermediate senescence. In “Differential roles of p38 isoforms in OIS” (page unavailable), the review identifies both as p38 isoforms that mediate oncogene-induced senescence. The passages on the senescence-associated secretory phenotype do not establish a role for these two isoforms in the SASP. (LLM, conf=0.84)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Partly supported
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We also show that the senescent phenotype is dynamic, changing at varying intervals after senescence induction.”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Cell-type-dependent genes were enriched in different GO terms. For instance, few GO terms related to intracellular transport, RNA and/or protein expression, or processing and immune system functions were associated with the different cell types (Figure S2B).”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes
- Probably not a substantial claim. 14
- It may state two separate claims as one. 23
Every source the paper cites for this claim was checked and supports it.
In the paper
“For example, upregulation of various components of the SASP has been reported to be dependent on the type of cell [24].”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
What the sources say
- Supportedcites [24] Coppé, 2008, Senescence-associated secretory phenotypes reveal cell-nonautonomous functions of oncogenic RAS and the p53 tumor suppressor, PLoS Biol. source
The Results (passage [7]; page not provided) identify SASP factors that differ between senescent prostate epithelial cells and fibroblasts, including factors unique to each. The Discussion (passage [3]) likewise reports quantitative and qualitative differences among cell strains and lines. (LLM, conf=0.93)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“This variability highlights the importance of time and cellular identity in determining the SASP and reflects the complexity of its regulation and biological functions [1].”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
What the sources say
- Supportedcites [1] Loaiza, 2016, Cellular senescence and tumor promotion: is aging the key?, Biochim. Biophys. Acta source
Section 4.1 states that the SASP develops slowly over several days and describes multiple regulatory pathways. Sections 4.2 and 5.1 describe variation across cell types and tissues, as well as diverse, sometimes opposing biological functions. Page numbers were not supplied in the copy. (LLM, conf=0.91)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“Nonetheless, one sample within one of the datasets (RS IMR90 [14]) clustered differently from its replicates. The aberrant clustering of this sample was reported in the original study, and this sample was then removed from further analysis (Figure S1A).”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
What the sources say
- Supportedcites [14] Marthandan, 2016, Conserved senescence associated genes and pathways in primary human fibroblasts detected by RNA-seq, PLoS ONE sourceExperimental — accuracy not yet measured
In Results, under “Correlation among the mRNA expression levels of fibroblast triplicates,” the paper reports that one late-passage IMR-90 sample showed increased variance relative to its two replicates in the clustering plot and was removed from further analysis. This supports the claim about the RS IMR90 sample. (LLM, conf=0.94)
Strength:plain· not yet calibratedSingle caseTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“The senescence phenotype, including the transcriptome, is highly dynamic, and not all the common senescence markers appear or persist simultaneously [34, 35].”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
What the sources say
- Not checked — no full text of the sourcecites [34] Kim, 2013, Implications of time-series gene expression profiles of replicative senescence, Aging Cell source
- Partly supportedcites [35] Schäuble, 2012, Quantitative model of cell cycle arrest and cellular senescence in primary human fibroblasts, PLoS ONE sourceExperimental — accuracy not yet measured
The Results (Model Application to Differently Stressed Cells; page not provided) show that senescence markers appear at different times in BJ fibroblasts and that those cells do not form SAHF, supporting the point that common markers need not appear simultaneously. The paper does not establish that the transcriptome is highly dynamic or that markers cease to persist after appearing. (LLM, conf=0.86)
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
Every source the paper cites for this claim was checked and supports it.
In the paper
“However, it is possible that samples collected to perform the RNA-seq experiments might have been in a pre-p16INK4A engagement phase, as p16INK4A is often induced late after senescence induction [39].”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
What the sources say
- Supportedcites [39] Stein, 1999, Differential roles for cyclin-dependent kinase inhibitors p21 and p16 in the mechanisms of senescence and differentiation in human fibroblasts, Mol. Cell. Biol. source
The Results and Discussion report that p16 increases after human fibroblasts achieve senescence and that cells at the first signs of senescence can show almost no p16 increase. This supports the claimed late timing, although the paper’s observations concern replicative senescence in human fibroblasts. (LLM, conf=0.90)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
- Supported
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We also validated a subset of these genes in primary human HCA-2 fibroblasts and confirmed differential expression compared to that in proliferating and quiescent cells (Figures S4B and S4C).”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, the second and third principal components separated the cells according to senescence status, with some influence from the study/dataset of origin (Figure S1A).”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“By contrast, p21CIP1 was among the genes differentially expressed by all senescent cell types and in response to all stimuli, although it was also slightly upregulated in quiescence, concordant with its known involvement in both types of cell-cycle arrest [40].”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
What the sources say
- Not checked — no full text of the sourcecites [40] Terzi, 2016, The cell fate: senescence or quiescence, Mol. Biol. Rep. source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Within the senescence-associated signature of fibroblasts, multiple genes related to transcription and RNA synthesis were downregulated, while genes involved in vesicle transport were upregulated (Figure 1B).”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“LMNB1 was strongly downregulated in all cell types, with the exception of melanocytes, but was also somewhat downregulated at quiescence.”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
Strength:boosted· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Importantly, this gene was no longer differentially expressed 24 hr or 14 days after the radiation or at any time after radiation in a radioresistant lymphoblast line (data not shown).”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We identified 61 genes that were shared among all cell types and time points, 34 of which were not shared with quiescent cells (Figure S4A; Data S3D).”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A number of genes were associated with a specific senescence-inducing stimulus: 1,699 genes with RS, 2,365 genes with OIS, and 647 genes with IRIS (Figures 1A and S1C; Data S1B–S1D).”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“While we found differential expression of all the genes at day 10 for melanocytes and keratinocytes, other time points showed high variability.”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Of note, most of the genes had a moderate fold change, yet 26 of them changed greater than 1.3-fold in all cell types.”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In terms of GO and pathway analysis, some of the downregulated genes were associated with DNA binding or regulation of transcription, while upregulated genes were mainly related to DNA damage checkpoints and mitosis (Figures 2C and 2D).”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
Strength:hedged· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The extracted RNA was quantitated using a NanoDrop (higher than 1 μg) and RNA quality was measured via BioAnalyzer chip (Agilent) (RIN of 8 or greater).”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > STAR★METHODS > METHOD DETAILS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Of note, the stimulus-specific signature might be influenced by the fact that more than one dataset was available only for RS.”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Randomization and blinding of most experiments were not possible, but otherwise described.”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > STAR★METHODS > METHOD DETAILS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“To ensure the identification of genes associated with senescence, and not growth arrest per se, we analyzed quiescent (HCA2) fibroblasts and removed from subsequent analysis those genes similarly regulated in both quiescence and each of the senescence conditions.”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
- Rests on an assumption: Quiescent cells provide a valid control for growth arrest per se.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Every biological replicate was stained in duplicate, and counting was made in blind.”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > STAR★METHODS > METHOD DETAILS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In a few cases, the differential expression of individual genes was not statistically significant, suggesting that a combination of the expression level of senescence core genes might be a much stronger predictor of senescence.”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
Strength:hedged· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, our data clearly highlight the heterogeneity of senescent cells in culture, anticipating that these challenges might be amplified in vivo, where less is known about the stimuli and cell types associated with senescence.”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“the senescent phenotype is variable, and methods for clearly identifying senescent cells are lacking [10].”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > Abstract
What the sources say
- Not checked — no full text of the sourcecites [10] Sharpless, 2015, Forging a signature of in vivo senescence, Nat. Rev. Cancer source
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We set a stringent threshold of nominal p ≤ 0.01 to reduce the odds of false-positive results and retained only those genes that were differentially expressed by the three different methods.”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
In the paper
“It is noteworthy that the common senescence markers, CDKN2A, CDKN1A, and LMNB1, were not within the core signature, supporting the idea that known senescence markers lack universality for different cell types and inducers of senescence [10].”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
What the sources say
- Not checked — no full text of the sourcecites [10] Sharpless, 2015, Forging a signature of in vivo senescence, Nat. Rev. Cancer source
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Cells (6 biological replicates per condition) were prepared for RNA extraction via an RNAeasy mini kit (QIAGEN).”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > STAR★METHODS > METHOD DETAILS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These signatures can help identify senescent cells and discriminate among different senescence programs.”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > RESULTS AND DISCUSSION
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“All samples were run with a technical replicate and in 2–3 biological replicates.”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > STAR★METHODS > QUANTIFICATION AND STATISTICAL ANALYSIS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“In all cases, both for SA-βgal assay and for EdU staining, samples were done in triplicates and at least 100 cells were counted in each replicate (in blind) and corresponding barplots were generated, where error bars represent the Standard Error of the Mean (SEM).”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > STAR★METHODS > QUANTIFICATION AND STATISTICAL ANALYSIS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Quality control of all samples, including our own, was performed using the FastQC software v0.11.5 and the low quality reads (Average Quality: < 20) were discarded.”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > STAR★METHODS > METHOD DETAILS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Every biological replicate was stained in duplicate, and counting was made in blind.”
§ Unmasking Transcriptional Heterogeneity in Senescent Cells > STAR★METHODS > METHOD DETAILS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
The paper relies on this without support.
Many senescence-associated markers arise from altered transcription.
“Many senescence-associated markers result from altered transcription, but the senescent phenotype is variable, and methods for clearly identifying senescent cells are lacking [10].”
The paper relies on this without support.
SA-βgal activity and growth arrest are valid indicators of senescence status.
“senescence status was confirmed by SA-βgal activity and growth arrest (Figure S2A).”
“Senescence status was confirmed by SA-βgal activity (Figure S3A), lack of 5-ethynyl-2′-deoxyuridine (EdU) incorporation (Figure S3B), and increased expression of p16INK4a and p21CIP1 (for RS cells; Figure S3C).”
The paper relies on this without support.
Quiescent cells provide a valid control for growth arrest per se.
“To ensure the identification of genes associated with senescence, and not growth arrest per se, we analyzed quiescent (HCA2) fibroblasts and removed from subsequent analysis those genes similarly regulated in both quiescence and each of the senescence conditions.”
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“SASP factors, senescence markers and markers of other fundamental aging processes (for example, α-Klotho) can be assayed in body fluids such as urine, saliva, blood or cerebrospinal fluid7,19,48,59,61,64,132,133.”
From Cellular senescence and senolytics: the path to the clinic (2022) · cites this paper as [132]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Senescent phenotypes vary depending on the cell type, senescence-inducing stimulus, microenvironment, and time since senescence induction, with distinct transcriptomic and proteomic profiles reported across models.9–11”
From SenCat: Cataloging human cell senescence through multi-omic profiling of multiple senescent primary cell types (2026) · cites this paper as [11]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Induction of senescence is a tumor suppressor mechanism143–145 and a side effect of several chemotherapeutic drugs that induce a phenotype that might be considered an acquired premature progeroid syndrome in both normal and cancer cells146.”
From Guidelines for minimal information on cellular senescence experimentation in vivo (2024) · cites this paper as [146]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Even p16 INK4A , which is considered more specific to senescence, is expressed in certain non-senescent cells (Sharpless and Sherr, 2015) and is not expressed by all senescent cells (Hernandez-Segura et al., 2017).”
From Cellular Senescence: Defining a Path Forward (2019) · cites this paper as Hernandez-Segura et al., 2017
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Adding to this complexity, senescent cells and their SASP exhibit variability contingent upon the specific physiological context, stress, cell type, and tissue under investigation (Hernandez-Segura et al, 2017).”
From Distinct senotypes in p16- and p21-positive cells across human and mouse aging tissues (2025) · cites this paper as Hernandez-Segura et al, 2017
Experimental — accuracy not yet measured
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Despite growing recognition of SnC heterogeneity, most studies have primarily focused on bulk analyses or primary senescence induced by specific stressors such as ionizing radiation or oncogene activation (Hernandez‐Segura et al. 2017).”
From Transcriptional Profiling at Single-Cell Resolution Reveals Diversity and Regulatory Networks of Primary and Secondary Senescent Cells (2026) · cites this paper as Hernandez‐Segura et al. 2017
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“This temporal regulation of senescence- associated phenotypes seems to be, at least in part, controlled by the sequential and dynamic activation of diverse transcriptional programmes and hierarchies 72-74 .”
From Senescence and cancer — role and therapeutic opportunities (2022) · cites this paper as [72]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Besides, senescence patterns are variable across cell types, tissues, and inductions.17”
From Single-cell senescence identification reveals senescence heterogeneity, trajectory, and modulators (2024) · cites this paper as [17]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“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 [44]
The cited source says what the claim attributes to it.
In the citing paper
“A set of 13 genes was differentially regulated in several cell types undergoing distinct forms of senescence, including oncogene-, replicative-, and DNA-damage-induced senescence (Hernandez-Segura et al., 2017).”
From Cellular Senescence: Defining a Path Forward (2019) · cites this paper as Hernandez-Segura et al., 2017
The cited source says what the claim attributes to it.
In the citing paper
“Sncs are heterogeneous for several reasons. First, senescence is a dynamic, not static, process. Thus, it is reasonable to assume that within a tissue both early and late Sncs coexist and have distinct phenotypes. Second, Sncs have different expression profiles based on their cell lineage as well as the type of stress that triggered senescence (31). Finally, Sncs play different roles depending on”
From Senolytic Drugs: Reducing Senescent Cell Viability to Extend Health Span (2021) · cites this paper as [31]
The cited source says what the claim attributes to it.
In the citing paper
“SASP gene expression is temporally dynamic100, and temporal changes in NOTCH1 activity during senescence have been reported to modulate the composition of SASP.”
From Cellular senescence in ageing: from mechanisms to therapeutic opportunities (2021) · cites this paper as [100]
The cited source says what the claim attributes to it.
In the citing paper
“However, currently no specific marker of the senescent cell-cycle arrest has been identified (Hernandez-Segura et al., 2017).”
From Cellular Senescence: Defining a Path Forward (2019) · cites this paper as Hernandez-Segura et al., 2017
The cited source says what the claim attributes to it.
In the citing paper
“SASP strength and composition is also regulated temporally (Hernandez-Segura et al. 2017).”
From Senescence and the SASP: many therapeutic avenues (2020) · cites this paper as Hernandez-Segura et al. 2017
The cited source says what the claim attributes to it.
In the citing paper
“A central challenge in senescence research is the inherent heterogeneity within SnC populations (Cohn et al. 2023; Hernandez‐Segura et al. 2017; Wechter et al. 2023).”
From Transcriptional Profiling at Single-Cell Resolution Reveals Diversity and Regulatory Networks of Primary and Secondary Senescent Cells (2026) · cites this paper as Hernandez‐Segura et al. 2017
The cited source says what the claim attributes to it.
In the citing paper
“Indeed, senescence- associated phenotypes are temporal and early- stage senescent cells are phenotypically different from late- stage senescent cells 72-74 .”
From Senescence and cancer — role and therapeutic opportunities (2022) · cites this paper as [72]
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“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 [44]
Experimental — accuracy not yet measuredIn the citing paper
“Induction of p21WAF1/CIP1 is crucial for initiation of senescence mediated growth arrest by different stimuli (Noda et al., 1994; Hernandez-Segura et al., 2017).”
From Mechanisms of Cellular Senescence: Cell Cycle Arrest and Senescence Associated Secretory Phenotype (2021) · cites this paper as Hernandez-Segura et al., 2017
In the citing paper
“However, the difficulty in the identification of a general regulatory mechanism restricts its utility as an unequivocal marker for senescence as no unique form of SASP is known to exist (Coppé et al., 2010a; Hernandez-Segura et al., 2017; Sun et al., 2018).”
From Mechanisms of Cellular Senescence: Cell Cycle Arrest and Senescence Associated Secretory Phenotype (2021) · cites this paper as Hernandez-Segura et al., 2017
In the citing paper
“Senescence associated secretory phenotype is nonspecific, context dependent and highly heterogeneous which can be regulated at multiple different levels.”
From Mechanisms of Cellular Senescence: Cell Cycle Arrest and Senescence Associated Secretory Phenotype (2021) · cites this paper as Hernandez-Segura et al., 2017
In the citing paper
“Attempts to distinguish between beneficial and pathological cell senescence at the proteome (15), transcriptome (56, 57), and functional levels have not been successful to date.”
From Connecting aging biology and inflammation in the omics era (2022) · cites this paper as [57]
In the citing paper
“Relevant to inflammageing, senescent cells acquire a senescence-associated secretory phenotype (SASP) that involves the secretion of a wide range of soluble molecules.”
From Inflammageing: chronic inflammation in ageing, cardiovascular disease, and frailty (2018) · cites this paper as [95]
In the citing paper
“Senescence and the SASP are dynamic phenotypes that change over time (De Cecco et al., 2019; Hernandez-Segura et al., 2017).”
From Oxylipin biosynthesis reinforces cellular senescence and allows detection of senolysis (2021) · cites this paper as Hernandez-Segura et al., 2017
In the citing paper
“Many global gene expression analyses to identify gene expression signatures of senescence have highlighted highly variable and heterogeneous profiles in function of the cell of origin, the mode of induction, and the time after induction of the senescence program [133,134].”
From Mechanisms and Regulation of Cellular Senescence (2021) · cites this paper as [133]
In the citing paper
“Conversely, genes involved in membrane trafficking and intercellular signaling, such as cell–cell adhesion molecules and cell–surface receptors, are upregulated in senescent cells [133,140].”
From Mechanisms and Regulation of Cellular Senescence (2021) · cites this paper as [133]
In the citing paper
“For instance, in senescent cells, biosynthetic activity is decreased due to the downregulation of genes required for DNA, RNA, and protein synthesis, as well as of genes with a role in glucose and fatty acid metabolism [133].”
From Mechanisms and Regulation of Cellular Senescence (2021) · cites this paper as [133]
In the citing paper
“DNA repair and chromatin organization genes are downregulated [133,139,140].”
From Mechanisms and Regulation of Cellular Senescence (2021) · cites this paper as [133]
In the citing paper
“Half of the genes differentially expressed by senescent fibroblasts (regardless of the senescence inducer) are not shared with quiescent cells [133].”
From Mechanisms and Regulation of Cellular Senescence (2021) · cites this paper as [133]
In the citing paper
“These chromatin rearrangements affect the transcriptional program of senescent cells and contribute to their transcriptome diversity [133,136,275].”
From Mechanisms and Regulation of Cellular Senescence (2021) · cites this paper as [133]
In the citing paper
“Senescent cells undergo extensive epigenome and chromatin organization changes that contribute to the persistent proliferative arrest and progression to full senescence (Figure 2).”
From Mechanisms and Regulation of Cellular Senescence (2021) · cites this paper as [133]
In the citing paper
“Senescent cell populations are generally highly heterogeneous in function of the cell type, the senescence-initiating insult, and the interactions within the microenvironment [133,134,135].”
From Mechanisms and Regulation of Cellular Senescence (2021) · cites this paper as [133]
In the citing paper
“Analysis of bulk RNA sequencing (RNA-seq) data from fibroblasts from both humans (foreskin fibroblasts, epidermal melanocytes) and mice (embryonic fibroblasts, skin microvascular endothelial cells) demonstrate differences in transcriptomic signatures and SASPs based on senescence inducers, cell types, and stages of the senescence process [22], which may contribute to differences in function.”
From The heterogeneity of cellular senescence: insights at the single-cell level (2023) · cites this paper as [22]
In the citing paper
“Even in the case of senescence where multiple different senescent states have been defined,55 they are still modeled as discrete.”
From Asynchronous, contagious and digital aging (2021) · cites this paper as [55]
In the citing paper
“However, these analyses allowed the identification of a ‘core’ senescence signature—a set of genes that are commonly differentially expressed in all the senescent cells analyzed5,38.”
From Algorithmic assessment of cellular senescence in experimental and clinical specimens (2021) · cites this paper as [5]
In the citing paper
“Accordingly, by comparing whole-transcriptome datasets obtained from different types of senescent cells, we and others have recently shown that neither p21WAF1/Cip1 nor p16INK4a are consistently upregulated.”
From Algorithmic assessment of cellular senescence in experimental and clinical specimens (2021) · cites this paper as [5]
In the citing paper
“The SASP is highly complex and heterogeneous, with a composition that is influenced by many intrinsic and extrinsic factors5,38.”
From Algorithmic assessment of cellular senescence in experimental and clinical specimens (2021) · cites this paper as [5]
In the citing paper
“Importantly, the analysis and comparison of whole-transcriptome datasets allowed the definition of gene sets that associate specifically with individual senescent subtypes5,38.”
From Algorithmic assessment of cellular senescence in experimental and clinical specimens (2021) · cites this paper as [5]
In the citing paper
“a subset of genes that are part of the core senescence signature we identified previously on the basis of by fold change in expression compared to non-senescent tissues or cells and p-values > 0.05)5”
From Algorithmic assessment of cellular senescence in experimental and clinical specimens (2021) · cites this paper as [5]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Biological replicate counts conflict
MajorThe sample-preparation section states that each condition had three biological replicates, while the RNA-seq section states that each condition had six. Neither statement qualifies the count to reconcile the two.
“For each condition, 3 biological replicates were generated.”
“Cells (6 biological replicates per condition) were prepared for RNA extraction via an RNAeasy mini kit (QIAGEN).”
Citations
Cites
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
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“For RS, the only group with more than one dataset, we performed a meta-analysis combining three different methods: we used (1) a negative binomial-generalized linear model (NB-GLM), pooling all the samples in all the datasets for one particular senescence-inducing stimulus and comparing them to proliferating counterpa…”
Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C., Gøtzsche, P. C., Ioannidis, J. P. A., Clarke, M., Devereaux, P. J., Kleijnen, J., & Moher, D. (2009) · PLoS Medicine · doi:10.1371/journal.pmed.1000100 · Cited by 28,164 · cited 1×
“To increase statistical power, and limit biases associated with individual studies [11], we used several datasets generated at different times and in different laboratories, including ours.”
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Oncogenic ras provokes premature cell senescence associated with accumulation of p53 and p16INK4a
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BackgroundMethodNaturally occurring p16Ink4a-positive cells shorten healthy lifespan
Baker, D. J., Childs, B. G., Durik, M., Wijers, M. E., Sieben, C. J., Zhong, J., A. Saltness, R., Jeganathan, K. B., Verzosa, G. C., Pezeshki, A., et al. (2016) · Nature · doi:10.1038/nature16932 · Cited by 2,876 · cited 1×
“Senescent cells participate in a variety of physiological and pathological conditions, including tumor suppression [2], embryonic development [3, 4], tissue repair [5–8], and organismal aging [9].”
BackgroundThe role of senescent cells in ageing
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“However, most studies analyze senescent phenotypes 7–10 days after applying the senescence inducers [36, 37].”
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Childs, B. G., Durik, M., Baker, D. J., & van Deursen, J. M. (2015) · Nature Medicine · doi:10.1038/nm.4000 · Cited by 2,363 · cited 1×
“These findings suggest that even in whole tissues where the number of senescent cells is small (most aged or diseased tissues contained 1%–3% senescent cells [33]), some of the genes of our core signature can be identified as differentially regulated.”
BackgroundAn Essential Role for Senescent Cells in Optimal Wound Healing through Secretion of PDGF-AA
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Items 701–800 of 920
Two roads to fibrosis: Contrasting initiating mechanisms of Bleomycin and TGFβ-1 in lung fibroblasts
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Early Neutrophil Sensing Shapes the Innate Response to Preneoplastic Mammary CellsPreprint
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YAP activation reverses aging-related visual dysfunction caused by impaired cell‒matrix adhesionPreprint
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“A central challenge in senescence research is the inherent heterogeneity within SnC populations (Cohn et al. 2023; Hernandez-Segura et al. 2017; Wechter et al. 2023).”
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“We included five well-cited gene sets empirically derived from different cell types and senescence-inducing stimuli: SAUL_SEN_MAYO, CSGene [ 15 ], CellAge [ 35 ], SeneQuest [ 4 ], and HernandezSegura [ 13 ].”
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Adipocytes as core drivers of skin aging and novel targets for regeneration
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Cellular senescence in cancer immunology and potential therapeutic strategy
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“This ecosystem generates competing signals that critically shape the local immune milieu (70).”
Senescent Factors Suppress Innate Antiviral Immunity in Aged Mice via Two Distinct Mechanisms
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“To identify potential functional SASP factors, we cross-examined genes up-regulated in senescent MEFs with secretory proteins reported in published senescence-associated proteomic datasets (Hernandez-Segura et al. 2017; Basisty et al. 2020).”
Spliceosome induction is a druggable dependency of RAS-driven senescence and cancer
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“Collectively, these results indicate that harmonization reduced residual batch structure and recovered a reproducible, condition-driven transcriptomic space suitable for defining shared senescence components across distinct triggers [4].”
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“The p53 signalling gene set was derived from the KEGG database (hsa04115), and the SASP gene set from the Reactome database (R- HSA-2559582), both of which have been used to characterise senescent transcriptional programmes [26, 27].”
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“…and confirmed brain-specific expression of each gene in published brain single-cell RNA sequencing and spatial transcriptome aging datasets 20,33,36–40 panel was previously annotated by the company to include markers of senescence and a subset of these genes were combined with the custom…”
Self-citationSenescent cells cluster CTCF on nuclear speckles to instruct an alternative splicing program
Palikyras, S., Varamogianni‐Mamatsi, V., Zhu, Y., Mizi, A., Ramasamy, S., Grini, J. V., Liebermann, I., Stavropoulou, A., Penagos‐Puig, A., Ogurlu-Tank, T. S., et al. (2026) · Nature Aging · doi:10.1038/s43587-026-01171-6 · Cited by 10
“Many of these changes converge between different cells and types of senescence 7,8,13 .”
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“The Hallmark pathways and Sen Mayo Signature are from the Mouse MSigDB Collection (Mootha et al, 2003; Subramanian et al, 2005; Liberzon et al, 2015), the Universal Signature was de fi ned by (Hernandez-Segura et al, 2017b).”
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The fundamental foundations of periodontal aging. Part 1
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“Three in vitro-derived senescence signatures from the literature (Hernandez-Segura et al., 2017) (irradiation, replicative, and oncogene induced senescence) did not map strongly to the scRNAseq cells when compared to the in vivo derived signature (Fig.”
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“We found strong overlap with previously published signature of senescent fibroblasts (Hernandez-Segura et al., 2017): out of 1311 genes in the universal signature of senescent fibroblasts, 1072 were present in our dataset, and when adjusted for multiple comparison 205 of them had statistically…”
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Metadata
- Authors
- Hernandez-Segura, A., de Jong, T. V., Melov, S., Guryev, V., Campisi, J., & Demaria, M.
- Affiliations
- Buck Institute for Research on Aging (US)
- University Medical Center Groningen (NL)
- Corresponding author
- Demaria, Marco
- Venue
- Current Biology
- Publisher
- Elsevier BV
- Published
- 2017-09
- Volume
- 27
- Issue
- 17
- Pages
- 2652-2660.e4
- ISSN
- 0960-9822 (ISSN-L)
- PMC
- PMC5788810
- OpenAlex
- W2749511637
- Cited by
- 972
- References
- 45
- Citations by year
- 2026: 105 · 2025: 122 · 2024: 141 · 2023: 122 · 2022: 134 · 2021: 129 · 2020: 83 · 2019: 54 · 2018: 30 · 2017: 5
- FWCI
- 27.39
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Current Biology (publishedVersion)
- PubMed (publishedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (publishedVersion, other-oa)
- Europe PMC (PubMed Central) (submittedVersion)
- PubMed Central (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Telomeres, Telomerase, and Senescence
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Advanced biosensing and bioanalysis techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Keywords
- cellular senescence, transcriptional heterogeneity, transcriptome signature, senescence-associated secretory phenotype, senescence-associated β-galactosidase, DNA damage response, p16INK4a, p21
- MeSH terms
- Animals, Cell Line, Humans, Cellular Senescence, Rats, Transcriptome
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