Unmasking Transcriptional Heterogeneity in Senescent Cells

Hernandez-Segura, Alejandra; de Jong, Tristan V.; Melov, Simon; Guryev, Victor; Campisi, Judith; Demaria, Marco

doi:10.1016/j.cub.2017.07.033

Cited by 972Telomeres, Telomerase, and SenescenceAdvanced biosensing and bioanalysis techniquesGenomics and Chromatin Dynamics

Unmasking Transcriptional Heterogeneity in Senescent Cells

Open access

Hernandez-Segura, Alejandra, de Jong, Tristan V., Melov, Simon, Guryev, Victor, Campisi, Judith, Demaria, Marco·2017·Current Biology

DOI 10.1016/j.cub.2017.07.033PMC PMC5788810

Open this paper in CoChat — free account Open PDF

Abstract

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.

Integrity signals

Registry

Crossref · 10.1016/j.cub.2017.07.033

Cites

44 of 44 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

17 of 23 cited sources checked · 9 supported · 0 flagged · accuracy not yet measured

Findingcitation
Altered GO pathways in senescent cells included chromatin organization, DNA repair, membrane trafficking, and NF-kappaB activation.
“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].”
Quote in the paperNot a substantial claim2 of 2 sources checked
- cites [19] Kamburov, 2009, ConsensusPathDB--a database for integrating human functional interaction networks, Nucleic Acids Res. source
  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)
  Experimental — accuracy not yet measured
- cites [20] Kamburov, 2011, ConsensusPathDB: toward a more complete picture of cell biology, Nucleic Acids Res. source
  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)
  Experimental — accuracy not yet measured
Findingcitation
The core signature includes BCL2L2, PATZ1, and SMO, genes previously linked to senescence.
“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”
Quote in the paperNot a substantial claim3 of 3 sources checked
- cites [26] Yosef, 2016, Directed elimination of senescent cells by inhibition of BCL-W and BCL-XL, Nat. Commun. source
- cites [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
- cites [28] Breslin, 2014, Ciliary abnormalities in senescent human fibroblasts impair proliferative capacity, Cell Cycle source
Interpretationown data
Even in whole tissues with a small senescent cell fraction (1-3%), some core signature genes can be identified as differentially regulated.
“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.”
Quote in the paperSubstantial claim1 of 1 sources checked
- cites [33] Childs, 2015, Cellular senescence in aging and age-related disease: from mechanisms to therapy, Nat. Med. source
  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)
  Experimental — accuracy not yet measured
Findingcitation
Ten core signature genes (DGKA, GBE1, GDNF, KCTD3, MEIS1, PDLIM4, RAI4, SPIN4, TAF13, and TRDMT1) were also differentially regulated in lung tissue from idiopathic pulmonary fibrosis patients (adjusted p ≤ 0.01).
“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).”
Quote in the paperSubstantial claim1 of 1 sources checked
- cites [32] Schafer, 2017, Cellular senescence mediates fibrotic pulmonary disease, Nat. Commun. source
Premisecitation
One study [14] showed that p16INK4A mRNA levels are not always significantly changed in senescence in some fibroblast strains.
“Indeed, one of the studies used here [14] showed that p16INK4A mRNA levels are not always significantly changed in senescence in some fibroblast strains.”
Quote in the paperSubstantial claim1 of 1 sources checked
- cites [14] Marthandan, 2016, Conserved senescence associated genes and pathways in primary human fibroblasts detected by RNA-seq, PLoS ONE source

Findingcitation
Only one core signature gene (PLK3) was reported differentially expressed in a radiosensitive lymphoblast line 4 hr after 2 Gy ionizing radiation (FDR ≤ 0.05).
“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.”
Quote in the paperSubstantial claim1 of 1 sources checked
- cites [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. source
  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)
  Experimental — accuracy not yet measured
Premisecitation
Most studies analyze senescent phenotypes 7-10 days after applying senescence inducers.
“However, most studies analyze senescent phenotypes 7–10 days after applying the senescence inducers [36, 37].”
Quote in the paperSubstantial claim2 of 2 sources checked
- cites [36] Velarde, 2016, Targeting senescent cells: possible implications for delaying skin aging: a mini-review, Gerontology source
  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)
  Experimental — accuracy not yet measured
- cites [37] van Deursen, 2014, The role of senescent cells in ageing, Nature source
  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)
  Experimental — accuracy not yet measured
Findingcitation
Intermediate senescence was characterized by metabolic changes (citric acid cycle and respiratory electron transport), p53-associated pathways, and p38-gamma/p38-delta signaling.
“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].”
Quote in the paperSubstantial claim1 of 1 sources checked
- cites [38] Xu, 2014, Emerging roles of the p38 MAPK and PI3K/AKT/mTOR pathways in oncogene-induced senescence, Trends Biochem. Sci. source
  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)
  Experimental — accuracy not yet measured
Findingown data
The senescent phenotype changes at different times after senescence induction.
“We also show that the senescent phenotype is dynamic, changing at varying intervals after senescence induction.”
Quote in the paperSubstantial claim
Findingown data
Cell-type-dependent genes were enriched in different GO terms, including few terms related to intracellular transport, RNA/protein expression or processing, and immune system functions.
“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).”
Quote in the paperNot a substantial claim
Findingcitation
The core signature includes CCND1, a regulatory subunit of CDK4 or CDK6.
“and CCND1, a regulatory subunit of CDK4 or CDK6, whose activity is required for the G1/S transition [29].”
Quote in the paperNot a substantial claim0 of 1 sources checked
- cites [29] Burton, 2007, Cyclin D1 overexpression permits the reproducible detection of senescent human vascular smooth muscle cells, Ann. N Y Acad. Sci. source
Findingown data
Early senescence was characterized by DNA damage response and p53 signaling.
“Early senescence was characterized by DNA damage response and p53 signaling, perhaps reflecting the first response to the damage caused by the radiation.”
Quote in the paperSubstantial claim
Findingown data
Genes that are commonly differentially regulated in senescence were identified and validated.
“We identify transcriptome signatures associated with specific senescence-inducing stresses or senescent cell types and identify and validate genes that are commonly differentially regulated.”
Quote in the paperSubstantial claim
Findingown data
None of the classical senescence markers (CDKN2A, CDKN1A, LMNB1, and SASP members) were among the 55 core signature genes.
“Remarkably, none of the classical senescence markers (CDKN2A, CDKN1A, LMNB1, and members of the SASP) were among these hits, since either they were not differentially expressed in all the cell types, or they were shared with quiescence (Figure S2C).”
Quote in the paperSubstantial claim
Findingown data
SASP factor genes showed significant time-point- and cell-type-dependent heterogeneity.
“Interestingly, genes encoding SASP factors showed significant time-point- and cell-type-dependent heterogeneity (Figure 3D).”
Quote in the paperSubstantial claim
Findingown data
Only in late senescence were cell-cycle arrest and chromatin remodeling among the top differentially expressed pathways.
“Notably, only in late senescence were cell-cycle arrest and chromatin remodeling among the top differentially expressed pathways, surpassing other pathways in importance (Figure 3C).”
Quote in the paperSubstantial claim
Findingown data
2,330 genes were differentially expressed in senescent fibroblasts regardless of the senescence inducer.
“We found that 2,330 genes were differentially expressed by senescent fibroblasts, regardless of the senescence inducer, and half of these genes (1311 genes) were not shared with quiescent cells (Figure 1A; Data S1E).”
Quote in the paperSubstantial claim
Findingown data
Tissue of origin (lung or foreskin) explained most of the variation in principal-component analysis.
“Principal-component analysis (PCA) revealed that the tissue of origin (lung or foreskin) accounted for most of the variation (data not shown).”
Quote in the paperNot a substantial claim
Findingown data
qPCR validation in BJ fibroblasts confirmed differential expression of selected core signature genes under most senescence-inducing conditions tested.
“We confirmed the differential expression of these genes under most of the conditions tested, further validating our identification of a senescence core signature.”
Quote in the paperSubstantial claim
Findingown data
55 genes were common differentially expressed hits comprising a senescence core signature.
“Importantly, upon examining the list of common differentially expressed genes, we identified a significant number of hits (55 in total; Figure 2B; Data S2F) comprising a senescence core signature.”
- Also stated in: § RESULTS AND DISCUSSION · plain
  “55 genes were also shared among four different cell types induced to senesce by four different stimuli.”
Quote in the paperSubstantial claim
Findingown data
Transcriptome signatures are associated with particular senescence-inducing stresses or senescent cell types.
“We identify transcriptome signatures associated with specific senescence-inducing stresses or senescent cell types and identify and validate genes that are commonly differentially regulated.”
Quote in the paperSubstantial claim
Findingown data
Intra- and inter-laboratory culture conditions contributed to variability in the analysis.
“Interestingly, our analysis revealed variability due to intra- and inter-laboratory culture conditions (Figure S1B).”
Quote in the paperNot a substantial claim
Findingown data
Each sample showed transcriptional induction of at least some known senescence-associated genes, including p16INK4A, p21CIP1, GLB1, and SASP factors.
“Each sample showed transcriptional induction of at least some of the known senescence-associated genes, namely, p16INK4A (CDKN2A), p21CIP1 (CDKN1A), GLB1 (SA-βgal), and several senescence-associated secretory phenotype (SASP) factors (Figure S1B).”
Quote in the paperSubstantial claim
Findingown data
GO and pathway analysis of time-course data revealed differential regulation of genes involved in cancer and cell-cycle progression.
“GO annotations and pathway analysis revealed the differential regulation of genes involved in cancer and cell-cycle progression (Figure 3B).”
Quote in the paperSubstantial claim
Findingown data
13 of the 55 core signature genes were differentially regulated at every time point and in every cell type.
“Nonetheless, among the 55 genes of the senescence core signature, 13 genes were differentially regulated at every time point and in every cell type (Figure 4, genes in red).”
- Also stated in: § RESULTS AND DISCUSSION · plain
  “Nevertheless, we were able to identify 13 genes as differentially regulated in all the conditions considered, including time.”
Quote in the paperSubstantial claim
Findingown data
1,311 of the 2,330 senescence-associated genes were not shared with quiescent cells.
“We found that 2,330 genes were differentially expressed by senescent fibroblasts, regardless of the senescence inducer, and half of these genes (1311 genes) were not shared with quiescent cells (Figure 1A; Data S1E).”
- Also stated in: § RESULTS AND DISCUSSION · plain
  “We found 1,311 genes uniquely differentially regulated in senescent fibroblasts and not quiescent fibroblasts.”
Quote in the paperSubstantial claim
Findingown data
Three enriched GO terms for astrocytes or keratinocytes were associated with differentiation in their tissue of origin (neurogenesis/neuron differentiation and epithelial cell differentiation).
“Three of the enriched GO terms for either astrocytes or keratinocytes were associated with differentiation in their tissue of origin (namely, “neurogenesis” or “neuron differentiation” and “epithelial cell differentiation,” respectively).”
Quote in the paperNot a substantial claim
Findingown data
Common differentially expressed genes between different stimuli were not affected by the number of datasets.
“However, common differentially expressed genes between the different stimuli were not affected by this variable.”
Quote in the paperSubstantial claim
Interpretationown data
Temporal dynamics strongly influence the detection of differentially expressed genes.
“Finally, we showed that temporal dynamics strongly influence the detection of differentially expressed genes.”
Quote in the paperSubstantial claim
Interpretationnone given
There is as yet no universal marker of senescence.
“It is clear, though, that there is, as yet, no universal marker of senescence.”
Quote in the paperSubstantial claim
Interpretationown data
EFNB3 showed discrepancies between mouse and human cells, suggesting potential species differences in senescence core signatures.
“Moreover, we identified discrepancies between mouse and human cells for EFNB3, suggesting potential differences in senescence core signatures among species.”
Quote in the paperNot a substantial claim
Interpretationown data
In fibroblasts, lack of significance of some core genes at day 10 is likely due to low power from using a single dataset, since they reached significance when multiple datasets were pooled.
“In the case of fibroblasts, the lack of significance of some genes at day 10 is likely due to the lack of power from using a single dataset, since these genes reached statistical significance only when multiple datasets were pooled.”
Quote in the paperNot a substantial claim
Interpretationown data
The senescence signature found is highly time dependent.
“The temporal dynamics of these genes exposed a new layer of complexity, revealing that the senescence signature found is highly time dependent.”
Quote in the paperSubstantial claim
Premisecitation
Cell-type-specific gene expression contributes to heterogeneity of the senescence program.
“An important contributor to the heterogeneity of the senescence program is the expression of cell-type-specific genes [23].”
Quote in the paperSubstantial claim0 of 1 sources checked
- cites [23] Fridlyanskaya, 2015, Senescence as a general cellular response to stress: A mini-review, Exp. Gerontol. source

Classified as probably not a substantial claim. 14
May combine two claims. 23

Classified as probably not a substantial claim.
Premisecitation
SASP component upregulation depends on the type of cell.
“For example, upregulation of various components of the SASP has been reported to be dependent on the type of cell [24].”
Quote in the paperSubstantial claim1 of 1 sources checked
- cites [24] Coppé, 2008, Senescence-associated secretory phenotypes reveal cell-nonautonomous functions of oncogenic RAS and the p53 tumor suppressor, PLoS Biol. source
May combine two claims.
Interpretationown data
This SASP variability highlights the importance of time and cellular identity in determining the SASP and reflects the complexity of its regulation and biological functions.
“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].”
Quote in the paperSubstantial claim1 of 1 sources checked
- cites [1] Loaiza, 2016, Cellular senescence and tumor promotion: is aging the key?, Biochim. Biophys. Acta source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductcitation
One RS IMR90 sample clustered differently from its replicates and was removed from further analysis.
“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).”
Quote in the paperNot a substantial claim1 of 1 sources checked
- cites [14] Marthandan, 2016, Conserved senescence associated genes and pathways in primary human fibroblasts detected by RNA-seq, PLoS ONE source
  Experimental — accuracy not yet measured
May combine two claims.
Premisecitation
The senescence phenotype, including the transcriptome, is highly dynamic and not all common senescence markers appear or persist simultaneously.
“The senescence phenotype, including the transcriptome, is highly dynamic, and not all the common senescence markers appear or persist simultaneously [34, 35].”
Quote in the paperSubstantial claim1 of 2 sources checked
- cites [34] Kim, 2013, Implications of time-series gene expression profiles of replicative senescence, Aging Cell source
- cites [35] Schäuble, 2012, Quantitative model of cell cycle arrest and cellular senescence in primary human fibroblasts, PLoS ONE source
  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)
  Experimental — accuracy not yet measured
Classified as probably not a substantial claim.
Premisecitation
p16INK4A is often induced late after senescence induction.
“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].”
Quote in the paperSubstantial claim1 of 1 sources checked
- cites [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
May combine two claims.
Findingown data
A subset of core signature genes was validated in primary human HCA-2 fibroblasts and confirmed differentially expressed compared to proliferating and quiescent cells.
“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).”
Quote in the paperSubstantial claim
May combine two claims.
Findingown data
The second and third principal components separated cells according to senescence status, with some influence from study/dataset origin.
“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).”
Quote in the paperSubstantial claim
May combine two claims.
Findingcitation
p21CIP1 was among genes differentially expressed by all senescent cell types and in response to all stimuli, although it was also slightly upregulated in quiescence.
“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].”
Quote in the paperSubstantial claim0 of 1 sources checked
- cites [40] Terzi, 2016, The cell fate: senescence or quiescence, Mol. Biol. Rep. source
May combine two claims.
Findingown data
In the fibroblast senescence signature, genes related to transcription and RNA synthesis were downregulated, while vesicle transport genes were upregulated.
“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).”
Quote in the paperNot a substantial claim
May combine two claims.
Findingown data
LMNB1 was strongly downregulated in all cell types except melanocytes, but was also somewhat downregulated at quiescence.
“LMNB1 was strongly downregulated in all cell types, with the exception of melanocytes, but was also somewhat downregulated at quiescence.”
Quote in the paperNot a substantial claim
May combine two claims.
Findingcitation
PLK3 was no longer differentially expressed 24 hr or 14 days after radiation or at any time in a radioresistant lymphoblast line.
“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).”
Quote in the paperSubstantial claim
May combine two claims.
Findingown data
61 genes were shared among all cell types and time points after ionizing radiation, and 34 of these were not shared with quiescent cells.
“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).”
Quote in the paperSubstantial claim
May combine two claims.
Findingown data
1,699 genes were associated with RS, 2,365 with OIS, and 647 with IRIS.
“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).”
Quote in the paperSubstantial claim
May combine two claims.
Findingown data
All 55 core signature genes were differentially expressed at day 10 for melanocytes and keratinocytes, while other time points showed high variability.
“While we found differential expression of all the genes at day 10 for melanocytes and keratinocytes, other time points showed high variability.”
Quote in the paperNot a substantial claim
May combine two claims.
Findingown data
Most core signature genes had moderate fold change, but 26 changed greater than 1.3-fold in all cell types.
“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.”
Quote in the paperNot a substantial claim
May combine two claims.
Findingown data
In the core signature, downregulated genes were associated with DNA binding or transcription regulation, while upregulated genes were mainly related to DNA damage checkpoints and mitosis.
“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).”
Quote in the paperNot a substantial claim
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown data
RNA quality was measured and RIN was 8 or greater.
“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).”
Quote in the paperNot a substantial claim
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductreasoning
The stimulus-specific signature might be influenced by having more than one dataset only for RS.
“Of note, the stimulus-specific signature might be influenced by the fact that more than one dataset was available only for RS.”
Quote in the paperNot a substantial claim
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone given
Randomization and blinding of most experiments were not possible.
“Randomization and blinding of most experiments were not possible, but otherwise described.”
Quote in the paperNot a substantial claim
Classified as probably not a substantial claim.
Study design and conductreasoning
Genes similarly regulated in quiescence and senescence were removed to avoid identifying genes associated with growth arrest rather than senescence.
“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.”
Quote in the paperSubstantial claim
- Rests on an assumption: Quiescent cells provide a valid control for growth arrest per se.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown data
SA-βgal counting was performed blind.
“Every biological replicate was stained in duplicate, and counting was made in blind.”
Quote in the paperNot a substantial claim
May combine two claims.
Interpretationown data
In a few cases, individual gene differential expression was not statistically significant, suggesting that a combination of core gene expression levels might be a stronger predictor of senescence.
“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.”
Quote in the paperNot a substantial claim
May combine two claims.
Interpretationown data
The heterogeneity of senescent cells in culture is clear, and challenges may be amplified in vivo.
“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.”
Quote in the paperSubstantial claim
May combine two claims.
Premisecitation
The senescence phenotype varies between cells, and no method currently identifies senescent cells with certainty.
“the senescent phenotype is variable, and methods for clearly identifying senescent cells are lacking [10].”
Quote in the paperSubstantial claim0 of 1 sources checked
- cites [10] Sharpless, 2015, Forging a signature of in vivo senescence, Nat. Rev. Cancer source
Classified as probably not a substantial claim. May combine two claims.
Study design and conductown data
For RS, three meta-analysis methods were used, and only genes differentially expressed by all three at nominal p ≤ 0.01 were retained.
“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.”
Quote in the paperSubstantial claim
May combine two claims.
Interpretationcitation
Known senescence markers CDKN2A, CDKN1A, and LMNB1 were not within the core signature, supporting that known markers lack universality for different cell types and inducers.
“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].”
Quote in the paperSubstantial claim0 of 1 sources checked
- cites [10] Sharpless, 2015, Forging a signature of in vivo senescence, Nat. Rev. Cancer source
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown data
RNA-seq used 6 biological replicates per condition.
“Cells (6 biological replicates per condition) were prepared for RNA extraction via an RNAeasy mini kit (QIAGEN).”
Quote in the paperNot a substantial claim
May combine two claims.
Interpretationown data
Core transcriptome signatures can help identify senescent cells and discriminate among different senescence programs.
“These signatures can help identify senescent cells and discriminate among different senescence programs.”
Quote in the paperSubstantial claim
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone given
qPCR samples were run with a technical replicate and in 2-3 biological replicates.
“All samples were run with a technical replicate and in 2–3 biological replicates.”
Quote in the paperNot a substantial claim
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown data
SA-βgal and EdU samples were done in triplicates and at least 100 cells were counted per replicate in blind.
“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).”
Quote in the paperNot a substantial claim
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone given
Low quality reads (average quality < 20) were discarded.
“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.”
Quote in the paperNot a substantial claim
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone given
EdU counting was performed blind.
“Every biological replicate was stained in duplicate, and counting was made in blind.”
Quote in the paperNot a substantial claim

32 of 32

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.”

3 of 3

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?

SASP factors, senescence markers, and markers of other aging processes such as α-Klotho can be assayed in body fluids including urine, saliva, blood, and cerebrospinal fluid.
“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]
The Results and Discussion (page unavailable) discuss SASP factors and senescence markers, including genes used to identify senescent cells. They do not establish that these markers can be assayed in urine, saliva, blood, or cerebrospinal fluid, and the passages found do not address α-Klotho (searched: body fluids and α-Klotho). (LLM, conf=0.82)
Experimental — accuracy not yet measured
Senescent phenotypes are heterogeneous, varying with cell type, inducing stimulus, microenvironment, and time since induction, and distinct transcriptomic and proteomic profiles have been reported across models.
“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]
The Results and Discussion report distinct transcriptomic signatures by cell type and inducing stimulus, as well as changes over time after induction. They also note variability associated with laboratory culture conditions, but do not establish microenvironment-dependent phenotypes more broadly. This paper analyzes transcriptomes; it does not report distinct proteomic profiles across models. Page numbers were not available in our copy. (LLM, conf=0.86)
Experimental — accuracy not yet measured
Induction of senescence is a tumor suppressor mechanism and a side effect of several chemotherapeutic drugs.
“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]
The Results and Discussion (page unavailable) describe doxorubicin as a chemotherapeutic agent known to cause senescence and report using it to induce senescence in primary fibroblasts. The paper does not establish the claim about several chemotherapeutic drugs or a premature progeroid phenotype in both normal and cancer cells. Its abstract also links senescence to tumor suppression, although that clause has separate citations in the citing sentence. (LLM, conf=0.88)
Experimental — accuracy not yet measured
p16 INK4A is not expressed by all senescent cells.
“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
The Results and Discussion say that CDKN2A (p16INK4A) is not part of the core senescence signature and that p16INK4A mRNA does not always change significantly in senescent fibroblast strains. This supports the point that p16INK4A is not a universal senescence marker, but bulk mRNA comparisons do not establish that some individual senescent cells do not express it. (LLM, conf=0.85)
Experimental — accuracy not yet measured
Senescent cells and their SASP exhibit variability contingent upon specific physiological context, stress, cell type, and tissue.
“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
The Results and Discussion report senescence signatures that vary by inducing stress and cell type, and genes encoding SASP factors that vary by cell type and time after induction. They also report variation associated with fibroblast tissue of origin, but do not establish tissue-dependent SASP variation or test variability across physiological contexts. No page numbers are available in our copy. (LLM, conf=0.86)
Experimental — accuracy not yet measured

Most studies have primarily focused on bulk analyses or primary senescence induced by specific stressors such as ionizing radiation or oncogene activation.
“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
The Results and Discussion says senescence-associated transcriptome programs had mainly been characterized in fibroblasts and describes datasets using oncogene activation and ionizing radiation to induce senescence. It does not establish that most senescence studies relied on bulk analyses, so that part of the broader claim is unsupported. (LLM, conf=0.82)
Experimental — accuracy not yet measured
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.
“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]
The Results and Discussion report distinct transcriptomic signatures in early, intermediate and late senescence, along with time-dependent changes in genes encoding SASP factors. This supports dynamic, sequential transcriptional changes, but the paper does not establish a hierarchy of transcriptional programmes or show that their activation controls the timing of senescence-associated phenotypes. (LLM, conf=0.82)
Experimental — accuracy not yet measured
Senescence patterns are variable across cell types, tissues, and inductions.
“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]
The Results and Discussion (page not provided) report senescence-signature differences by cell type and inducing stress. The analyses use cultured cells from different tissue origins, but do not establish variation across intact tissues, so the tissue portion of the claim is not directly supported. (LLM, conf=0.84)
Experimental — accuracy not yet measured
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 [44]
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.
“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
Senescent cells are heterogeneous because senescence is dynamic, expression profiles vary by cell lineage and triggering stress, and their roles differ by physiological context.
“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]
SASP gene expression changes over time.
“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]
Currently no specific marker of the senescent cell-cycle arrest has been identified.
“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
SASP strength and composition is regulated temporally.
“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
A central challenge in senescence research is the inherent heterogeneity within senescent cell populations.
“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
Senescence-associated phenotypes are temporal and early-stage senescent cells are phenotypically different from late-stage senescent cells.
“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]
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 [44]
The Results and Discussion describes the paper’s senescence transcriptome signatures, including a 55-gene core signature, but does not compare them with SenMayo. Searches for SenMayo, normalized enrichment scores, and senescent-cell clearance found no passage supporting the claimed performance comparison; page numbers were not available in our copy. (LLM, conf=0.76)
Experimental — accuracy not yet measured
Induction of p21 is crucial for initiation of senescence mediated growth arrest by different stimuli.
“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
No unique form of SASP is known to exist, and difficulty in identifying a general regulatory mechanism restricts its utility as an unequivocal marker for senescence.
“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
Senescence associated secretory phenotype is nonspecific, context dependent and highly heterogeneous, and can be regulated at multiple different levels.
“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
Attempts to distinguish between beneficial and pathological cell senescence at the proteome, transcriptome, and functional levels have not been successful to date.
“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]
Senescent cells acquire a senescence-associated secretory phenotype involving secretion of a wide range of soluble molecules.
“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]
Senescence and the SASP are dynamic phenotypes that change over time.
“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
Many global gene expression analyses to identify gene expression signatures of senescence have highlighted highly variable and heterogeneous profiles depending on cell of origin, mode of induction, and time after induction.
“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]
Genes involved in membrane trafficking and intercellular signaling, such as cell-cell adhesion molecules and cell-surface receptors, are upregulated in senescent cells.
“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 senescent cells, biosynthetic activity is decreased due to downregulation of genes required for DNA, RNA, and protein synthesis, as well as genes with a role in glucose and fatty acid metabolism.
“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]
DNA repair and chromatin organization genes are downregulated in senescent cells.
“DNA repair and chromatin organization genes are downregulated [133,139,140].”
From Mechanisms and Regulation of Cellular Senescence (2021) · cites this paper as [133]
Half of the genes differentially expressed by senescent fibroblasts, regardless of the senescence inducer, are not shared with quiescent cells.
“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]
Chromatin rearrangements affect the transcriptional program of senescent cells and contribute to their transcriptome diversity.
“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]
Senescent cells undergo extensive epigenome and chromatin organization changes that contribute to persistent proliferative arrest and progression to full senescence.
“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]
Senescent cell populations are generally highly heterogeneous in function of the cell type, the senescence-initiating insult, and the interactions within the microenvironment.
“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]
Bulk RNA-seq data from human and mouse fibroblasts demonstrate differences in transcriptomic signatures and SASPs based on senescence inducers, cell types, and stages of the senescence process.
“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]
Even in the case of senescence where multiple different senescent states have been defined, they are still modeled as discrete.
“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]
A 'core' senescence signature exists: a set of genes commonly differentially expressed in all senescent cells analyzed.
“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]
Neither p21WAF1/Cip1 nor p16INK4a are consistently upregulated across different types of senescent cells.
“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]
The SASP is highly complex and heterogeneous, with a composition influenced by many intrinsic and extrinsic factors.
“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]
Analysis and comparison of whole-transcriptome datasets allowed definition of gene sets that associate specifically with individual senescent subtypes.
“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]
A core senescence signature was previously identified based on fold change in expression compared to non-senescent tissues or cells and p-values > 0.05.
“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
Major
The 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.

1 of 1

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106 · cited 1× · see citing works
“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…”
The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration
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× · see citing works
“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.”
Method
The “Golden Age” of Probiotics: A Systematic Review and Meta-Analysis of Randomized and Observational Studies in Preterm Infants
Dermyshi, E., Wang, Y., Yan, C., Hong, W., Qiu, G., Gong, X., & Zhang, T. (2017) · Neonatology · doi:10.1159/000454668 · Cited by 24,577 · see citing works
The Hallmarks of Aging
López-Otín, C., Blasco, M. A., Partridge, L., Serrano, M., & Kroemer, G. (2013) · Cell · doi:10.1016/j.cell.2013.05.039 · Cited by 14,982 · see citing works
The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration
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) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2009.06.006 · Cited by 10,578 · see citing works
Oncogenic ras provokes premature cell senescence associated with accumulation of p53 and p16INK4a
Serrano, M., Lin, A. W., McCurrach, M. E., Beach, D., & Lowe, S. W. (1997) · Cell · doi:10.1016/s0092-8674(00)81902-9 · Cited by 5,178 · cited 2× · see citing works
“[2] (ID code: GSE64553) used five different strains of fibroblasts (BJ, WI-38, IMR90, HFF and MRC-5 cells) to study RS.”
BackgroundMethod
Naturally 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 2,891 · cited 1× · see citing works
“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].”
Background
The role of senescent cells in ageing
van Deursen, J. M. (2014) · Nature · doi:10.1038/nature13193 · Cited by 2,623 · cited 1× · see citing works
“However, most studies analyze senescent phenotypes 7–10 days after applying the senescence inducers [36, 37].”
Background
Cellular senescence in aging and age-related disease: from mechanisms to therapy
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× · see citing works
“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.”
Background
An Essential Role for Senescent Cells in Optimal Wound Healing through Secretion of PDGF-AA
Demaria, M., Ohtani, N., Youssef, S. A., Rodier, F., Toussaint, W., Mitchell, J. R., Laberge, R.-M., Vijg, J., Van Steeg, H., Dollé, M. E. T., et al. (2014) · Developmental Cell · doi:10.1016/j.devcel.2014.11.012 · Cited by 2,045 · see citing works
Self-citation
Senescence of activated stellate cells limits liver fibrosis
Krizhanovsky, V., Yon, M., Dickins, R. A., Hearn, S., Simon, J., Miething, C., Yee, H., Zender, L., & Lowe, S. W. (2008) · Cell · doi:10.1016/j.cell.2008.06.049 · Cited by 2,029 · see citing works
Senescence of Activated Stellate Cells Limits Liver Fibrosis
Krizhanovsky, V., Yon, M., Dickins, R. A., Hearn, S., Simon, J., Miething, C., Yee, H., Zender, L., & Lowe, S. W. (2008) · Cell · doi:10.1016/j.cell.2008.09.015 · Cited by 2,027
Cellular senescence mediates fibrotic pulmonary disease
Schafer, M. J., White, T. A., Iijima, K., Haak, A. J., Ligresti, G., Atkinson, E. J., Oberg, A. L., Birch, J., Salmonowicz, H., Zhu, Y., et al. (2017) · Nature Communications · doi:10.1038/ncomms14532 · Cited by 1,613 · cited 1× · see citing works
“To understand whether genes present in the core signature were differentially regulated in diseased and senescence-enriched tissues, we used an RNA sequencing (RNA-seq) dataset from lung tissues of patients with idiopathic pulmonary fibrosis, in which known senescence markers were detected [32].”
Method
Programmed cell senescence during mammalian embryonic development
Muñoz-Espín, D., Cañamero, M., Maraver, A., Gómez-López, G., Contreras, J., Murillo-Cuesta, S., Rodríguez-Baeza, A., Varela-Nieto, I., Ruberte, J., Collado, M., et al. (2013) · Cell · doi:10.1016/j.cell.2013.10.019 · Cited by 1,428 · cited 1× · see citing works
“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].”
Background
Cellular senescence promotes adverse effects of chemotherapy and cancer relapse
Demaria, M., O'Leary, M. N., Chang, J., Shao, L., Liu, S., Alimirah, F., Koenig, K., Le, C., Mitin, N., Deal, A. M., et al. (2017) · Cancer Discovery · doi:10.1158/2159-8290.cd-16-0241 · Cited by 1,338 · cited 1× · see citing works
“We induced senescence by various means, including those used in the previous analyses (ionizing radiation, replication, and oxidative stress), as well as doxorubicin, a DNA-damaging chemotherapeutic agent known to cause senescence [30]) (Figures S3A–S3D).”
MethodSelf-citation
Senescence is a developmental mechanism that contributes to embryonic growth and patterning
Storer, M., Mas, A., Robert-Moreno, A., Pecoraro, M., Ortells, M. C., Di Giacomo, V., Yosef, R., Pilpel, N., Krizhanovsky, V., Sharpe, J., et al. (2013) · Cell · doi:10.1016/j.cell.2013.10.041 · Cited by 1,186 · cited 1× · see citing works
“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].”
Background
Forging a signature of in vivo senescence
Sharpless, N. E., & Sherr, C. J. (2015) · Nature Reviews Cancer · doi:10.1038/nrc3960 · Cited by 1,104 · cited 4× · see citing works
“Many senescence-associated markers result from altered transcription, but the senescent phenotype is variable, and methods for clearly identifying senescent cells are lacking [10].”
BackgroundMethodInfluential
Directed elimination of senescent cells by inhibition of BCL-W and BCL-XL
Yosef, R., Pilpel, N., Tokarsky-Amiel, R., Biran, A., Ovadya, Y., Cohen, S., Vadai, E., Dassa, L., Shahar, E., Condiotti, R., et al. (2016) · Nature Communications · doi:10.1038/ncomms11190 · Cited by 1,032 · cited 1× · see citing works
“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 Hernandez-Segura et al.”
Background
The matricellular protein CCN1 induces fibroblast senescence and restricts fibrosis in cutaneous wound healing
Jun, J.-I., & Lau, L. F. (2010) · Nature Cell Biology · doi:10.1038/ncb2070 · Cited by 998 · see citing works
Differential roles for cyclin-dependent kinase inhibitors p21 and p16 in the mechanisms of senescence and differentiation in human fibroblasts.
Stein, G. H., Drullinger, L. F., Soulard, A., & Dulić, V. (1999) · Molecular and Cellular Biology · doi:10.1128/mcb.19.3.2109 · Cited by 868 · cited 1× · see citing works
“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].”
Background
mTOR regulates MAPKAPK2 translation to control the senescence-associated secretory phenotype
Herranz, N., Gallage, S., Mellone, M., Wuestefeld, T., Klotz, S., Hanley, C. J., Raguz, S., Acosta, J. C., Innes, A. J., Banito, A., et al. (2015) · Nature Cell Biology · doi:10.1038/ncb3225 · Cited by 788 · see citing works
ConsensusPathDB: toward a more complete picture of cell biology
Kamburov, A., Pentchev, K., Galicka, H., Wierling, C., Lehrach, H., & Herwig, R. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkq1156 · Cited by 671 · cited 1× · see citing works
“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].”
Background
ConsensusPathDB--a database for integrating human functional interaction networks
Kamburov, A., Wierling, C., Lehrach, H., & Herwig, R. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkn698 · Cited by 565 · cited 1× · see citing works
“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].”
Background
Senescence-Associated Secretory Phenotypes Reveal Cell-Nonautonomous Functions of Oncogenic RAS and the p53 Tumor Suppressor
Coppé, J.-P., Patil, C. K., Rodier, F., Sun, Y., Muñoz, D. P., Goldstein, J., Nelson, P. S., Desprez, P.-Y., & Campisi, J. (2008) · PLoS Biology · doi:10.1371/journal.pbio.0060301 · Cited by 302 · cited 1× · see citing works
“For example, upregulation of various components of the SASP has been reported to be dependent on the type of cell [24].”
BackgroundSelf-citation
Emerging roles of the p38 MAPK and PI3K/AKT/mTOR pathways in oncogene-induced senescence
Xu, Y., Li, N., Xiang, R., & Sun, P. (2014) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2014.04.004 · Cited by 282 · cited 13× · see citing works
“For example, upregulation of various components of the SASP has been reported to be dependent on the type of cell [24].”
BackgroundInfluential
A STAT3-mediated metabolic switch is involved in tumour transformation and STAT3 addiction
Demaria, M., Giorgi, C., Lebiedzińska, M., Esposito, G., D’Angeli, L., Bartoli, A., Gough, D. J., Turkson, J., Levy, D., Watson, C., et al. (2010) · Aging · doi:10.18632/aging.100232 · Cited by 277 · see citing works
Self-citation
Essential role for premature senescence of myofibroblasts in myocardial fibrosis
Meyer, K., Hodwin, B., Ramanujam, D., Engelhardt, S., & Sarikas, A. (2016) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2016.02.047 · Cited by 247 · see citing works
The cell fate: senescence or quiescence
Terzi, M. Y., Izmirli, M., & Gogebakan, B. (2016) · Molecular Biology Reports · doi:10.1007/s11033-016-4065-0 · Cited by 208 · cited 1× · see citing works
“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].”
Result
Therapeutic interventions for aging: the case of cellular senescence
Soto-Gamez, A., & Demaria, M. (2017) · Drug Discovery Today · doi:10.1016/j.drudis.2017.01.004 · Cited by 192 · cited 1× · see citing works
“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].”
BackgroundSelf-citation
Differential meta-analysis of RNA-seq data from multiple studies
Rau, A., Marot, G., & Jaffrézic, F. (2014) · BMC Bioinformatics · doi:10.1186/1471-2105-15-91 · Cited by 174 · cited 1× · see citing works
“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…”
Method
p38MAPK plays a crucial role in stromal-mediated tumorigenesis
Alspach, E., Flanagan, K. C., Luo, X., Ruhland, M. K., Huang, H., Pazolli, E., Donlin, M. J., Marsh, T., Piwnica-Worms, D., Monahan, J., et al. (2014) · Cancer Discovery · doi:10.1158/2159-8290.cd-13-0743 · Cited by 167 · see citing works
HIRA orchestrates a dynamic chromatin landscape in senescence and is required for suppression of neoplasia
Rai, T. S., Cole, J. J., Nelson, D. M., Dikovskaya, D., Faller, W. J., Vizioli, M. G., Hewitt, R. N., Anannya, O., McBryan, T., Manoharan, I., et al. (2014) · Genes & Development · doi:10.1101/gad.247528.114 · Cited by 162 · see citing works
Changes in the Transcriptome of Human Astrocytes Accompanying Oxidative Stress-Induced Senescence
Crowe, E. P., Tuzer, F., Gregory, B. D., Donahue, G., Gosai, S. J., Cohen, J., Leung, Y. Y., Yetkin, E., Nativio, R., Wang, L.-S., et al. (2016) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2016.00208 · Cited by 110 · cited 1× · see citing works
“The dataset from astrocytes was publicly available, and senescence was induced by oxidative stress [25] (Figure 2A).”
Method
Implications of time-series gene expression profiles of replicative senescence.
Kim, Y., Byun, H., Jee, B. A., Cho, H., Seo, Y., Kim, Y., Park, M. H., Chung, H., Woo, H. G., & Yoon, G. (2013) · Aging Cell · doi:10.1111/acel.12087 · Cited by 106 · cited 1× · see citing works
“The senescence phenotype, including the transcriptome, is highly dynamic, and not all the common senescence markers appear or persist simultaneously [34, 35].”
Background
Cellular senescence and tumor promotion: Is aging the key?
Loaiza, N., & Demaria, M. (2016) · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer · doi:10.1016/j.bbcan.2016.01.007 · Cited by 101 · cited 10× · see citing works
“Cellular senescence is a state of irreversibly arrested proliferation, often induced by genotoxic stress [1].”
BackgroundMethodInfluentialSelf-citation
Senescence as a general cellular response to stress: A mini-review
Fridlyanskaya, I., Alekseenko, L., & Nikolsky, N. (2015) · Experimental Gerontology · doi:10.1016/j.exger.2015.09.021 · Cited by 97 · cited 1× · see citing works
“An important contributor to the heterogeneity of the senescence program is the expression of cell-type-specific genes [23].”
Background
Conserved senescence associated genes and pathways in primary human fibroblasts detected by RNA-seq
Marthandan, S., Baumgart, M., Priebe, S., Groth, M., Schaer, J., Kaether, C., Guthke, R., Cellerino, A., Platzer, M., Diekmann, S., et al. (2016) · PLOS ONE · doi:10.1371/journal.pone.0154531 · Cited by 91 · cited 6× · see citing works
“The selected datasets covered 6 different fibroblast strains (BJ, IMR90, HFF, MRC5, WI38, and HCA-2) and 3 different senescence-inducing stimuli (replicative senescence [RS], oncogene-induced senescence [OIS], and ionizing radiation-induced senescence [IRIS]) and were generated by 5 independent laboratories (Figure 1A…”
BackgroundResultInfluential
Targeting senescent cells: possible implications for delaying skin aging: a mini-review
Velarde, M. C., & Demaria, M. (2016) · Gerontology · doi:10.1159/000444877 · Cited by 69 · cited 1× · see citing works
“However, most studies analyze senescent phenotypes 7–10 days after applying the senescence inducers [36, 37].”
BackgroundSelf-citation
POZ/BTB and AT-hook-containing zinc finger protein 1 (PATZ1) inhibits endothelial cell senescence through a p53 dependent pathway
Cho, J. H., Kim, M. J., Kim, K. J., & Kim, J.-R. (2012) · Cell Death & Differentiation · doi:10.1038/cdd.2011.142 · Cited by 59 · cited 2× · see citing works
“Among the known senescence-associated genes, we identified PATZ1, a transcriptional repressor that inhibits senescence [27], and CCND1, a regulatory subunit of CDK4 or CDK6 [29].”
Background
Differences in DNA repair capacity, cell death and transcriptional response after irradiation between a radiosensitive and a radioresistant cell line
Borràs-Fresneda, M., Barquinero, J.-F., Gomolka, M., Hornhardt, S., Rössler, U., Armengol, G., & Barrios, L. (2016) · Scientific Reports · doi:10.1038/srep27043 · Cited by 54 · cited 1× · see citing works
“To exclude the possibility that genes in our core signature were predictors of a general response to genotoxic stress, we interrogated published datasets that used mild forms of DNA damage ([31]; GEO:GSE80207).”
Method
Cyclin D1 overexpression permits the reproducible detection of senescent human vascular smooth muscle cells
BURTON, D. G. A., SHEERIN, A. N., OSTLER, E. L., SMITH, K., GILES, P. J., LOWE, J., RHYS‐WILLIAMS, W., KIPLING, D. G., & FARAGHER, R. G. A. (2007) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1404.026 · Cited by 49 · cited 3× · see citing works
“Among the known senescence-associated genes, we identified PATZ1, a transcriptional repressor that inhibits senescence [27], and CCND1, a regulatory subunit of CDK4 or CDK6 [29].”
Background
Similarities in Gene Expression Profiles duringIn VitroAging of Primary Human Embryonic Lung and Foreskin Fibroblasts
Marthandan, S., Priebe, S., Baumgart, M., Groth, M., Cellerino, A., Guthke, R., Hemmerich, P., & Diekmann, S. (2015) · BioMed Research International · doi:10.1155/2015/731938 · Cited by 47 · see citing works
Ciliary abnormalities in senescent human fibroblasts impair proliferative capacity
Breslin, L., Prosser, S. L., Cuffe, S., & Morrison, C. G. (2014) · Cell Cycle · doi:10.4161/15384101.2015.945868 · Cited by 39 · cited 1× · see citing works
“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 required for the G1/S transition [29].”
Background
Quantitative model of cell cycle arrest and cellular senescence in primary human fibroblasts
Schäuble, S., Klement, K., Marthandan, S., Münch, S., Heiland, I., Schuster, S., Hemmerich, P., & Diekmann, S. (2012) · PLoS ONE · doi:10.1371/journal.pone.0042150 · Cited by 35 · cited 1× · see citing works
“The senescence phenotype, including the transcriptome, is highly dynamic, and not all the common senescence markers appear or persist simultaneously [34, 35].”
Background

Flagged first, then by citations

1 of the 45 references couldn’t be matched to a known paper.

Sorted by citations

Inflammageing: chronic inflammation in ageing, cardiovascular disease, and frailty
Ferrucci, L., & Fabbri, E. (2018) · Nature Reviews Cardiology · doi:10.1038/s41569-018-0064-2 · Cited by 3,690 · see citing works
Cellular Senescence: Defining a Path Forward
Gorgoulis, V., Adams, P. D., Alimonti, A., Bennett, D. C., Bischof, O., Bishop, C., Campisi, J., Collado, M., Evangelou, K., Ferbeyre, G., et al. (2019) · Cell · doi:10.1016/j.cell.2019.10.005 · Cited by 3,225 · see citing works
Self-citation
Hallmarks of Cellular Senescence
Hernandez-Segura, A., Nehme, J., & Demaria, M. (2018) · Trends in Cell Biology · doi:10.1016/j.tcb.2018.02.001 · Cited by 2,605 · see citing works
“It is clear that the SASP has an important role in the pathophysiological activity of senescent cells, but it is too unspecific and heterogeneous to be used as an unequivocal marker for senescence [49,52].”
InfluentialSelf-citation
Cellular senescence in ageing: from mechanisms to therapeutic opportunities
Di Micco, R., Krizhanovsky, V., Baker, D., & d’Adda di Fagagna, F. (2021) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-020-00314-w · Cited by 2,277 · see citing works
Mechanisms of Cellular Senescence: Cell Cycle Arrest and Senescence Associated Secretory Phenotype
Kumari, R., & Jat, P. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.645593 · Cited by 1,622 · see citing works
A proteomic atlas of senescence-associated secretomes for aging biomarker development
Basisty, N., Kale, A., Jeon, O. H., Kuehnemann, C., Payne, T., Rao, C., Holtz, A., Shah, S., Sharma, V., Ferrucci, L., et al. (2020) · PLOS Biology · doi:10.1371/journal.pbio.3000599 · Cited by 1,348 · see citing works
“Transcriptome analysis of IR- and RAS-induced senescent fibroblasts were obtained from published studies [24,44] and combined.”
BackgroundMethodResultInfluentialSelf-citation
Single-Cell Transcriptomic Analysis of Human Lung Provides Insights into the Pathobiology of Pulmonary Fibrosis
Reyfman, P. A., Walter, J. M., Joshi, N., Anekalla, K. R., McQuattie-Pimentel, A. C., Chiu, S., Fernandez, R., Akbarpour, M., Chen, C.-I., Ren, Z., et al. (2019) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201712-2410oc · Cited by 1,203 · see citing works
“Therefore, we used the expression of 1,311 replicative senescence-associated genes to generate a senescence score for any individual cell and applied it to epithelial cells in our dataset (Figure 9B, see Figure 6 for a description of the clusters) (46).”
Method
Senescence and the SASP: many therapeutic avenues
Birch, J., & Gil, J. (2020) · Genes & Development · doi:10.1101/gad.343129.120 · Cited by 1,177 · see citing works
Cellular senescence and senolytics: the path to the clinic
Chaib, S., Tchkonia, T., & Kirkland, J. L. (2022) · Nature Medicine · doi:10.1038/s41591-022-01923-y · Cited by 1,105 · see citing works
A new gene set identifies senescent cells and predicts senescence-associated pathways across tissues
Saul, D., Kosinsky, R. L., Atkinson, E. J., Doolittle, M. L., Zhang, X., LeBrasseur, N. K., Pignolo, R. J., Robbins, P. D., Niedernhofer, L. J., Ikeno, Y., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-32552-1 · Cited by 1,060 · see citing works
Immunosenescence: molecular mechanisms and diseases
Liu, Z., Liang, Q., Ren, Y., Guo, C., Ge, X., Wang, L., Cheng, Q., Luo, P., Zhang, Y., & Han, X. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01451-2 · Cited by 1,023 · see citing works
“Senescence is not an acute transition but is progressive and phased from a temporary or reversible state to a chronic irreversible state.(163,194) Simple anti-senescence may not produce the expected therapeutic effects and can harm healthy tissues in elderly individuals.”
Background
Exploiting senescence for the treatment of cancer
Wang, L., Lankhorst, L., & Bernards, R. (2022) · Nature Reviews Cancer · doi:10.1038/s41568-022-00450-9 · Cited by 867 · see citing works
Unmasking senescence: context-dependent effects of SASP in cancer
Faget, D. V., Ren, Q., & Stewart, S. A. (2019) · Nature Reviews Cancer · doi:10.1038/s41568-019-0156-2 · Cited by 863 · see citing works
The senescence-associated secretory phenotype and its physiological and pathological implications
Wang, B., Han, J., Elisseeff, J. H., & Demaria, M. (2024) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-024-00727-x · Cited by 948 · see citing works
“It was also demonstrated that the production of SASP proteins follows the upregulation of their mRNAs, thus allowing the use of qPCR and later RNA sequencing for SASP identification 11,21 .”
Self-citation
Senescence and cancer — role and therapeutic opportunities
Schmitt, C. A., Wang, B., & Demaria, M. (2022) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-022-00668-4 · Cited by 794 · see citing works
Self-citation
The metabolic roots of senescence: mechanisms and opportunities for intervention
Wiley, C. D., & Campisi, J. (2021) · Nature Metabolism · doi:10.1038/s42255-021-00483-8 · Cited by 691 · see citing works
Self-citation
A guide to assessing cellular senescence in vitro and in vivo
González‐Gualda, E., Baker, A. G., Fruk, L., & Muñoz‐Espín, D. (2021) · The FEBS Journal · doi:10.1111/febs.15570 · Cited by 645 · see citing works
Role of p53 in the Regulation of Cellular Senescence
Mijit, M., Caracciolo, V., Melillo, A., Amicarelli, F., & Giordano, A. (2020) · Biomolecules · doi:10.3390/biom10030420 · Cited by 639 · see citing works
“Additionally, while a significant contribution to this heterogeneity was shown to be dependent on the different types of cells, time-series transcriptomic profiling studies also showed the expression of different genes at different times [64].”
Background
Aging and age‐related diseases: from mechanisms to therapeutic strategies
Li, Z., Zhang, Z., Ren, Y., Wang, Y., Fang, J., Yue, H., Ma, S., & Guan, F. (2021) · Biogerontology · doi:10.1007/s10522-021-09910-5 · Cited by 668 · see citing works
“The senescence-related secreted phenotype (SASP) and DNA damage are the main factors leading to senescence (Hernandez-Segura et al. 2017).”
Background
The dynamic nature of senescence in cancer
Lee, S., & Schmitt, C. A. (2019) · Nature Cell Biology · doi:10.1038/s41556-018-0249-2 · Cited by 588 · see citing works
The senescence-associated secretory phenotype and its regulation
Lopes-Paciencia, S., Saint-Germain, E., Rowell, M.-C., Ruiz, A. F., Kalegari, P., & Ferbeyre, G. (2019) · Cytokine · doi:10.1016/j.cyto.2019.01.013 · Cited by 601 · see citing works
The role of cellular senescence in ageing and endocrine disease
Khosla, S., Farr, J. N., Tchkonia, T., & Kirkland, J. L. (2020) · Nature Reviews Endocrinology · doi:10.1038/s41574-020-0335-y · Cited by 523 · see citing works
Strategies for targeting senescent cells in human disease
Gasek, N. S., Kuchel, G. A., Kirkland, J. L., & Xu, M. (2021) · Nature Aging · doi:10.1038/s43587-021-00121-8 · Cited by 501 · see citing works
Senescent cell clearance by the immune system: Emerging therapeutic opportunities
Prata, L. G. P. L., Ovsyannikova, I. G., Tchkonia, T., & Kirkland, J. L. (2018) · Seminars in Immunology · doi:10.1016/j.smim.2019.04.003 · Cited by 497 · see citing works
“The array of SASP factors appears to vary among SC types and with the stimuli that originally drove the cells into senescence [43].”
Background
Senescent Cells in Cancer Therapy: Friends or Foes?
Wang, B., Kohli, J., & Demaria, M. (2020) · Trends in Cancer · doi:10.1016/j.trecan.2020.05.004 · Cited by 508 · see citing works
“This is particularly important because of the heterogeneous phenotypes of the different senescence programs; for example, the dependence of SASP composition on the cell type [131,132].”
BackgroundSelf-citation
Mechanisms and consequences of endothelial cell senescence
Bloom, S. I., Islam, M. T., Lesniewski, L. A., & Donato, A. J. (2022) · Nature Reviews Cardiology · doi:10.1038/s41569-022-00739-0 · Cited by 512 · see citing works
Pan-cancer single-cell RNA-seq identifies recurring programs of cellular heterogeneity
Kinker, G. S., Greenwald, A. C., Tal, R., Orlova, Z., Cuoco, M. S., McFarland, J. M., Warren, A., Rodman, C., Roth, J. A., Bender, S. A., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-00726-6 · Cited by 445 · see citing works
Taurine deficiency as a driver of aging
Singh, P. P., Gollapalli, K., Mangiola, S., Schranner, D., Yusuf, M. A., Chamoli, M., Shi, S. L., Lopes-Bastos, B., Nair, T., Riermeier, A., et al. (2023) · Science · doi:10.1126/science.abn9257 · Cited by 447 · see citing works
Senescence atlas reveals an aged-like inflamed niche that blunts muscle regeneration
Moiseeva, V., Cisneros, A., Sica, V., Deryagin, O., Lai, Y., Jung, S., Andrés, E., An, J., Segalés, J., Ortet, L., et al. (2023) · Nature · doi:10.1038/s41586-022-05535-x · Cited by 423 · see citing works
A multidimensional systems biology analysis of cellular senescence in aging and disease
Avelar, R. A., Ortega, J. G., Tacutu, R., Tyler, E. J., Bennett, D., Binetti, P., Budovsky, A., Chatsirisupachai, K., Johnson, E., Murray, A., et al. (2020) · Genome Biology · doi:10.1186/s13059-020-01990-9 · Cited by 399 · see citing works
“Expedited by recent advances in genomic and transcriptomic sequencing, alongside high-throughput genetic screens, a wealth of publicly available data now exists which has furthered the understanding of senescence regulation [19, 20].”
Background
The landscape of aging
Cai, Y., Song, W., Li, J., Jing, Y., Liang, C., Zhang, L., Zhang, X., Zhang, W., Liu, B., An, Y., et al. (2022) · Science China Life Sciences · doi:10.1007/s11427-022-2161-3 · Cited by 436 · see citing works
Mechanisms and Regulation of Cellular Senescence
Roger, L., Tomas, F., & Gire, V. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms222313173 · Cited by 395 · see citing works
“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].”
BackgroundInfluential
Elimination of senescent cells by β-galactosidase-targeted prodrug attenuates inflammation and restores physical function in aged mice
Cai, Y., Zhou, H., Zhu, Y., Sun, Q., Ji, Y., Xue, A., Wang, Y., Chen, W., Yu, X., Wang, L., et al. (2020) · Cell Research · doi:10.1038/s41422-020-0314-9 · Cited by 397 · see citing works
Immune ageing at single-cell resolution
Mogilenko, D. A., Shchukina, I., & Artyomov, M. N. (2021) · Nature reviews. Immunology · doi:10.1038/s41577-021-00646-4 · Cited by 392 · see citing works
Biomarkers of aging
Bao, H., Cao, J., Chen, M., Min, C., Chen, W., Chen, X., Chen, Y., Chen, Y., Chen, Y., Chen, Z., et al. (2023) · Science China Life Sciences · doi:10.1007/s11427-023-2305-0 · Cited by 389 · see citing works
Guidelines for minimal information on cellular senescence experimentation in vivo
Ogrodnik, M., Carlos Acosta, J., Adams, P. D., d’Adda di Fagagna, F., Baker, D. J., Bishop, C. L., Chandra, T., Collado, M., Gil, J., Gorgoulis, V., et al. (2024) · Cell · doi:10.1016/j.cell.2024.05.059 · Cited by 376 · see citing works
Self-citation
Targeted Elimination of Senescent Beta Cells Prevents Type 1 Diabetes
Thompson, P. J., Shah, A., Ntranos, V., Van Gool, F., Atkinson, M., & Bhushan, A. (2019) · Cell Metabolism · doi:10.1016/j.cmet.2019.01.021 · Cited by 353 · see citing works
Transcriptome signature of cellular senescence
Casella, G., Munk, R., Kim, K. M., Piao, Y., De, S., Abdelmohsen, K., & Gorospe, M. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz555 · Cited by 359 · see citing works
“Due to this heterogeneity, finding broad biomarkers of senescence has been challenging (16,48) and senescent cells are currently found through the combined detection of multiple biochemical markers such as p16, p53, p21 and SA- Gal, despite the fact that they are not exclusively nor consistently induced in senescence…”
Background
Role of immune cells in the removal of deleterious senescent cells
Kale, A., Sharma, A., Stolzing, A., Desprez, P.-Y., & Campisi, J. (2020) · Immunity & Ageing · doi:10.1186/s12979-020-00187-9 · Cited by 351 · see citing works
“Further, events that disrupt mitochondrial function triggers a mitochondrial dysfunction-associated senescence (MiDAS) arrest [8], and oxidative stress [9, 10] and inhibitors of DNA methylases or histone deacetylases [6] also cause a senescence arrest (Fig.”
BackgroundSelf-citation
Therapy-Induced Senescence: Opportunities to Improve Anticancer Therapy
Prasanna, P. G. S., Citrin, D. E., Hildesheim, J., Ahmed, M. M., Venkatachalam, S., Riscuta, G., Xi, D., Zheng, G., van Deursen, J., Goronzy, J. J., et al. (2021) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djab064 · Cited by 351 · see citing works
“However, at the core of SnC heterogeneity, characterization of whole-transcriptome datasets seems to provide a fingerprint of 55 senescence-associated gene transcriptomes in fibroblasts (56).”
BackgroundSelf-citation
Hallmarks of senescence and aging
Dodig, S., Čepelak, I., & Pavić, I. (2019) · Biochemia Medica · doi:10.11613/bm.2019.030501 · Cited by 347 · see citing works
Senolytic Drugs: Reducing Senescent Cell Viability to Extend Health Span
Robbins, P. D., Jurk, D., Khosla, S., Kirkland, J. L., LeBrasseur, N. K., Miller, J. D., Passos, J. F., Pignolo, R. J., Tchkonia, T., & Niedernhofer, L. J. (2021) · Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-050120-105018 · Cited by 339 · see citing works
“Second, Sncs have different expression profiles based on their cell lineage as well as the type of stress that triggered senescence (31).”
Background
Senolytics reduce coronavirus-related mortality in old mice
Camell, C. D., Yousefzadeh, M. J., Zhu, Y., Prata, L. G. P. L., Huggins, M. A., Pierson, M., Zhang, L., O’Kelly, R. D., Pirtskhalava, T., Xun, P., et al. (2021) · Science · doi:10.1126/science.abe4832 · Cited by 320 · see citing works
Replicative senescence dictates the emergence of disease-associated microglia and contributes to Aβ pathology
Hu, Y., Fryatt, G. L., Ghorbani, M., Obst, J., Menassa, D. A., Martin-Estebane, M., Muntslag, T. A. O., Olmos-Alonso, A., Guerrero-Carrasco, M., Thomas, D., et al. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109228 · Cited by 298 · see citing works
SHP2 is required for growth of KRAS-mutant non-small-cell lung cancer in vivo
Mainardi, S., Mulero-Sánchez, A., Prahallad, A., Germano, G., Bosma, A., Krimpenfort, P., Lieftink, C., Steinberg, J. D., de Wit, N., Gonçalves-Ribeiro, S., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0023-9 · Cited by 320 · see citing works
Neuroinflammation in Alzheimer’s Disease
Onyango, I. G., Jauregui, G. V., Čarná, M., Bennett, J. P., & Stokin, G. B. (2021) · Biomedicines · doi:10.3390/biomedicines9050524 · Cited by 330 · see citing works
Skin Aging, Cellular Senescence and Natural Polyphenols
Csekes, E., & Račková, L. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms222312641 · Cited by 334 · see citing works
“However, senescence can also be induced prematurely as a consequence of direct and persistent DNA damage [15], oxidative stress [16], strong mitogenic signal, the inactivation of a tumor suppressor (such as phosphatase and tensin homolog (PTEN)) and/or oncogenes (such as Raf or BRAF) (so called oncogene-induced senesc…”
Background
Cells exhibiting strong p16 INK4a promoter activation in vivo display features of senescence
Liu, J.-Y., Souroullas, G. P., Diekman, B. O., Krishnamurthy, J., Hall, B. M., Sorrentino, J. A., Parker, J. S., Sessions, G. A., Gudkov, A. V., & Sharpless, N. E. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1818313116 · Cited by 306 · see citing works
“pulmonary fibrosis and atherosclerosis (36-38).”
Cellular senescence in development, regeneration and disease
Rhinn, M., Ritschka, B., & Keyes, W. M. (2019) · Development · doi:10.1242/dev.151837 · Cited by 296 · see citing works
Therapy-Induced Senescence: An “Old” Friend Becomes the Enemy
Saleh, T., Bloukh, S., Carpenter, V. J., Alwohoush, E., Bakeer, J., Darwish, S., Azab, B., & Gewirtz, D. A. (2020) · Cancers · doi:10.3390/cancers12040822 · Cited by 289 · see citing works
The heterogeneity of cellular senescence: insights at the single-cell level
Cohn, R. L., Gasek, N. S., Kuchel, G. A., & Xu, M. (2023) · Trends in Cell Biology · doi:10.1016/j.tcb.2022.04.011 · Cited by 294 · see citing works
A Senescence-Centric View of Aging: Implications for Longevity and Disease
Borghesan, M., Hoogaars, W. M. H., Varela-Eirin, M., Talma, N., & Demaria, M. (2020) · Trends in Cell Biology · doi:10.1016/j.tcb.2020.07.002 · Cited by 267 · see citing works
“The SASP is a highly heterogeneous program whose composition depends on various intrinsic and extrinsic factors [4,5].”
BackgroundSelf-citation
Cellular senescence in bone
Farr, J. N., & Khosla, S. (2019) · Bone · doi:10.1016/j.bone.2019.01.015 · Cited by 263 · see citing works
“Given that senescent cell-to-cell variability exists [14] and the known heterogeneity of the SASP of different types of senescent cells [12, 13], it will be important in future studies to determine the efficiency by which senotherapeutics, including those that selectively eliminate senescent cells (“senolytics”) or th…”
Background
Cellular senescence and Alzheimer disease: the egg and the chicken scenario
Saez-Atienzar, S., & Masliah, E. (2020) · Nature Reviews Neuroscience · doi:10.1038/s41583-020-0325-z · Cited by 257 · see citing works
HMGB2 Loss upon Senescence Entry Disrupts Genomic Organization and Induces CTCF Clustering across Cell Types
Zirkel, A., Nikolic, M., Sofiadis, K., Mallm, J.-P., Brackley, C. A., Gothe, H., Drechsel, O., Becker, C., Altmüller, J., Josipovic, N., et al. (2018) · Molecular Cell · doi:10.1016/j.molcel.2018.03.030 · Cited by 226 · see citing works
Chemotherapy Induces Senescence-Like Resilient Cells Capable of Initiating AML Recurrence
Duy, C., Li, M., Teater, M., Meydan, C., Garrett-Bakelman, F. E., Lee, T. C., Chin, C. R., Durmaz, C., Kawabata, K. C., Dhimolea, E., et al. (2021) · Cancer Discovery · doi:10.1158/2159-8290.cd-20-1375 · Cited by 253 · see citing works
“of senescence-associated genes are also expressed in quiescent cells, potentially indicating a mechanistic overlap between senescence and dormancy (71).”
Background
Cellular senescence at the crossroads of inflammation and Alzheimer's disease
Guerrero, A., De Strooper, B., & Arancibia-Cárcamo, I. L. (2021) · Trends in Neurosciences · doi:10.1016/j.tins.2021.06.007 · Cited by 236 · see citing works
Single-nuclear transcriptomics reveals diversity of proximal tubule cell states in a dynamic response to acute kidney injury
Gerhardt, L. M. S., Liu, J., Koppitch, K. A., Cippà, P. E., & McMahon, A. P. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2026684118 · Cited by 232 · see citing works
Senescence Rewires Microenvironment Sensing to Facilitate Antitumor Immunity
Chen, H.-A., Ho, Y.-J., Mezzadra, R., Adrover, J. M., Smolkin, R. M., Zhu, C., Woess, K., Bernstein, N., Schmitt, G., Fong, L. E., et al. (2022) · Cancer Discovery · doi:10.1158/2159-8290.cd-22-0528 · Cited by 230 · see citing works
Cellular senescence: the sought or the unwanted?
Sun, Y., Coppé, J.-P., & Lam, E. W.-F. (2018) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2018.08.002 · Cited by 208 · see citing works
Single-cell RNA sequencing identifies senescent cerebromicrovascular endothelial cells in the aged mouse brain
Kiss, T., Nyúl-Tóth, Á., Balasubramanian, P., Tarantini, S., Ahire, C., DelFavero, J., Yabluchanskiy, A., Csipo, T., Farkas, E., Wiley, G., et al. (2020) · GeroScience · doi:10.1007/s11357-020-00177-1 · Cited by 203 · see citing works
Transcriptional and epigenetic decoding of the microglial aging process
Li, X., Li, Y., Jin, Y., Zhang, Y., Wu, J., Xu, Z., Huang, Y., Cai, L., Gao, S., Liu, T., et al. (2023) · Nature Aging · doi:10.1038/s43587-023-00479-x · Cited by 225 · see citing works
Characterization of cellular senescence in aging skeletal muscle
Zhang, X., Habiballa, L., Aversa, Z., Ng, Y. E., Sakamoto, A. E., Englund, D. A., Pearsall, V. M., White, T. A., Robinson, M. M., Rivas, D. A., et al. (2022) · Nature Aging · doi:10.1038/s43587-022-00250-8 · Cited by 206 · see citing works
Cellular senescence: Molecular mechanisms and pathogenicity
Wei, W., & Ji, S. (2018) · Journal of Cellular Physiology · doi:10.1002/jcp.26956 · Cited by 205 · see citing works
The ageing kidney: Molecular mechanisms and clinical implications
Fang, Y., Gong, A. Y., Haller, S. T., Dworkin, L. D., Liu, Z., & Gong, R. (2020) · Ageing Research Reviews · doi:10.1016/j.arr.2020.101151 · Cited by 211 · see citing works
“4) may manifest in the ageing kidney as hypertrophy, binucleate, detachment, cytoplasmic resorption droplets, and foot processes effacement, in parallel with increased expression of SASP (Ortmann et al., 2004; Verzola et al., 2008), ultimately leading to podocytes depletion and age-related global glomerulosclerosis (W…”
Influential
The Cancer SENESCopedia: A delineation of cancer cell senescence
Jochems, F., Thijssen, B., De Conti, G., Jansen, R., Pogacar, Z., Groot, K., Wang, L., Schepers, A., Wang, C., Jin, H., et al. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109441 · Cited by 201 · see citing works
“This phenotype is heterogeneous and dynamic and depends not only on the senescence trigger, but also on the cell of origin (Basisty et al., 2020; Hernandez-Segura et al., 2017; Wiley et al., 2017).”
BackgroundResult
Single-cell analyses of aging, inflammation and senescence
Uyar, B., Palmer, D. H., Kowald, A., Escobar, H. M., Barrantes, I., Möller, S., Akalin, A., & Fuellen, G. (2020) · Ageing Research Reviews · doi:10.1016/j.arr.2020.101156 · Cited by 202 · see citing works
“Molecular identification of senescent cells is not trivial, since the senescent state induced by different triggers in different tissues displays a certain degree of heterogeneity (Hernandez-Segura et al., 2017).”
Cellular Senescence and Inflammaging in Age-Related Diseases
Olivieri, F., Prattichizzo, F., Grillari, J., & Balistreri, C. R. (2018) · Mediators of Inflammation · doi:10.1155/2018/9076485 · Cited by 200 · see citing works
“The field is rapidly expanding, and the information provided by new technologies, for example, single-cell RNAseq, is expected to provide more insights into the heterogeneity of SCs in order to facilitate the development of new senolytic drugs [35].”
Background
Senescent Cells: Emerging Targets for Human Aging and Age-Related Diseases
Song, S., Lam, E. W.-F., Tchkonia, T., Kirkland, J. L., & Sun, Y. (2020) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2020.03.008 · Cited by 195 · see citing works
“Senescent cells manifest a robust, profound, and stable proinflammatory secretory activity with the expression spectrum largely conserved between different cell types, cell states, and stress types, although there are variations in the SASP signature, a form of heterogeneity driven by certain unknown mechanism(s) [20].”
Background
Algorithmic assessment of cellular senescence in experimental and clinical specimens
Kohli, J., Wang, B., Brandenburg, S. M., Basisty, N., Evangelou, K., Varela-Eirin, M., Campisi, J., Schilling, B., Gorgoulis, V., & Demaria, M. (2021) · Nature Protocols · doi:10.1038/s41596-021-00505-5 · Cited by 196 · see citing works
Self-citation
Integrating cellular senescence with the concept of damage accumulation in aging: Relevance for clearance of senescent cells
Ogrodnik, M., Salmonowicz, H., & Gladyshev, V. N. (2019) · Aging Cell · doi:10.1111/acel.12841 · Cited by 184 · see citing works
Connecting aging biology and inflammation in the omics era
Walker, K. A., Basisty, N., Wilson, D. M., & Ferrucci, L. (2022) · Journal of Clinical Investigation · doi:10.1172/jci158448 · Cited by 189 · see citing works
“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.”
Background
Cellular senescence in cancer: from mechanisms to detection
Ou, H., Hoffmann, R. J., González‐López, C., Doherty, G. J., Korkola, J. E., & Muñoz‐Espín, D. (2020) · Molecular Oncology · doi:10.1002/1878-0261.12807 · Cited by 198 · see citing works
Clearance of therapy‐induced senescent tumor cells by the senolytic ABT‐263 via interference with BCL‐XL–BAX interaction
Saleh, T., Carpenter, V. J., Tyutyunyk‐Massey, L., Murray, G., Leverson, J. D., Souers, A. J., Alotaibi, M. R., Faber, A. C., Reed, J., Harada, H., et al. (2020) · Molecular Oncology · doi:10.1002/1878-0261.12761 · Cited by 190 · see citing works
Paracrine roles of cellular senescence in promoting tumourigenesis
Gonzalez-Meljem, J. M., Apps, J. R., Fraser, H. C., & Martinez-Barbera, J. P. (2018) · British Journal of Cancer · doi:10.1038/s41416-018-0066-1 · Cited by 183 · see citing works
Regulation of Survival Networks in Senescent Cells: From Mechanisms to Interventions
Soto-Gamez, A., Quax, W. J., & Demaria, M. (2019) · Journal of Molecular Biology · doi:10.1016/j.jmb.2019.05.036 · Cited by 175 · see citing works
“The heterogeneity of the senescent phenotype is exemplified by the intrinsic differences that distinguish each senescent program [33] and by the complex biological roles that senescent cells can cover, appearing at times even paradoxical: acting both as tumor suppressor or tumor promoter, limiting or exacerbating fibr…”
BackgroundSelf-citation
Tumor cell escape from therapy-induced senescence
Saleh, T., Tyutyunyk-Massey, L., Murray, G. F., Alotaibi, M. R., Kawale, A. S., Elsayed, Z., Henderson, S. C., Yakovlev, V., Elmore, L. W., Toor, A., et al. (2019) · Biochemical Pharmacology · doi:10.1016/j.bcp.2018.12.013 · Cited by 182 · see citing works
On the evolution of cellular senescence
Kowald, A., Passos, J. F., & Kirkwood, T. B. L. (2020) · Aging Cell · doi:10.1111/acel.13270 · Cited by 179 · see citing works
“…cells are quite heterogeneous regarding their transcriptional profile and SASP composition, depending on the original cell type and type of induction of cellular senescence (Coppe et al., 2010; Hernandez-Segura et al., 2017, 2018), which complicates a common recognition mechanism even more.”
Background
Hepatic stellate cell senescence in liver fibrosis: Characteristics, mechanisms and perspectives
Zhang, M., Salas, S. S., Damba, T., Borghesan, M., Demaria, M., & Moshage, H. J. (2021) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2021.111572 · Cited by 180 · see citing works
“Interestingly, the quest for senescence-specific gene expression signatures also revealed that besides changes in cell-cycle regulators, senescent cells exhibited changes in genes that appeared to be unrelated to growth arrest (Hernandez-Segura et al., 2017; Mason et al., 2004; Shelton et al., 1999).”
Self-citation
Obesity and hyperinsulinemia drive adipocytes to activate a cell cycle program and senesce
Li, Q., Hagberg, C. E., Silva Cascales, H., Lang, S., Hyvönen, M. T., Salehzadeh, F., Chen, P., Alexandersson, I., Terezaki, E., Harms, M. J., et al. (2021) · Nature Medicine · doi:10.1038/s41591-021-01501-8 · Cited by 178 · see citing works
Reduced subcutaneous adipogenesis in human hypertrophic obesity is linked to senescent precursor cells
Gustafson, B., Nerstedt, A., & Smith, U. (2019) · Nature Communications · doi:10.1038/s41467-019-10688-x · Cited by 182 · see citing works
Oxylipin biosynthesis reinforces cellular senescence and allows detection of senolysis
Wiley, C. D., Sharma, R., Davis, S. S., Lopez-Dominguez, J. A., Mitchell, K. P., Wiley, S., Alimirah, F., Kim, D. E., Payne, T., Rosko, A., et al. (2021) · Cell Metabolism · doi:10.1016/j.cmet.2021.03.008 · Cited by 173 · see citing works
“Senescence and the SASP are dynamic phenotypes that change over time (De Cecco et al., 2019; Hernandez-Segura et al., 2017).”
BackgroundSelf-citation
4D Genome Rewiring during Oncogene-Induced and Replicative Senescence
Sati, S., Bonev, B., Szabo, Q., Jost, D., Bensadoun, P., Serra, F., Loubiere, V., Papadopoulos, G. L., Rivera-Mulia, J.-C., Fritsch, L., et al. (2020) · Molecular Cell · doi:10.1016/j.molcel.2020.03.007 · Cited by 170 · see citing works
“, which are concordant with previously published GO analysis (Table S5) (Hernandez-Segura et al., 2017).”
Result
Cell-Free Osteoarthritis Treatment with Sustained-Release of Chondrocyte-Targeting Exosomes from Umbilical Cord-Derived Mesenchymal Stem Cells to Rejuvenate Aging Chondrocytes
Cao, H., Chen, M., Cui, X., Liu, Y., Liu, Y., Deng, S., Yuan, T., Fan, Y., Wang, Q., & Zhang, X. (2023) · ACS Nano · doi:10.1021/acsnano.3c01612 · Cited by 168 · see citing works
Overcoming the senescence‐associated secretory phenotype (SASP): a complex mechanism of resistance in the treatment of cancer
Chambers, C. R., Ritchie, S., Pereira, B., & Timpson, P. (2021) · Molecular Oncology · doi:10.1002/1878-0261.13042 · Cited by 172 · see citing works
Turning back time with emerging rejuvenation strategies
Mahmoudi, S., Xu, L., & Brunet, A. (2018) · Nature Cell Biology · doi:10.1038/s41556-018-0206-0 · Cited by 163 · see citing works
Why Senescent Cells Are Resistant to Apoptosis: An Insight for Senolytic Development
Hu, L., Li, H., Zi, M., Li, W., Liu, J., Yang, Y., Zhou, D., Kong, Q., Zhang, Y., & He, Y. (2022) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2022.822816 · Cited by 167 · see citing works
Cellular Senescence: From Mechanisms to Current Biomarkers and Senotherapies
Lucas, V., Cavadas, C., & Aveleira, C. A. (2023) · Pharmacological Reviews · doi:10.1124/pharmrev.122.000622 · Cited by 169 · see citing works
Cellular senescence in musculoskeletal homeostasis, diseases, and regeneration
Wan, M., Gray-Gaillard, E. F., & Elisseeff, J. H. (2021) · Bone Research · doi:10.1038/s41413-021-00164-y · Cited by 150 · see citing works
“Despite different pathways identified in mediating SnC cycle arrest, no consensus exists regarding the biomarkers of the SnCs.35 Generally, none of the commonly used senescence-associated markers are specific or universal for all cell types, making identification of SnCs challenging.”
BackgroundInfluential
Single-cell senescence identification reveals senescence heterogeneity, trajectory, and modulators
Tao, W., Yu, Z., & Han, J.-D. J. (2024) · Cell Metabolism · doi:10.1016/j.cmet.2024.03.009 · Cited by 147 · see citing works
FoxM1 repression during human aging leads to mitotic decline and aneuploidy-driven full senescence
Macedo, J. C., Vaz, S., Bakker, B., Ribeiro, R., Bakker, P. L., Escandell, J. M., Ferreira, M. G., Medema, R., Foijer, F., & Logarinho, E. (2018) · Nature Communications · doi:10.1038/s41467-018-05258-6 · Cited by 131 · see citing works
Immunosenescence and inflammaging: Mechanisms and role in diseases
Ajoolabady, A., Praticò, D., Tang, D., Zhou, S., Franceschi, C., & Ren, J. T. (2024) · Ageing Research Reviews · doi:10.1016/j.arr.2024.102540 · Cited by 160 · see citing works
The chemistry of senescence
Lozano-Torres, B., Estepa-Fernández, A., Rovira, M., Orzáez, M., Serrano, M., Martínez-Máñez, R., & Sancenón, F. (2019) · Nature Reviews Chemistry · doi:10.1038/s41570-019-0108-0 · Cited by 140 · see citing works
Senescence and the tumor-immune landscape: Implications for cancer immunotherapy
Chibaya, L., Snyder, J. T., & Ruscetti, M. A. (2022) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2022.02.005 · Cited by 138 · see citing works
Lysosomal control of senescence and inflammation through cholesterol partitioning
Roh, K., Noh, J., Kim, Y., Jang, Y., Kim, J., Choi, H., Lee, Y., Ji, M., Kang, D., Kim, M.-S., et al. (2023) · Nature Metabolism · doi:10.1038/s42255-023-00747-5 · Cited by 143 · see citing works
Identifying specific functional roles for senescence across cell types
(2024) · doi:10.1016/j.cell.2024.09.021 · Cited by 139 · see citing works
Graded regulation of cellular quiescence depth between proliferation and senescence by a lysosomal dimmer switch
Fujimaki, K., Li, R., Chen, H., Croce, K. D., Zhang, H. H., Xing, J., Bai, F., & Yao, G. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1915905116 · Cited by 130 · see citing works
“We found that a set of “senescence core signature” genes (19) show similar expression patterns in deep quiescence as in senescence, and that a gene-expression signature we developed to indicate cellular quiescence depth by comparing deep and shallow quiescent REF cells is able to correctly classify senescent and aging…”
Background
Secretion of leukotrienes by senescent lung fibroblasts promotes pulmonary fibrosis
Wiley, C. D., Brumwell, A. N., Davis, S. S., Jackson, J., Valdovinos, A., Calhoun, C., Alimirah, F., Castellanos, C. A., Ruan, R., Wei, Y., et al. (2019) · JCI Insight · doi:10.1172/jci.insight.130056 · Cited by 132 · see citing works
“demonstrated that, among the 55 genes of the senescence core signature that they have previously identified, 13 genes were differentially regulated at every time point and in every cell type (46).”
BackgroundSelf-citation
Targeting Senescent Cells for a Healthier Aging: Challenges and Opportunities
Song, S., Tchkonia, T., Jiang, J., Kirkland, J. L., & Sun, Y. (2020) · Advanced Science · doi:10.1002/advs.202002611 · Cited by 129 · see citing works
Senolytics for Cancer Therapy: Is All that Glitters Really Gold?
Carpenter, V. J., Saleh, T., & Gewirtz, D. A. (2021) · Cancers · doi:10.3390/cancers13040723 · Cited by 124 · see citing works
“The mRNA profiles of senescent cells are remarkably different from their proliferating or quiescent counterparts [13]; however, these senescence-associated transcriptional profiles are also heterogenous among senescent cells [15].”
BackgroundInfluential

FISH analysis reveals CDKN2A and IFNA14 co-deletion is heterogeneous and is a prominent feature of glioblastoma
Shboul, S. A., Boyle, S., Singh, A., Saleh, T., Alrjoub, M., Karsaneh, O. A. A., Mryyian, A., Dawoud, R., Gul, S., Baker, S. A., et al. (2023) · Brain Tumor Pathology · doi:10.1007/s10014-023-00473-6 · Cited by 8 · see citing works
Increased C-MYC copy numbers on the background of CDKN2A loss is associated with improved survival in nodular melanoma
Koynova, D. K., Jordanova, E. S., Kukutsch, N. A., et al. (2006) · Journal of Cancer Research and Clinical Oncology · doi:10.1007/s00432-006-0150-4 · Cited by 10 · see citing works
P16 immunohistochemistry is a sensitive and specific surrogate marker for CDKN2A homozygous deletion in gliomas
Vij, M., Cho, B. B., Yokoda, R. T., Rashidipour, O., Umphlett, M., Richardson, T. E., & Tsankova, N. M. (2023) · Acta Neuropathologica Communications · doi:10.1186/s40478-023-01573-2 · Cited by 40 · see citing works
CDKN2A mutations have equivalent prognostic significance to homozygous deletion in IDH-mutant astrocytoma
Yokoda, R. T., Cobb, W. S., Yong, R. L. M., Crary, J. F., Viapiano, M. S., Walker, J. M., Umphlett, M., Tsankova, N. M., & Richardson, T. E. (2023) · Journal of Neuropathology & Experimental Neurology · doi:10.1093/jnen/nlad063 · Cited by 13 · see citing works
F.3 Comprehensive multiplatform analysis of CDKN2A alterations in meningiomas
Wang, J., Patil, V., Liu, J., et al. (2023) · Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · doi:10.1017/cjn.2023.102

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)
DOI: 10.1016/j.cub.2017.07.033
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 · 2013: 1
FWCI: 27.39
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/open-access/userlicense/1.0/ (vor, 376 d)
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: Health Sciences › Medicine › Physiology › 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

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.

Claims read under definition version 3 (extract-v3) on 2026-09-28.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-09-28.

Cited sources are checked by gpt-6-sol.

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

Unmasking Transcriptional Heterogeneity in Senescent Cells

Abstract

Integrity signals

Claims the paper makes

Claims other papers make about this one

Self-check

Cites

Cited by

Related

Record

About these checks