Evidence mapPaperPMID 42410256Full record

ArticleThe EMBO journal2026

SenFlag gene signature identifies senescent cells in mouse and human tissues through a conserved core transcriptional program.

Abdullah Altulea, Sebastian Mackedenski, Jamil Nehme, Marco Demaria

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Article in The EMBO journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Abdullah AltuleaEuropean Research Institute for the Biology of Ageing (ERIBA), University Medical Center Groningen (UMCG), University of Groningen (RUG), Groningen, The Netherlands.ORCID http://orcid.org/0000-0001-6138-6486
Sebastian MackedenskiEuropean Research Institute for the Biology of Ageing (ERIBA), University Medical Center Groningen (UMCG), University of Groningen (RUG), Groningen, The Netherlands.ORCID http://orcid.org/0009-0004-2559-9803
Jamil NehmeEuropean Research Institute for the Biology of Ageing (ERIBA), University Medical Center Groningen (UMCG), University of Groningen (RUG), Groningen, The Netherlands.ORCID http://orcid.org/0000-0003-2771-2043
Marco DemariaEuropean Research Institute for the Biology of Ageing (ERIBA), University Medical Center Groningen (UMCG), University of Groningen (RUG), Groningen, The Netherlands. m.demaria@umcg.nl.ORCID http://orcid.org/0000-0002-8429-4813

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identifying senescent cells via single-cell transcriptome profiling data remains challenging due to cellular heterogeneity and overlap with other cellular states. Here, we present SenFlag, a streamlined gene signature for enhanced identification of senescent cells based on integration of core gene expression features. SenFlag was derived through systematic assessment of bulk and single-cell RNA-sequencing datasets across multiple senescence models. It captures a conserved transcriptional program characterized by reduced expression of proliferation-associated genes and chromatin-associated genes (HMGB1/2, HMGN2), combined with upregulation of cell-cycle inhibitors (CDKN1A/CDKN2A) and of CCND1. Additionally, SenFlag incorporates lysosomal features, including increased expression of V-ATPase subunits and cathepsins. SenFlag identifies a rare but progressively accumulating population of senescent cells across tissues in both mice and humans in vivo, with enrichment in epithelial and endothelial compartments. SenFlag-positive cells increase with age and following tissue injury, and are reduced in datasets involving senescence-targeting interventions, supporting its specificity in vivo. Together, SenFlag provides a robust and interpretable signature for identifying senescent cells in single-cell datasets and facilitates the study of senescence across physiological and pathological contexts.

Indexed as

Cellular SenescenceGene Expression ProfilingTranscriptomeAnimalsHumansMiceSingle-Cell AnalysisSingle-Cell Gene Expression Analysis

Identifiers

PMID42410256
PMCPMC13433995

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.