⚠️ Auto-extracted by Claude on 2026-06-13 — preprint; not peer-reviewed. Content sourced exclusively from the verbatim abstract (biorxiv doi:10.1101/2025.11.14.688272). No primary-data results, gene lists, quantitative figures, or section content have been inferred beyond the abstract. Do NOT rely on any quantitative specifics from this page until a full-text verification pass is completed. gap/preprint-not-peer-reviewed gap/no-fulltext-access

Cherqui et al. 2025 — Single-cell quantification of senescence burden across organs

Preprint (bioRxiv), posted 2025-11-14. doi:10.1101/2025.11.14.688272. Authors: Cherqui U, Sopher I-R, Akiva H, Menahem O, Kopitman E, Blecher-Gonen R, Keren-Shaul H, Rachmian N, Mayo A, Alon U, Gal H, Krizhanovsky V — Weizmann Institute of Science, Israel (Krizhanovsky lab). Not a SenNet consortium paper.

Access: Preprint; bioRxiv open access. Not yet peer-reviewed or journal-published as of seeding date.


What this paper is

A primary data preprint from the Krizhanovsky laboratory at the Weizmann Institute. It introduces a novel single-cell, protein-level methodology for quantifying senescent cells simultaneously across multiple tissues in mice and in human PBMCs. This is distinct from the 2026 NIH SenNet Perspective (suryadevara-2026-senotypes) — it is an independent empirical study from a different institution providing quantitative data on senescence accumulation dynamics.

The paper is a contemporaneous empirical contribution to the senescence-heterogeneity framework. Its findings provide direct quantitative grounding for the tissue-specificity claim in the senotype framework, complementing the SenNet conceptual framing.


Model systems

  • Mouse tissues (multi-organ; specific organ identities not confirmed from abstract alone) — gap/preprint-not-peer-reviewed; enumeration of specific tissues requires full-text
  • Human PBMCs — peripheral blood mononuclear cells as the human data component

Key methodological contribution

Per the abstract, the paper introduces “the first, single-cell, protein-level approach, combining multiple senescence markers for the identification and quantification of senescent cells across multiple tissues.” Prior methods relied on bulk-tissue assays or single-marker approaches; this multi-marker protein-level, single-cell protocol enables simultaneous cross-tissue comparison.

The senescent cells identified by this protein-level approach were validated by showing they also “displayed transcriptomic senescence signatures” — providing “a direct molecular link between protein- and mRNA-level detection of senescence.” This cross-modality validation is a key methodological quality claim.


Central findings (abstract only)

Per the verbatim abstract, applying this method revealed:

  1. Widespread but heterogeneous changes in senescence marker expression across cell types and tissues — senescence accumulation is not uniform.
  2. Intra-organ coordination: senescence accumulation was “strongly coordinated within organs” — cell types within the same organ show correlated senescence dynamics.
  3. Inter-organ uncoupling: senescence accumulation “showed little correlation across” different organs — tissue-specific progression of aging, not a systemic synchronous process.
  4. Tissue-specific progression of ageing as a supported conclusion from the above two findings.
  5. The methodology provides “a framework for evaluating diverse therapeutic interventions.”

Critical caveat: The specific quantitative values underlying these findings (cell counts, marker levels, correlation coefficients, organ-specific rates) are NOT available from the abstract and must NOT be inferred. They require full-text verification before being cited on any atomic wiki page.


Significance for the senotype framework

This paper provides the cell-type- and organ-level empirical foundation for the tissue-specificity arm of the senotype concept. The SenNet Perspective (suryadevara-2026-senotypes) argues conceptually that senotypes are tissue-specific; Cherqui 2025 provides the quantitative coordination / uncorrelation evidence across organs that makes tissue-specificity an empirically measurable property, not just a conceptual claim.

Key import:

  • The finding that intra-organ senescence is coordinated (but inter-organ senescence is uncorrelated) implies that aging progresses as a tissue-autonomous process — the cellular aging clock runs at different speeds and via different cell types in different organs.
  • This directly challenges models of aging as a systemically synchronized (e.g., blood-borne factor-driven) process, and supports the view that targeted, tissue-specific interventions may be more appropriate than systemic approaches.
  • The framework for evaluating therapeutic interventions implies that the methodology could be used to assess whether a given senolytic or senomorphic reduces senescence burden in a tissue-specific, cell-type-specific manner.

Limitations

  • Preprint status — not yet peer-reviewed; results should be weighted accordingly. gap/preprint-not-peer-reviewed
  • Abstract-only extraction — quantitative specifics, detailed organ enumeration, and mechanistic claims in the body of the paper are not available for this seeding pass. gap/no-fulltext-access
  • Mouse tissue data require extrapolation to humans (human PBMCs are included but are a single compartment).
  • Multi-marker senescence identification methodology not yet independently replicated by another lab.

Cross-references

  • cellular-senescence — primary atomic home; see § Senescent-cell heterogeneity and the senotype concept
  • suryadevara-2026-senotypes — companion SenNet Perspective; conceptual senotype framework that this study empirically informs
  • freizus-2025-atp6v1b2-persistent-senescence — companion Krizhanovsky-lab preprint on the csV1B2-marked persistent subset
  • sasp — SASP heterogeneity is one dimension of the senotype variation characterized across tissues
  • senolytics — the tissue-specific aging-progression finding has implications for senolytic trial design and tissue targeting