SenCat: Cataloging human cell senescence through multi-omic profiling of multiple senescent primary cell types

Jun 11, 2026Molecular cell

SenCat: Cataloging human cell aging by analyzing multiple types of aged primary cells using different molecular data

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Longevity & Aging on OpenScience ↗PubMed ↗DOI ↗

Abstract

A catalog of senescence markers, termed SenCat, was created by profiling the transcriptomes and proteomes of 14 different primary human cell types.

Senescent cells from various primary cell types do not share a single unique marker.
Common metabolic and damage-response pathways are activated in senescent cells, which may be involved in tissue repair.
Machine-learning techniques improved the scoring and identification of senescence in multiple datasets from humans and mice.
SenCat can be utilized for identifying senescence across different cell types and tissues.

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There is an urgent need to comprehensively catalog senescence markers across cell types in an organism in order to characterize senescent-cell heterogeneity. Here, we profiled the transcriptomes and proteomes in 14 different primary human cell types undergoing over 30 senescence paradigms to create a senescence catalog we termed "SenCat." We found that while senescent cells from all primary cell types did not share a single unique marker, they did activate shared specific metabolic and damage-response pathways implicated in tissue repair. Moreover, machine-learning-refined SenCat signatures enabled senescence scoring and identification across multiple human and mouse datasets, both at bulk and single-cell levels. In sum, SenCat represents a much-needed resource to identify senescence across multiple cell types and tissues in the body.