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

Molecular Cell 2026 Open access

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Authors: Carlos Anerillas, Gisela Altés, Katarína Grešová, Dimitrios Tsitsipatis, Krystyna Mazan-Mamczarz, Reema Banarjee, Ana S.G. Cunningham, Martin Salamini-Montemurri, Jen‐Hao Yang, Rachel Munk, Martina Rossi, Yulan Piao
+17 more Bradley Olinger, Quinn Strassheim, Jennifer L. Martindale, Jinshui Fan, Chang-Yi Cui, Supriyo De, Delaney Rutherford, Ying Hao, Z Li, Jessica Roberts, Yue Andy Qi, Kotb Abdelmohsen, Rafael de Cabo, Allison B. Herman, Manolis Maragkakis, Nathan Basisty, Myriam Gorospe
DOI: 10.1016/j.molcel.2026.05.017
Cited by: 4
References: 41

Abstract

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.

Fields of Study & Subjects

Telomeres Telomerase and Senescence Single-cell and spatial transcriptomics Cell Image Analysis Techniques

Publication details

Journal / source
Molecular Cell
Publisher
Elsevier BV
Volume
86
Issue
13
Pages
2605–2616.e8
Publication date
11 June 2026
Language
EN