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

Carlos Anerillas, Gisela Altés, Katarina Gresova, Dimitrios Tsitsipatis, Krystyna Mazan-Mamczarz, Reema Banarjee, Ana S G Cunningham, Martin Salamini-Montemurri, Jen-Hao Yang, Rachel Munk, Martina Rossi, Yulan Piao, Bradley Olinger, Quinn Strassheim, Jennifer L Martindale, Jinshui Fan, Chang-Yi Cui, Supriyo De, Delaney V Rutherford, Ying Hao, Ziyi Li, Jessica Roberts, Yue Andy Qi, Kotb Abdelmohsen, Rafael de Cabo, Allison B Herman, Manolis Maragkakis, Nathan Basisty, Myriam Gorospe

Laboratory of Genetics and Genomics, National Institute on Aging Intramural Research Program (NIA IRP), National Institutes of Health (NIH), Baltimore, MD, USA; Tissue and Organ Homeostasis Program, Centro de Biología Molecular Severo Ochoa (CBM), Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain; Instituto Aragonés de Ciencias de la Salud (IACS) and Fundación Agencia Aragonesa para la Investigación y el Desarrollo (ARAID), Zaragoza, Spain. Electronic address: [email protected]. · pubmed

Paper

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.

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Research summary

The authors constructed a multi-omic catalog of senescence markers across 14 primary human cell types to identify shared metabolic and damage-response pathways, providing a foundational resource for senescence research. This work is relevant because senescent cell accumulation is a recognized root cause of aging, and characterizing these cells is essential for developing senolytics or senomorphics; however, the impact is limited as it is primarily a descriptive resource generation study rather than a mechanistic breakthrough or therapeutic intervention.

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