Organoids for modeling cellular senescence and age-related pathology: From experimental reconstruction to mechanistic and translational applications.

Authors

Zhonglu Yang, Huifang Sun, Fan Zhang, Wei Ji, Youde Liang, Min Wang, Mingdong Yan, Zifan Zhao, Liangliang Fu

Published in

Ageing research reviews. Pages 103408. Oct 08, 2026. Epub Oct 08, 2026.

Abstract

Cellular senescence, characterized by irreversible cell cycle arrest and the acquisition of a senescence-associated secretory phenotype (SASP), is a fundamental hallmark of aging and a key driver of numerous age-related diseases. However, conventional two-dimensional cell cultures and animal models fail to fully replicate the complex cellular architecture, multicellular interactions, and tissue-specific microenvironments in which senescence develops in vivo. Organoids, three-dimensional tissue models derived from pluripotent or adult stem cells, have emerged as physiologically relevant platforms that recapitulate selected aspects of human tissue organization, cellular diversity, and functional characteristics. These features make organoids well suited for investigating the mechanisms, dynamics, and pathological consequences of cellular senescence. In this review, we summarize recent advances in organoid-based models for senescence research, highlighting their physiological relevance, strategies for organoid generation, approaches for inducing and characterizing senescence, and their applications in modeling age-related diseases. We further discuss the emerging roles of organoids in senescence-targeted drug discovery, regenerative medicine, and precision therapeutics. While organoids provide experimentally tractable platforms for dissecting the biology of cellular senescence and accelerating the development of therapeutic strategies for aging and age-related diseases, their capacity to fully recapitulate the complexity of human aging remains limited. Future advances in vascularization, immune integration, multi-organ systems, spatial multi-omics, and artificial intelligence-assisted analyses may help address these limitations and further enhance the physiological relevance and translational potential of organoid-based models.

PMID:
42849758
Bibliographic data and abstract were imported from PubMed on 09 Oct 2026.

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