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From binary senescence to state-resolved senotherapy in cancer: therapeutic windows from heterogeneity
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DOI：10.1016/j.arr.2026.103270.png)
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Abstract
En 中文
• Senescence is not binary because SASP programs are state dependent across contexts. • A function time space framework maps tumour senescence into an operational state space for decision making. • Phase aware rules are proposed to guide when to eliminate, remodel, or preserve senescent states. • Single cell, spatial, imaging, and circulating readouts are integrated to map senescent niches and track state transitions. • AI enabled scoring and forecasting are critically appraised to derive testable therapeutic windows for precision senotherapy.
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