衰老
生物
转录组
纤维化
卵巢
细胞生物学
细胞衰老
癌症研究
细胞外基质
病理
基因表达谱
卵巢皮质
中国仓鼠卵巢细胞
毛茛
作者
Mark A Watson,Pooja Raj Devrukhkar,Natalia F. Murad,Fan Wu,Moo Joong Kim,Hannah Anvari,Uyen Tran,Nicholas Martin,Tommy Tran,Giuliana Zaza,Kevin Schneider,Bikem Soygur,Elisheva D Shanes,Denis Wirtz,Mary Ellen G. Pavone,Simon Melov,Pei-Hsun Wu,David Furman,Francesca E Duncan,Birgit Schilling
标识
DOI:10.64898/2025.12.03.692228
摘要
Abstract Cellular senescence is implicated as a driver of ovarian aging, but senescent cells in the human postmenopausal ovary remain poorly defined. Using spatially resolved p16 INK 4a protein expression, a canonical senescence marker, we identified and mapped senescent cells in postmenopausal ovaries. We integrated p16 immunohistochemistry, multiplexed immunofluorescence, spatial transcriptomics, and AI-guided digital pathology to map senescent microenvironments. p16-positive cells formed discrete stromal, vascular, and cyst-associated clusters that increased with age and were enriched for macrophages and myofibroblast-like cells. Wholetranscriptome profiling of 92 spatial regions uncovered a 32-gene p16-associated signature, BuckSenOvary, that distinguished p16-positive regions across cortex and medulla. BuckSenOvary is characterized by suppression of cell-cycle regulators and activation of inflammatory and extracellular-matrix remodelling genes. AI-based collagen matrix analysis confirmed that p16-positive regions exhibit more architecturally complex collagen, demonstrating that focal senescent microenvironments are fibro-inflammatory. These findings position senescent ovarian niches as therapeutic targets to preserve ovarian function.
科研通智能强力驱动
Strongly Powered by AbleSci AI