bioRxivCell BiologyPreprint
Senescence-Linked Fibrosis in the Aging Human Ovary Revealed by p16-Based Histological Profiling and Spatial Transcriptomics
Mark A. Watson, Pooja Raj DevrukhkariD, Natalia Murad, Fan WuiD, Moo Joong Kim, Hannah AnvariiD, Uyen TraniD, Nicholas G. MartiniD, Tommy TraniD, Giuliana Zaza, Kevin SchneideriD, Bikem SoyguriD, Elisheva D. ShanesiD, Denis WirtziD, Mary Ellen PavoneiD, Simon MeloviD, Pei-Hsun WuiD, David FurmaniD, Francesca E. DuncaniD, Birgit SchillingiD
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 p16INK4a 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.
- organism: human
- assay: spatial transcriptomics
- assay: imaging
- research focus: cell type annotation
- research focus: differential expression
- research focus: cell-cell communication
- approach: deep learning
- Citations
- 6
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