bioRxivCancer BiologyPreprint
Spatial multi-omics resolve epithelium-fibroblast gradients and highlight NESTIN-NOTCH1-expressing subepithelial fibroblasts during human pancreatic tumorigenesis
Maëlle Batardière, Myriam Iliana Ibanez-RiosiD, Abdelhakim KhellafiD, Elham Dianati, Sarah-Slim DiwaniD, Maxence PellouxiD, Alexandre Archambault-MarsaniD, Camille Beaussier, Jade Diwan, Sasha Sapon-CousineauiD, Jumanah BaigiD, Shoukari Ayman, Zean Ghanmeh, Zhiyuan Yang, Melisa Farias Gonzalez, Jia-Lin Li, Ali KassabiD, Leonardo LandóiD, Philippe LefrançoisiD, Simon TurcotteiD, Youngmin A. LeeiD, Simon F. RoyiD, Mahdi S. HosseiniiD, Basile Tessier‐CloutieriD, Marcus Chuan Beng TaniD, , Vincent Quoc‐Huy TrinhiD
Abstract
Intraductal papillary mucinous neoplasms (IPMNs) are cystic precursors of pancreatic ductal adenocarcinoma undergoing dynamic epithelial and stromal remodeling during progression. In this study, we integrated computational pathology, cyclic immunofluorescence, and Xenium spatial transcriptomics to define the spatial organization of the IPMN microenvironment. We queried cell-based histopathological features and identified stromal patterns strongly associated with epithelium proximity. Cyclic immunofluorescence and Xenium revealed a subepithelial gradient extending from myofibroblasts to inflammatory fibroblasts. Xenium further identified a distinct subepithelial NOTCH1-NESTIN-expressing fibroblast subset in myofibroblasts that expands with tumor progression. By recapitulating the spatial remodeling event using human pancreatic tumor cells and primary myofibroblast co-culture models, we demonstrated the capacity of pancreatic tumor cells to induce a NESTIN-expressing state in neighboring myofibroblasts. These findings reveal new dynamic epithelial-stromal interactions through subepithelial NESTIN+ fibroblasts associated with pancreatic tumorigenesis and immediate microenvironment remodeling by active tumor cells, highlighting the power of computational pathology integrated with spatial transcriptomics.
- organism: human
- assay: spatial transcriptomics
- research focus: cell-cell communication
- research focus: spatial domain detection
- approach: deep learning
- approach: statistical model
- Citations
- 0
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