Cell type-centric interaction networks define spatial architecture of intrahepatic cholangiocarcinoma
Lee, H.-P.; Liu, M.; Wu, W.; Nguyen, N. T. L.; Chaisaingmongkol, J.; Castven, D.; Levy, E.; Kedei, N.; Hernandez, M. O.; Kundu, M.; Forgues, M.; Hung, M.-H.; Budhu, A.; Alani, N.; Hewitt, S. M.; Lake, R.; Ruppin, E.; Lipkowitz, S.; Wang, X. W.; Marquardt, J. U.; Ruchirawat, M.; Ma, L.
Show abstract
Tumor spatial organization critically shapes disease progression and therapeutic response, yet remains poorly defined. Intrahepatic cholangiocarcinoma (iCCA), a rare and aggressive liver malignancy with extensive stromal and immune remodeling, provides a compelling model to study tumor architecture. We generated a single-cell spatial atlas of 1 million cells from 131 iCCA patients using 53-plex spatial proteomics. To systemically characterize tumor spatial organization, we developed a graph-based deep learning framework to define cell type-centric interaction networks, identifying 41 distinct multicellular spatial patterns. Integration of these networks revealed higher-order tumor- and immune-enriched microenvironments associated with patient outcomes. Notably, neutrophil-associated tumor-enriched and tumor-desert microenvironments delineated patient groups with opposing clinical outcomes and distinct neutrophil states. These findings were validated by single-cell spatial transcriptomic profiling of 6 million cells from 162 iCCA patients. Together, this study defines the spatial architecture of iCCA and provides a comprehensive resource for exploring tumor spatial organization.
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