Therapy-associated remodeling of pancreatic cancer revealed by single-cell spatial transcriptomics and optimal transport analysis
Shiau, C.; Cao, J.; Gregory, M. T.; Gong, D.; Yin, X.; Cho, J.-W.; Wang, P. L.; Su, J.; Wang, S.; Reeves, J. W.; Kim, T. K.; Kim, Y.; Guo, J. A.; Lester, N. A.; Schurman, N.; Barth, J. L.; Weissleder, R.; Jacks, T.; Qadan, M.; Hong, T. S.; Wo, J. Y.; Roberts, H.; Beechem, J. M.; Fernandez-del Castillo, C.; Mino-Kenudson, M.; Ting, D. T.; Hemberg, M.; Hwang, W. L.
Show abstract
In combination with cell intrinsic properties, interactions in the tumor microenvironment modulate therapeutic response. We leveraged high-plex single-cell spatial transcriptomics to dissect the remodeling of multicellular neighborhoods and cell-cell interactions in human pancreatic cancer associated with specific malignant subtypes and neoadjuvant chemotherapy/radiotherapy. We developed Spatially Constrained Optimal Transport Interaction Analysis (SCOTIA), an optimal transport model with a cost function that includes both spatial distance and ligand-receptor gene expression. Our results uncovered a marked change in ligand-receptor interactions between cancer-associated fibroblasts and malignant cells in response to treatment, which was supported by orthogonal datasets, including an ex vivo tumoroid co-culture system. Overall, this study demonstrates that characterization of the tumor microenvironment using high-plex single-cell spatial transcriptomics allows for identification of molecular interactions that may play a role in the emergence of chemoresistance and establishes a translational spatial biology paradigm that can be broadly applied to other malignancies, diseases, and treatments.
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