作者
Samantha Guinn,Benedict Kinny‐Köster,Joseph A. Tandurella,Jacob T. Mitchell,Dimitrios N. Sidiropoulos,Melanie Loth,Melissa R. Lyman,Alexandra B. Pucsek,Daniel J. Zabransky,Jae W. Lee,Emma Kartalia,Mili Ramani,Toni T. Seppälä,Christopher Cherry,Reecha Suri,Haley Zlomke,Jignasha Patel,Jin He,Christopher L. Wolfgang,Jun Yu,Lei Zheng,David P. Ryan,David T. Ting,Alec C. Kimmelman,Anuj Gupta,Ludmila Danilova,Jennifer H. Elisseeff,Laura D. Wood,Genevieve Stein-O’Brien,Luciane T. Kagohara,Elizabeth M. Jaffee,Richard A. Burkhart,Elana J. Fertig,Jacquelyn W. Zimmerman
摘要
Abstract Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy characterized by an immunosuppressive tumor microenvironment enriched with cancer-associated fibroblasts (CAF). This study used a convergence approach to identify tumor cell and CAF interactions through the integration of single-cell data from human tumors with human organoid coculture experiments. Analysis of a comprehensive atlas of PDAC single-cell RNA sequencing data indicated that CAF density is associated with increased inflammation and epithelial–mesenchymal transition (EMT) in epithelial cells. Transfer learning using transcriptional data from patient-derived organoid and CAF cocultures provided in silico validation of CAF induction of inflammatory and EMT epithelial cell states. Further experimental validation in cocultures demonstrated integrin beta 1 (ITGB1) and vascular endothelial factor A (VEGFA) interactions with neuropilin-1 mediating CAF-epithelial cell cross-talk. Together, this study introduces transfer learning from human single-cell data to organoid coculture analyses for experimental validation of discoveries of cell–cell cross-talk and identifies fibroblast-mediated regulation of EMT and inflammation. Significance: Adaptation of transfer learning to relate human single-cell RNA sequencing data to organoid-CAF cocultures facilitates discovery of human pancreatic cancer intercellular interactions and uncovers cross-talk between CAFs and tumor cells through VEGFA and ITGB1.