Pixel-Level Clustering of Hematoxylin-Eosin-Stained Sections of Mouse and Human Biliary Tract Cancer.

ABSTRACT: We previously established mouse models of biliary tract cancer (BTC) based on the injection of cells with biliary epithelial stem cell properties derived from KRAS(G12V)-expressing organoids into syngeneic mice. The resulting mouse tumors appeared to recapitulate the pathological features of human BTC. Here we analyzed images of hematoxylin and eosin (H&E) staining for both the mouse tumor tissue and human cholangiocarcinoma tissue by pixel-level clustering with machine learning. A pixel-clustering model that was established via training with mouse images revealed homologies of tissue structure between the mouse and human tumors, suggesting similarities in tumor characteristics independent of animal species. Analysis of the human cholangiocarcinoma tissue samples with the model also reveal

SUBMITTER: Inoue H 

PROVIDER: S-EPMC9775647 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature