Fig 1: Distinct mesenchymal phenotypes and transcriptional state-specific immune heterogeneity exist in the liver metastatic microenvironment(A) t-SNE visualization of non-malignant cells identified in the metastatic microenvironment, abbreviations as in Figure S1J (TAM, tumor associated macrophage).(B) Expression of Fibroblast-like (PC2 low) and Pericyte-like (PC2 high) mesenchymal (Mes.) cell programs across different metastatic sites (top).(C) Density plots for mesenchymal cell phenotype score in single cells from our metastatic cohort (top) or previously published PDAC bulk RNA-seq profiles (bottom), fill indicates anatomic site. P-value determined by Student’s t test (top) or by ANOVA followed by Tukey’s HSD (bottom).(D) Summary of mesenchymal phenotypes in primary versus liver metastatic PDAC.(E) Correlation between microenvironment diversity (Simpson’s index, x axis) and the average malignant scBasal-scClassical commitment score (y axis) for each scRNA-seq sample.(F) Correlation between TME diversity as inferred by immunogenic signature score (x axis) versus average tumor scBasal-scClassical commitment score (y axis) in primary and metastatic bulk RNA-seq samples.(G and H) Sample-level (columns) variation in Simpson’s index (G, dot plot), average malignant scBasal-scClassical (G, top heat bar) and IC (G, bottom heat bar) expression, and fraction of non-malignant cell types (H). Samples were clustered and ordered within metastatic site (liver versus other) by their fractional representation of cell types. Dots indicate top statistically significant cell type frequency differences calculated using a Kruskal-Wallis test with multiple hypothesis correction.(I) Boxplots compare cell type fractions between the scBasal predominant tumors with low diversity (PANFR0593, 575, 545) and all others. P-value determined by Student’s t test.(J) Summary of associations between microenvironmental diversity, non-malignant cell types, and malignant cell state.See also Figure S6; Table S2.