Fig. 1: Study overview and pancreatic cancer single-cell analysis.

A Single-cell RNA sequencing (scRNA-seq) was performed on treatment-naïve pancreatic ductal adenocarcinoma (PDAC) tumor tissue samples acquired by esophageal ultrasound-guided fine needle biopsy (n = 25). These were integrated with in-house surgical resection PDAC samples from six patients and samples from three publicly available PDAC scRNA-seq datasets resulting in a combined dataset of ~190k cells from 80 independent PDAC patients. The resulting data were used to identify PDAC cell states, including malignant and immune subtypes based on gene sets and known expression markers from published studies. With single-cell annotations in hand, we determined fibroblast and malignant cell states and stemness and used a modified version of the Ecotyper tool to identify co-occurring patterns of cell states (termed ecotypes) in bulk RNA-seq samples. We found that pancreatic ecotype PE5, comprised of Malignant Basal-like cells, myCAFs, and SPP1+ TAMs, was associated with worse survival. B UMAP decomposition of scRNA-seq expression profiles. C Regenerated and sub-clustered UMAP plots for malignant, cancer-associated fibroblast (CAF), and tumor-associated macrophage (TAM) cell states. D Gene set scores from published data for the previously mentioned cell states. E, F CytoTRACE developmental stemness scores for CAF and malignant cell states. Higher values indicate more stem-like cells. *** indicates p-value << 0.005 as calculated by the Wilcoxon rank sum test. The upper and lower bounds signify the first and third quartiles, respectively. The median is denoted by the center line. The whiskers represent data points within 1.5 times the interquartile range.