Abstract A38: Defining heterogeneity of molecular subtypes in human PDAC with scRNA-Seq

Abstract

Abstract Introduction: Due to the widespread stromal involvement and sparse neoplastic populations in pancreatic ductal adenocarcinoma (PDAC) tumor biopsies, the discovery of novel biomarkers, subtypes, and therapeutic targets has been challenging. Previous work by our lab in the study of bulk tumors has established prognostic gene signatures of basal-like and classical tumor subtypes, and also normal and activated stromal subtypes. Leveraging the advances of microfluidics and single-cell RNA sequencing to digitally separate components of the tumor microenvironment (TME), we built a comprehensive single-cell atlas of human PDAC to better characterize the composition, pathology, and interactome of PDAC cells. Materials and Methods: Freshly resected human PDAC tissue is acquired immediately following resection. Bulk tissue is rapidly dissociated into single-cell suspension in order to reduce transcriptional artifacts of handling and time. Without manual phenotype preselection for specific cell types, suspension is processed and sequenced through 10X Chromium scRNA-seq and Illumina platforms. Seurat v3.0 and custom R packages were used for bioinformatic analysis. Results: Our single-cell human PDAC datasets recapitulate the highly desmoplastic composition expected from a PDAC tissue biopsy. Fibroblasts were most abundant alongside populations of preneoplastic cells, and neoplastic epithelial cells of both basal and classical subtypes. Both tumor subtype signatures were expressed within the same patient’s biopsy, raising further questions about the dichotomy and origin of PDAC subtypes. We also analyzed transcriptional heterogeneity in endocrine, exocrine, myeloid, and immune cells to establish a comprehensive transcriptomic picture of human PDAC TME. Several cancer-associated fibroblasts (CAFs) subtypes have been described. However, we observe enrichment of these gene signatures only in a subset of our fibroblasts, suggesting a broader landscape of fibroblast activity and differentiation may exist. Lastly, ligand and receptor interactions were mapped between cell types to highlight potential paracrine and autocrine mechanisms that potentiate the tumor microenvironment growth and maintenance. Conclusion: We present a comprehensive single-cell atlas of human PDAC with a focus on molecular subtypes in the TME at an unprecedented resolution. This offers novel insight into cell type heterogeneity, pathologic signaling, lineage trajectories, and specialized functions of TME components including macrophages, fibroblasts, and neoplastic cells leading to multi-axis pathways and interactions. Notably, we have found intrapatient heterogeneity in both the stromal and neoplastic tumor cell subtypes. Resolving the transcriptional heterogeneity of cells and the network of pathologic interactions within the TME allows for further revelations about cancer biology and potentially opens doors to novel combination therapies in the treatment of pancreatic cancer. Citation Format: Ki Oh, Manisha Rao, Mei Gao, Aaron Sasson, Georgios Georgakis, Joseph Kim, R. Scott Powers, Richard A Moffitt. Defining heterogeneity of molecular subtypes in human PDAC with scRNA-Seq [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2019 Sept 6-9; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2019;79(24 Suppl):Abstract nr A38.