Abstract A006: Integrating single cell and spatial transcriptomics define gene signature for pancreatic ductal adenocarcinoma pre-neoplastic lesion

Abstract

Abstract Pancreatic Cancer Ductal Adenocarcinoma (PDAC) is one of the deadliest cancers with 5-year survival of 11%. Understanding the intratumor heterogeneity is a pivotal piece to unravel the complexity of PDAC. While single cell RNASeq identifies the heterogeneous cell populations within the tumor tissue, spatially characterizing the transcriptomic profile of neoplastic and pre-neoplastic populations within the tissue remains a challenge, as the spatial dimension is usually lost upon tissue dissociation. We identified an approach to integrate spatial transcriptomics data with single cell RNASeq data. To characterize the cell populations within the tissue we performed single cell RNASeq on disease pathology-free pancreas tissue and primary PDAC samples. We profiled the transcriptomic profile of Acinar, Ductal, Acinar-to-Ductal (ADM), and Pancreatic Intraepithelial Neoplasia (PanINs) regions of interest (ROIs) across the tissue using the Nanostring GeoMx platform. Differential gene expression analysis using linear mixed-effect models of the cell-type specific ROIs defined pan-marker gene sets for each cell type, which were mapped to UMAP projections of single cell RNA sequencing data using AUCell scoring. As expected, the acinar pan-markers gene set derived from the spatial transcriptomics mapped to the manually annotated acinar population in the single cell data. On the other hand, Ductal, ADM, and PanIN pan-marker gene sets were mapped to distinct clusters that previously were not well-defined by single cell sequencing. The analysis coupled with orthogonal validation using RNAScope revealed gene signatures uniquely specific to ADM lesions and PanINs, respectively. Interestingly, our list included known markers as well as novel findings, supporting the validity of the findings. Furthermore, RNA velocity analysis using scVelo revealed a trajectory of cell evolution originating from acinar cells passing through the newly-defined ADM population and ending towards the ductal population derived from tumor samples. Overall, this integration approach of spatial and single cell transcriptomics can further define the characteristics that differentiate neoplastic and pre-neoplastic populations, as well as the potential drivers for tumorigenesis that could be therapeutically targeted. Citation Format: Ahmed M. Elhossiny, Eileen Carpenter, Padma Kadiyala, Yaqing Zhang, Filip Bednar, Arvind Rao, Timothy Frankel, Marina Pasca Di Magliano. Integrating single cell and spatial transcriptomics define gene signature for pancreatic ductal adenocarcinoma pre-neoplastic lesion [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr A006.