Abstract 1165: Mechanisms of therapeutic resistance in pancreatic cancer identified by single-cell spatial transcriptomics and genetically-engineered stromal tumoroids

Abstract Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with a 5-year survival rate of 11%. PDAC has limited response to current cytotoxic, targeted and immunotherapies. Thus, it is crucial to explore the molecular underpinnings of this disease in order to identify expression patterns and intercellular dialogue that are limiting the effectiveness of current therapies. Here, we dissected the single-cell spatial transcriptomic landscape of untreated (n=7) and treated (chemoradiation, n=7) primary resected human PDAC tumors using spatial molecular imaging with a custom 990-plex panel. We recovered 719,965 high-quality single cells of 20 distinct types, including epithelial, immune, endothelial, endocrine, and diverse stromal cells. We further dissected the malignant, cancer-associated fibroblasts (CAF), and endothelial cells by applying single-nucleus RNA sequencing (snRNA-seq)-derived signatures. We explored how treatment altered the intraglandular heterogeneity of malignant programs and intratumoral composition of multicellular neighborhoods, for which we developed a Gaussian-based computational model. In concordance with previous studies, we found that myofibroblastic CAFs spatially localized with malignant cells. Treatment-enriched neural-like progenitor malignant cells spatially localized with CD8+ T cells, which combined with other findings suggests that different malignant subtypes may employ distinct mechanisms of immune evasion. We further investigated receptor-ligand interactions associated with therapeutic resistance at subcellular spatial resolution. To this end, we developed an optimal transport-based computational method to infer cell-cell communication at the cancer-stromal interface. We functionally validated a subset of predicted interactions using a murine stromal tumoroid model, in which we co-cultured transformed pancreatic ductal cells and CAFs in a solubilized extracellular matrix. We evaluated the strength of predicted interactions in response to ex vivo chemotherapy using snRNA-seq. Moreover, we modulated the expression of select ligand-receptor pairs in the malignant-CAF co-cultures using CRISPR-mediated genetic engineering. We tested the effects of these perturbations on therapeutic resistance using cell viability assays, including live-cell label-free phase nanoscopy. In conclusion, we integrated single-cell spatial transcriptomics and novel computational methods to identify mechanisms of therapeutic resistance in PDAC at both cellular and molecular levels. We functionally validated a subset of cancer-stromal receptor-ligand interactions predicted to associate with treatment resistance using genetically-engineered stromal tumoroids, demonstrating the translational potential of spatial biology for guiding therapeutic development. Citation Format: Carina Shiau, Jingyi Cao, Mark Gregory, Tae Kyung Kim, Youngmi Kim, Jason W. Reeves, Peter L. Wang, Steven Wang, Nicole A. Lester, Jennifer Su, Jimmy Guo, Joseph M. Beechem, David T. Ting, Martin Hemberg, William L. Hwang. Mechanisms of therapeutic resistance in pancreatic cancer identified by single-cell spatial transcriptomics and genetically-engineered stromal tumoroids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1165.