Abstract 279: Optimal tumor metastatic gene programs in pancreatic cancer

Abstract Metastatic pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer-related deaths with very few treatment options and low-success rates. Generally speaking metastatic PDAC remains incurable. One reason behind PDAC morbidity and mortality is intratumor heterogeneity which allows metastatic dispersion and treatment resistance. We hypothesize that given multiple selective bottlenecks during metastatic progression, only a set of non-random gene programs are required for tumor cells to metastasize to different organs. To identify gene programs that become selected during PDAC metastatic progression we collected multiple (>20) metastatic tissue samples from different local and distant organs, from two clinically non-redundant human rapid-autopsies as part of the Human Tumor Atlas Network. We generated single-nuclei RNA-seq and Multiplexed Ion Beam Imaging data from these samples. Using trajectory analysis we inferred gene program dynamics between primary and metastatic samples and found an epithelial-to-mesenchymal-to-epithelial axis general to the metastases, suggesting that epithelial-mesenchymal plasticity is needed for cells to colonize other tissues. However, different organs have vastly different cell type compositions and may represent significantly different evolutionary bottlenecks. We employed archetype analysis as a tool to distinguish optimized phenotypes that may be shared or unique across colonized tissues. Archetype analysis revealed multiple gene programs, some of which are specific to a particular tissue and others ubiquitous. An epithelial-to-mesenchymal gene program was found to be shared across all samples at varying proportions, together with an extracellular matrix deposition/interaction program. Other gene programs identified include angiogenesis, hypoxia, cell cycle, immune interaction, lipid metabolism, autophagy/stress response, and cell migration. Some of these programs are present in various different metastases while others are unique to a specific site (e.g. Lipid metabolism in peritoneal metastasis). Together these programs shed light into organ tropism, metastatic modes of spread, adaptation to local tumor microenvironments, and cell-cell interactions with stromal cells. Further validation of these optimized phenotypes and integration of their spatial context will provide a deeper molecular understanding of metastatic PDAC and provide a source for data-driven therapeutic targets. [A. J-S. and Y.X contributed equally to this work.] Citation Format: Alejandro Jiménez-Sánchez, Yubin Xie, Roshan Sharma, Tin Yi Chu, Vincent Liu, Wungki Park, Akimasa Hayashi, Shigeaki Umeda, Linas Mazutis, Tal Nawy, Christine Iacobuzio-Donahue, Dana Pe’er. Optimal tumor metastatic gene programs in pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 279.