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Pancreatic tumors are highly heterogenous, often with more aggressive regions that are responsible for invasion and metastasis. These aggressive pancreatic ductal adenocarcinoma (PDAC) cells undergo epithelial to mesenchymal transition and create subregions in the tumor that evade treatments and provide a critical support niche for continued tumor growth and metastasis. Conventional chemotherapy plus radiation, or in advanced disease chemotherapy plus targeted drug therapy can lengthen patient survival. However, even in patients with local disease, the 5-year survival rate remains at around 40%, demonstrating that there is need for improved conventional and immune therapies for all pancreatic cancer patients. In this study, dozens of biomarkers have been used to probe tumor heterogeneity in pancreatic ductal adenocarcinoma (PDAC) tissue. We rely on the published finding that hypoxia gene expression is consistent in PDAC, regardless of tumor location, whether primary tumor or metastasis. With the spatial biology solution, Cell DIVETM and proprietary Spatial AI analytics software, dozens of biomarkers can be used to computationally reduce tumor heterogeneity, and to spatially define cells in the microenvironment within hypoxic and normoxic regions of PDAC, and in normal pancreas. We found that these hypoxic PDAC regions are devoid of immune cells in general, with the appearance of spatially co-localized populations of cell types consistent with tumor desmoplasia and inflammation. Taken together, multiplexed whole slide imaging and analysis enables spatially resolved whole tissue analysis of the tumor microenvironment, including new insights into spatial biology in the hypoxic PDAC environment. Citation Format: Michael J. Smith, Chi-Chou Huang, Tuan H. Phan, Hideki Sasaki, Katie O. White, Richard A. Heil-Chapdelaine, Melinda Angus-Hill. Spatial landscape of the tumor microenvironment in pancreatic ductal adenocarcinoma using multiplexed imaging and AI based analysis [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 2871. |
