Abstract 5640: Identifying pathophysiological features of mouse tumors using imaging mass cytometry

Abstract

Abstract Mouse tumor models are widely utilized for cancer studies and preclinical drug development. An obstacle in predicting therapeutic drug efficacy is the ability to quantitatively evaluate the multi-parametric post-treatment response in the tumor microenvironment (TME). Identification of immuno-oncological processes that dictate tumor growth, metastasis, and immune response is essential for selecting promising drug candidates for further clinical evaluation. Imaging Mass Cytometry™ (IMC™) is a vital and proven high-plex imaging technology that enables deep characterization of the complexity and diversity of tumor tissue without disrupting spatial context. The Hyperion™ Imaging System utilizes IMC technology to simultaneously assess 40-plus individual structural and functional markers in tissues, providing unprecedented insight into the organization and function of the TME. We have previously demonstrated the application of IMC in combination with Maxpar® and Maxpar OnDemand™ antibodies to highlight cellular composition of normal mouse tissues. Here, we showcase the Maxpar OnDemand Mouse Immuno-Oncology IMC Panel Kit for application on a variety of mouse tumor tissues. We compiled the antibody panel to quantitatively assess IO-related processes and applied it to a tissue microarray (TMA) containing a large variety of mouse tumors. Antibodies in panel kits were selected from the Maxpar and Maxpar OnDemand catalogs. We digitized high-plex data from mouse tissues using the Hyperion Imaging System and generated images demonstrating the detailed layout of the TME. We further conducted single-cell analysis to identify specific populations of tumor and immune cells in the TME. The Mouse Immuno-Oncology IMC Panel Kit successfully identified pathophysiological processes such as immune cell infiltration and activation, signaling pathway activation, biomarkers of epithelial-to-mesenchymal transition (EMT), metabolic activity, growth, and the tissue architecture of the TME. Single-cell analysis of several highly relevant tumor types separated distinct cellular clusters representing tumor, immune, stromal, and vascular cells. Activation of cellular processes associated with signaling, growth, and metastasis were identified in tumor cells. In addition, cytotoxic and inflammatory activation in lymphoid and myeloid immune cell subtypes were detected. Application of IMC based multiparametric analysis successfully identified the spatial landscape of the TME at single-cell resolution. Quantitative analysis of tumor composition revealed critical insights regarding prognostic parameters such as metastatic and growth potential of tumors, and identification and activation of immune cell infiltrates. Overall, we demonstrate the power of IMC and provide evidence of its successful application in mouse tumor models. For Research Use Only. Not for use in diagnostic procedures. Citation Format: Qanber Raza, Liang Lim, Thomas D. Pfister, Nick Zabinyakov, Christina Loh. Identifying pathophysiological features of mouse tumors using imaging mass cytometry. [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 5640.