Decoding the structural and cellular composition of the tumor microenvironment in multiple human cancers using Imaging Mass Cytometry

• Published in: The Journal of immunology (1950) Vol. 210; no. 1_Supplement; pp. 249 - 249.02
• Main Authors: Pfister, Thomas D, Lim, Liang, Ouladan, Shaida, Zabinyakov, Nick, Raza, Qanber, Loh, Christina
• Format: Journal Article
• Language: English
• Published: 01.05.2023
• ISSN: 0022-1767; 1550-6606
• DOI: 10.4049/jimmunol.210.Supp.249.02

High-plex imaging techniques such as Imaging Mass Cytometry™ (IMC™) have become key tools in understanding and decoding the spatial complexity of the tumor microenvironment (TME). The TME contains tumor-infiltrating lymphocytes that have been associated with positive therapeutic outcomes. IMC enables detailed assessment of cell phenotype and function using 40-plus markers simultaneously at subcellular resolution on a single slide without spectral overlap or background autofluorescence. We customized the Maxpar® Human Immuno-Oncology IMC Panel Kit using antibodies from the Standard BioTools™ catalog to create panels for tissue-based immuno-oncology research. Data acquisition was performed using a Hyperion™ Imaging System. Cell segmentation was facilitated using an IMC Cell Segmentation Kit. A pixel classification approach and CellProfiler™ were applied for single-cell segmentation. HistoCAT™ was used for single-cell analysis to visualize protein expression in various cancer types via PhenoGraph clustering and t-SNE maps. Our custom panels were applied to normal and cancer human tissue microarrays to phenotype and analyze cell populations in these tissues. We classified the activation state of immune cells, epithelial-to-mesenchymal transition (EMT) progression, and composition of the extracellular matrix. In-depth single-cell analysis quantitatively evaluated the cellular makeup and immune cell component in the TME of cancer tissues. This work demonstrates the capability of IMC to identify subcellular localization of cellular and structural markers, including quantitative and spatial identification of multiple immune parameters in the TME, in tumor microarrays of cancer subject samples.