Abstract 5144: Spatial T-cell atlas in more than 100 different tumor entities using BLEACH&STAIN

Abstract Background: The composition and functional state of T-cell subpopulations can highly impact patient’s outcome and response to immune checkpoint therapy. However, only little is known about the spatial interplay of most rare T-cell subpopulations. Design: To assess the density, composition, degree of immune checkpoint expression, and spatial interplay of T-cell subpopulations in 5989 tumor samples from more than 100 tumor entities, two different types of tissue microarrays (0.6 mm and 4 mm in diameter) were stained with antibodies directed against CD3, CD4, CD8, FOXP3, T-bet, GATA3, RORyT, BCL6, FOXP3, CD56, CD45RA, CD45RO, TIM3, PD-1, CTLA-4 Granzym B, and Ki67 using our BLEACH&STAIN multiplex fluorescence immunohistochemistry approach. A deep learning-based framework comprising two different convolutional neuronal networks (U-Net and DeepLabv3+) was used for image analysis. Results: For identification and definition of immune cell subpopulations unsupervised X-shift clustering and 2D/3D t-distributed stochastic neighbor embedding (t-SNE) using the “Rtsne” package (Rtsne (RRID:SCR_016342)) were applied and revealed 102 T-cell subpopulations at certain functional state. Within these subpopulations, the well-characterized expression profiles were visually matched with single T-cell expression profiles and documented as digital images. This process resulted in 12 main T-cell subsets that were further subclassified according to their functional state (proliferation, immune checkpoint expression) and studied according to their spatial orchestration. Interestingly, the vast majority of T-cell subsets were found in all analyzed tumor entities. However, their spatial orchestration, immune checkpoint expression profile was highly variable between different tumor entities. Conclusion: This study provides a comprehensive overview of rare T-cells subpopulations and its spatial orchestration in more than 100 different tumor entities. Citation Format: Zhihao Huang, Elena Bady, Jan H. Müller, Tim Mandelkow, Magalie C. Lurati, Ronald Simon, Christian Bernreuther, Frank Jacobsen, Guido Sauter, Katharina Möller, Andreas Luebke, Andrea Hinsch, Till S. Clauditz, Eike Burandt, Niclas C. Blessin. Spatial T-cell atlas in more than 100 different tumor entities using BLEACH&STAIN. [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 5144.