Abstract

Abstract Immunotherapy can result in lasting tumor regressions, but despite its success, only a subset of patients and cancer types benefit from immunotherapy. Thus, uncovering features of the tumor microenvironment (TME) that contribute to this differential response can inform candidates for novel therapies and biomarkers for patient stratification. Recent advances in single-cell technologies allow for profiling of cell states and their spatial interactions within a tumor. Here, we performed multiplexed immunofluorescence (mpIF), a method for in situ single-cell measurement of 30+ proteins, as well as bulk transcriptomics and genomics on 180 tumor samples across 4 immunotherapy-responsive and -resistant solid and liquid cancers: in-transit melanoma (ITM), non-small cell lung cancer (NSCLC), glioblastoma multiforme (GBM), and classical Hodgkin lymphoma (cHL). In aggregate, we measured over 100 million single cells and identified over 1,000 unique tumor and immune cell states. We uncovered immune-suppressive cell states, such as macrophages negative for PD-L1 and B7-H3 in immunotherapy-resistant ITM tumors and all GBM tumors, which generally fail to respond to immunotherapy. In GBM, macrophages exhibited two distinct spatial topologies, infiltrated or excluded. In ITM, we identified pre-treatment cell states and gene expression signatures that associate with immunotherapy response such as MHC class I expression on the tumor cell surface, B cell aggregates, “exhausted” PD-1/LAG-3/TIM-3 triple-positive CD8+ T cells, and expression of interferon-gamma genes. We observed a similar immune checkpoint-rich (PD-1/LAG-3/TIM-3 triple-positive) TME in all cHL tumors, which have remarkably high immunotherapy response rates. We spatially defined the microniche (30-micron radius neighborhood) of “exhausted” CD8+ T cells, and within the microniches, found antigen presentation competent tumor cells, proliferating T cells, and B7-H3 positive macrophages, which together contribute to an activated TME. Together, we present a statistical workflow for the integrated analysis of spatially resolved multidimensional data for cancer target discovery that is tailored towards application in routinely collected formalin-fixed paraffin-embedded cancer biospecimens. Citation Format: Maryam Pourmaleki, Caitlin J. Jones, Brian D. Greenstein, Sabrina D. Mellinghoff, Daniel A. Navarrete, Smrutiben A. Mehta, Nicholas D. Socci, Ingo K. Mellinghoff, Travis J. Hollmann. Towards a spatial view of immune cell function in 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 2125.

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