Abstract 3609: Defining extrinsic and intrinsic mechanisms of immune evasion in TRACERx using imaging mass cytometry
Authors: Enfield Katey , Colliver Emma , Angelova Mihaela , Magness Alastair , Lee Claudia , Grigoriadis Kristiana , Pich Oriol , Puttick Clare , Levi Dina , Hobson Philip , Moore David , Karasaki Takahiro , Veeriah Selvaraju ,   TRACERx Consortium, Jamal-Hanjani Mariam , McGranahan Nicholas , Sahai Erik , Downward Julian , Hiley Crispin , Swanton Charles 
Published: June 2022

Introduction: The relationship between the evolving cancer genome and its tumor microenvironment (TME) is poorly understood. TRACERx has examined the intrinsic mechanisms of immune escape in non-small cell lung cancer. Here, we applied imaging mass cytometry (IMC) to address the contribution of extrinsic mechanisms in the context of intrinsic mechanisms and genomic features such as neoantigen burden.

Methods: We applied two 35-antibody IMC panels to the treatment naïve multiregion TRACERx cohort (n=81 patients, 221 regions), and developed an IMC analysis pipeline to study T cell differentiation states, cancer associated fibroblasts, vasculature, and innate and adaptive immunity. Identities and functional states were assigned to over 4 million cells and their positions were mapped within tumor and stromal compartments.

Results: We identified four distinct TMEs according to the local densities of lymphoid and myeloid cells: high infiltrate, stroma TIL enriched, myeloid enriched, and low infiltrate. We confirmed frequent intratumor TME heterogeneity, previously inferred from RNA sequencing. In high and stroma TIL enriched TMEs, we found the balance of effector and suppressor cells either favoured an exhausted (exhausted T cells and Tregs, n=16, 26.7%), suppressed (effector T cells and suppressive macrophages, n=31, 51.6%) or effector phenotype (high M1:M2, n=13, 21.6%). Tregs within exhausted TMEs neighboured effector and exhausted T cells, whereas effector T cells were nearest tumor cells within effector TMEs. Cell-type specific checkpoint molecule expression favoured specific compartments and TMEs. For example, the highest density of intratumoral PDL1+ M2-macrophages was observed within high infiltrate regions. Complementary intrinsic and extrinsic immune evasion mechanisms were identified, including immune avoiding architectures and stromal barriers as spatial mechanisms of evasion. Tumor cells were found to express lactate transporter, MCT4, in high infiltrate environments. Neoantigen burden associated with immune cell densities in a histology-specific manner. In lung adenocarcinoma, neoantigen burden was associated with a high infiltrate TME and suppressive myeloid populations such as M2-macrophages. In squamous cell carcinoma, we observed significant associations with CD8+ T cells, including exhausted populations, specifically in tumors lacking HLALOH.

Conclusions: IMC allowed for the identification of spatial mechanisms of immune evasion that, when combined with intrinsic mechanisms, provided a more complete understanding of how lung tumors escape immune predation. By visualising single cells in their native context, we observed various immunosuppressive TMEs that defined high infiltrate tumors. Histology-specific relationships between immune cells and neoantigen burden point to different immune pressures, which may influence tumor evolution.

Citation Format: Katey Enfield, Emma Colliver, Mihaela Angelova, Alastair Magness, Claudia Lee, Kristiana Grigoriadis, Oriol Pich, Clare Puttick, Dina Levi, Philip Hobson, David Moore, Takahiro Karasaki, Selvaraju Veeriah, TRACERx Consortium, Mariam Jamal-Hanjani, Nicholas McGranahan, Erik Sahai, Julian Downward, Crispin Hiley, Charles Swanton. Defining extrinsic and intrinsic mechanisms of immune evasion in TRACERx using imaging mass cytometry [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 3609.