Spatial organization and stochastic fluctuations of immune cells impact clinical responsiveness to immune checkpoint inhibitors in patients with melanoma

Abstract

High-dimensional, spatial single-cell technologies such as CyTOF imaging mass cytometry (IMC) provide detailed information regarding locations of a large variety of cancer and immune cells in microscopic scales in tumor microarray (TMA) slides obtained from patients prior to immune checkpoint inhibitor (ICI) therapy. An important question is how the initial spatial organization of these cells in the tumor microenvironment (TME) change with time, regulate tumor growth and eventually outcomes as patients undergo ICI therapy. Utilizing IMC data of melanomas of patients who later underwent ICI therapy, we develop a spatially resolved interacting cell systems model that is calibrated against patient response data to address the above question. We find that the tumor fate in these patients is determined by the spatial organization of activated CD8+ T cells, macrophages, and melanoma cells and the interplay between these cells that regulate exhaustion of CD8+ T cells. We find that fencing of tumor cell boundaries by exhausted CD8+T cells is dynamically generated from the initial conditions that can play a pro-tumor role. Furthermore, we find that specific spatial features such as co-clustering of activated CD8+ T cells and macrophages in the pre-treatment samples determine the fate of the tumor progression, despite stochastic fluctuations and changes over the treatment course. Our framework enables determination of mechanisms of interplay between a key subset of tumor and immune cells in the TME that regulate clinical response to ICIs. SignificanceRecent advances in single cell technologies allows for spatial imaging a wide variety of cancer and immune cells in tissue samples obtained from solid tumors. This detailed snapshot data of microscale organization of tumor and immune cells could provide valuable insights into underlying biology and clinical responsiveness to cancer immunotherapy. By combining published data from imaging mass-cytometry and patient response against ICI drugs with data analysis rooted in statistical physics and statistical inference theory, we developed and studied the dynamics of mechanistic spatially resolved models: we show that tumor growth during ICI treatment is regulated by non-intuitive interplay between CD8+ T cells and tumor associated macrophages, formation of a pro-tumor fencing of exhausted CD8+ T cells around melanoma cells, specific features of spatial organization of these cells prior to treatment, and stochastic fluctuations in the dynamics. The mechanisms unveiled in our studies are general and can pertain to the response of other solid tumors to ICI therapy.