30 Synergistic systematic analysis with fully human tissue models andin silico modeling of “copycats” reveals mechanisms of T cell suppression in clear cell renal cell carcinoma
Authors: Zhang Xin-Wen , Pöchmann Alexandra , Holtkotte Xu , Suarez-Carmona Meggy , Duensing Prof Stefan , Zschäbitz Stefanie , Jäger Prof Dirk , Gaida Prof Matthias , Halama Prof Niels 
Published: August 2024

Abstract

Background
Immune checkpoint-inhibitors have become a standard treatment for clear cell renal cell carcinoma (ccRCC). However, responses to checkpoint-inhibition are heterogeneous and many patients are resistant or eventually develop resistance. A better understanding of functional mechanisms governing immune responses in ccRCC is needed to identify biomarkers for therapeutic responses and to unravel novel therapeutic targets to overcome primary or acquired resistance to therapies.

Methods
We developed a fully human explant model derived from freshly resected ccRCC tissue (Fig. 1A). Our tissue explant model preserves all components of the tumor microenvironment including not only tumor cells, but also the immune cell compartment as well as tumor-stroma and -vasculature in culture (Fig. 1B). Following treatment with combined checkpoint-inhibition (Nivolumab plus Ipilimumab) or an anti-CCR5 inhibitor (Maraviroc), the tissue explants were analyzed by immunohistochemistry staining and multiplex cytokine profiling of 50 cytokines. Spatial and functional insights were incorporated in an agent-based in silico model (PhysiCell, Ghaffarizadeh et al., PLoS Comput. Biol., 2018) for unlimited exploration of functional cellular dynamics in the tumor microenvironment (Fig. 1D).

Results
Immunohistochemical analyses and cytokine profiling of ccRCC-tissue explants showed heterogeneous immune responses among different patients and indicated an impaired cytotoxic T cell response following checkpoint-inhibition (Fig. 1C). Spatial analyses of immune cell populations revealed clusters of CD8+ T cells and CD163+ macrophages localized closely to CD31+ endothelial cells.
Further characterization of the tumor microenvironment revealed high CCR5-expression in the tumor, particularly on the tumor blood vessels (Fig. 1B). Treatment of the tissue explants with the anti-CCR5 inhibitor Maraviroc led to an increase of CD8+ T cells and cytotoxic cytokines (Granzyme B, IFNgamma, TNFalpha, IFNalpha2) in the tumor in comparison to checkpoint-inhibition (Fig. 1C).
Spatial and functional information from cultured ccRCC-tissue explants were integrated into an agent-based in silico model of the ccRCC tumor microenvironment, which includes tumor cells, T cells, macrophages and endothelial cells (Fig. 1D). In silico simulation of different immune cell modulating treatment conditions showed an increase of T cells and cytotoxic cytokines upon blockade of the interaction between T cells with endothelial cells or macrophages (Fig. 1E).

Conclusions
Our combined ex vivo and in silico analyses provide evidence for immunosuppression in the ccRCC tumor microenvironment mediated by macrophages and endothelial cells. CCR5 was shown to be a potential target to overcome immune resistance to checkpoint-inhibition in ccRCC. Further characterization of immune cell compositions and functional mechanisms in the perivascular area is imperative to enhance therapeutic responses to immunotherapies for ccRCC.