PROJECT 1: TIME-Based Spatiotemporal Cancer Immunograms Predictive for Immunotherapy-Targeted Therapy Sequential Combinations

Project 1 Summary/Abstract Combining immunotherapy with other therapy regimens, particularly targeted therapy, is a highly active area of exploration with the goal of improving anti-tumor efficacy and extending therapeutic benefits to more patients or tumor types. As the first mutation-immune co-targeted therapy, the simultaneous combination of anti-PD-L1 with BRAFV600MUT and MEK inhibitors (so-called “triplet” therapy) has been approved for patients with BRAFV600MUT melanoma. However, the data on this triplet appear mixed, with other trials not meeting key endpoints, suggesting that simultaneous combination is not optimal. Our recent work in syngeneic murine melanoma models showed uniformly, across tumor models of distinct driver mutations and cancer histologies, that a regimen of 1-week anti-PD-1/L1 (± anti-CTLA-4) pretreatment augments the efficacy of triplet therapy by enhancing MAPKi durability and dramatically suppressing melanoma brain metastasis. The improved therapy efficacy resulted from the promotion of pro-inflammatory polarization of tumor-associated macrophages and the elicitation of robust T cell clonal expansion and clonotypic convergence within the tumor-immune microenvironment (TIME) induced by the anti-PD-1/L1 lead-in. This is consistent with observations in the clinical trial data that prior immunotherapy before MAPKi is associated with improved progression-free survival. These results highlight the vital role of the sequence/timing of each therapy component in the rational design of combination therapies and also point to the need for a mechanistic understanding of the early-stage impact of each combinatorial therapy component on the TIME. However, the design of such sequential combination therapy trials is challenging because of the sheer number of variables (sequence order, dosing, and timing) to be tested. The level of complexity calls for a predictive framework to significantly reduce the parameter space and inform the identification of effective sequential immunotherapy-targeted inhibitor combinations. Herein, we hypothesize that a spatiotemporal, multi-omics analysis of early-stage (few days) monotherapy-induced changes in the TIME can provide deep insights for greatly simplifying the design of immunotherapy-targeted inhibitor sequential combination trials. The goal of Project 1 is to provide a data set that can be mined to inform the design of effective sequential combination regimens. We will leverage state-of-the-art, spatial multi-omics tissue profiling tools to build a spatiotemporal “movie” of the evolving TIME in established syngeneic melanoma tumor models, and their associated brain metastases, after treatment with each of the combinatorial therapy components. The resultant spatiotemporal multi-omic data will be analyzed to extract a number of highly informative TIME features from which agent-based models (Project 2) for predicting effective sequential combination regimens can be constructed. Retrospective studies of clinical tumor biopsies are proposed to validate the model findings.