Modeling T cell temporal response to cancer immunotherapy rationalize development of combinatorial treatments protocols

Successful immunotherapy relies on triggering complex responses involving T-cells dynamics in tumors and the periphery. Characterizing these responses remains challenging using static human single-cell atlases or mouse models. To address this, we developed a framework for in vivo tracking of tumor-specific CD8+ T cells over time and at single-cell resolution. Our tools facilitate the modeling of gene program dynamics in the tumor microenvironment (TME) and tumor-draining lymph node (tdLN). Using this approach, we characterize two modes of anti-PD1 (aPD1) activity, decoupling induced differentiation of tumor-specific activated precursor cells from cDC1-dependent proliferation and recruitment to the TME. We demonstrate that combining aPD1 with anti-4-1BB agonist enhances the recruitment and proliferation of activated precursors resulting in tumor control. These data suggest that effective response to aPD1 therapy is dependent on sufficient influx of activated precursor CD8+ cells to the TME, and highlight the importance of understanding system-level dynamics in optimizing immunotherapies. Overall design: Dissecting the temporal dynamics of CD8+ T cell in the tumor microenvironment using single-cell RNA sequencing. Mice were inoculated with different tumor cell lines (B16-OVA,MC38 and LLC) cells and treated with Anti-PD1, Anti-41BB, or both.OT1-CD8+,Bystanders CD8+, and endogenous CD8+ T Cells were harvested from tumors, tdLN, and spleen at different time points and underwent scRNAseq. We also utilized XCR1-DTR mice in various settings. Ex vivo incubation of CD8+ with tumor cell line cells was performed.