Bispecific dendritic-T cell engager potentiates anti-tumor immunity.

Immune checkpoint inhibition treatment using aPD-1 monoclonal antibodies is a promising cancer immunotherapy approach. However, its effect on tumor immunity is narrow, as most patients do not respond to the treatment or suffer from recurrence. We show that the crosstalk between conventional type I dendritic cells (cDC1) and T cells is essential for an effective aPD-1-mediated anti-tumor response. Accordingly, we developed a bispecific DC-T cell engager (BiCE), a reagent that facilitates physical interactions between PD-1+ T cells and cDC1. BiCE treatment promotes the formation of active dendritic/T cell crosstalk in the tumor and tumor-draining lymph nodes. In vivo, single-cell and physical interacting cell analysis demonstrates the distinct and superior immune reprogramming of the tumors and tumor-draining lymph nodes treated with BiCE as compared to conventional aPD-1 treatment. By bridging immune cells, BiCE potentiates cell circuits and communication pathways needed for effective anti-tumor immunity.

Time-resolved single-cell transcriptomics defines immune trajectories in glioblastoma.

Deciphering the cell-state transitions underlying immune adaptation across time is fundamental for advancing biology. Empirical in vivo genomic technologies that capture cellular dynamics are currently lacking. We present Zman-seq, a single-cell technology recording transcriptomic dynamics across time by introducing time stamps into circulating immune cells, tracking them in tissues for days. Applying Zman-seq resolved cell-state and molecular trajectories of the dysfunctional immune microenvironment in glioblastoma. Within 24 hours of tumor infiltration, cytotoxic natural killer cells transitioned to a dysfunctional program regulated by TGFB1 signaling. Infiltrating monocytes differentiated into immunosuppressive macrophages, characterized by the upregulation of suppressive myeloid checkpoints Trem2, Il18bp, and Arg1, over 36 to 48 hours. Treatment with an antagonistic anti-TREM2 antibody reshaped the tumor microenvironment by redirecting the monocyte trajectory toward pro-inflammatory macrophages. Zman-seq is a broadly applicable technology, enabling empirical measurements of differentiation trajectories, which can enhance the development of more efficacious immunotherapies.

The CD8+ T cell tolerance checkpoint triggers a distinct differentiation state defined by protein translation defects.

Peripheral CD8+ T cell tolerance is a checkpoint in both autoimmune disease and anti-cancer immunity. Despite its importance, the relationship between tolerance-induced states and other CD8+ T cell differentiation states remains unclear. Using flow cytometric phenotyping, single-cell RNA sequencing (scRNA-seq), and chromatin accessibility profiling, we demonstrated that in vivo peripheral tolerance to a self-antigen triggered a fundamentally distinct differentiation state separate from exhaustion, memory, and functional effector cells but analogous to cells defectively primed against tumors. Tolerant cells diverged early and progressively from effector cells, adopting a transcriptionally and epigenetically distinct state within 60 h of antigen encounter. Breaching tolerance required the synergistic actions of strong T cell receptor (TCR) signaling and inflammation, which cooperatively induced gene modules that enhanced protein translation. Weak TCR signaling during bystander infection failed to breach tolerance due to the uncoupling of effector gene expression from protein translation. Thus, tolerance engages a distinct differentiation trajectory enforced by protein translation defects.

p16-dependent increase of PD-L1 stability regulates immunosurveillance of senescent cells.

The accumulation of senescent cells promotes ageing and age-related diseases, but molecular mechanisms that senescent cells use to evade immune clearance and accumulate in tissues remain to be elucidated. Here we report that p16-positive senescent cells upregulate the immune checkpoint protein programmed death-ligand 1 (PD-L1) to accumulate in ageing and chronic inflammation. We show that p16-mediated inhibition of cell cycle kinases CDK4/6 induces PD-L1 stability in senescent cells via downregulation of its ubiquitin-dependent degradation. p16-expressing senescent alveolar macrophages elevate PD-L1 to promote an immunosuppressive environment that can contribute to an increased burden of senescent cells. Treatment with activating anti-PD-L1 antibodies engaging Fcγ receptors on effector cells leads to the elimination of PD-L1 and p16-positive cells. Our study uncovers a molecular mechanism of p16-dependent regulation of PD-L1 protein stability in senescent cells and reveals the potential of targeting PD-L1 to improve immunosurveillance of senescent cells and ameliorate senescence-associated inflammation.

Modeling T cell temporal response to cancer immunotherapy rationalizes development of combinatorial treatment protocols.

Successful immunotherapy relies on triggering complex responses involving T cell 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 the tumor-draining lymph node (tdLN). Using this approach, we characterize two modes of anti-programmed cell death protein 1 (PD-1) activity, decoupling induced differentiation of tumor-specific activated precursor cells from conventional type 1 dendritic cell (cDC1)-dependent proliferation and recruitment to the TME. We demonstrate that combining anti-PD-1 therapy with anti-4-1BB agonist enhances the recruitment and proliferation of activated precursors, resulting in tumor control. These data suggest that effective response to anti-PD-1 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.