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.

成功的免疫疗法依赖于触发涉及肿瘤和外周 T 细胞动态的复杂反应。使用静态人类单细胞图谱或小鼠模型来表征这些反应仍然具有挑战性。为了解决这个问题，我们开发了一个框架，用于在体内以单细胞分辨率跟踪肿瘤特异性 CD8 ⁺ T 细胞随时间的变化。我们的工具有助于对肿瘤微环境（TME）和肿瘤引流淋巴结（tdLN）中的基因程序动态进行建模。利用这种方法，我们表征了抗程序性细胞死亡蛋白 1 (PD-1) 活性的两种模式，将肿瘤特异性激活前体细胞的诱导分化与传统 1 型树突状细胞 (cDC1) 依赖性增殖和招募到 TME 中解耦。我们证明，抗 PD-1 疗法与抗 4-1BB 激动剂相结合可增强活化前体细胞的募集和增殖，从而实现肿瘤控制。这些数据表明，抗 PD-1 疗法的有效反应取决于活化的前体 CD8 ⁺细胞足够流入 TME，并强调了了解系统级动态在优化免疫疗法中的重要性。