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

  • Oren Barboy,
  • Akhiad Bercovich,
  • Hanjie Li,
  • Yaniv Eyal-Lubling,
  • Adam Yalin,
  • Yuval Shapir Itai,
  • Kathleen Abadie,
  • Mor Zada,
  • Eyal David,
  • Shir Shlomi-Loubaton,
  • Yonatan Katzenelenbogen,
  • Diego Adhemar Jaitin,
  • Chamutal Gur,
  • Ido Yofe,
  • Tali Feferman,
  • Merav Cohen,
  • Rony Dahan,
  • Evan W. Newell,
  • Aviezer Lifshitz,
  • Amos Tanay,
  • Ido Amit

摘要

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.