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

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

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)742-759
Number of pages18
JournalNature Cancer
Volume5
Issue number5
DOIs
StatePublished - May 2024

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research

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