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

Daniel Kirschenbaum, Ken Xie, Florian Ingelfinger, Yonatan Katzenelenbogen, Kathleen Abadie, Thomas Look, Fadi Sheban, Truong San Phan, Baoguo Li, Pascale Zwicky, Ido Yofe, Eyal David, Kfir Mazuz, Jinchao Hou, Yun Chen, Hila Shaim, Mayra Shanley, Soeren Becker, Jiawen Qian, Marco ColonnaFlorent Ginhoux, Katayoun Rezvani, Fabian J. Theis, Nir Yosef, Tobias Weiss, Assaf Weiner, Ido Amit

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)149-165.e23
JournalCell
Volume187
Issue number1
DOIs
StatePublished - Jan 4 2024

Keywords

  • cancer
  • computational biology
  • dynamics
  • glioblastoma
  • immunology
  • immunotherapy
  • single-cell biology
  • systems immunology
  • temporal transcriptomics
  • tumor-associated-macrophages

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