Journal for ImmunoTherapy of Cancer (Sep 2023)

KLRG1 marks tumor-infiltrating CD4 T cell subsets associated with tumor progression and immunotherapy response

  • Charles G Drake,
  • Benjamin Izar,
  • Casey R Ager,
  • Aleksandar Obradovic,
  • Matthew Chaimowitz,
  • Catherine Spina,
  • Mingxuan Zhang,
  • Shruti Bansal,
  • Somnath Tagore,
  • Collin Jugler,
  • Meri Rogava,
  • Johannes C Melms,
  • Patrick McCann,
  • Matthew C Dallos

DOI
https://doi.org/10.1136/jitc-2023-006782
Journal volume & issue
Vol. 11, no. 9

Abstract

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Current methods for biomarker discovery and target identification in immuno-oncology rely on static snapshots of tumor immunity. To thoroughly characterize the temporal nature of antitumor immune responses, we developed a 34-parameter spectral flow cytometry panel and performed high-throughput analyses in critical contexts. We leveraged two distinct preclinical models that recapitulate cancer immunoediting (NPK-C1) and immune checkpoint blockade (ICB) response (MC38), respectively, and profiled multiple relevant tissues at and around key inflection points of immune surveillance and escape and/or ICB response. Machine learning-driven data analysis revealed a pattern of KLRG1 expression that uniquely identified intratumoral effector CD4 T cell populations that constitutively associate with tumor burden across tumor models, and are lost in tumors undergoing regression in response to ICB. Similarly, a Helios-KLRG1+ subset of tumor-infiltrating regulatory T cells was associated with tumor progression from immune equilibrium to escape and was also lost in tumors responding to ICB. Validation studies confirmed KLRG1 signatures in human tumor-infiltrating CD4 T cells associate with disease progression in renal cancer. These findings nominate KLRG1+ CD4 T cell populations as subsets for further investigation in cancer immunity and demonstrate the utility of longitudinal spectral flow profiling as an engine of dynamic biomarker discovery.