ArticlebioRxiv : the preprint server for biology2023
KLRG1 marks tumor-infiltrating CD4 T cell subsets associated with tumor progression and immunotherapy response.
Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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12 authors at 2 institutions in 2 countries.
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Abstract
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
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