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HaYeun Ji, Niyati Jhaveri, Aditya Pratapa, Ning Ma, Bassem Ben Cheikh, James Monkman, Ken O’Byrne, Brett Hughes, Arutha Kulasinghe, Oliver Braubach, Spatial phenotyping of cytokine signatures reflecting the immunotherapy responses in head and neck cancer, The Journal of Immunology, Volume 210, Issue Supplement_1, May 2023, Page 171.09, https://doi.org/10.4049/jimmunol.210.Supp.171.09
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Abstract
Immune checkpoint inhibitor (ICI) therapy has drastically improved the treatment strategies for mucosal head and neck squamous cell cancer (HNSCC). To increase treatment response rates for highly targeted ICI therapies, predictive and prognostic biomarkers are being actively explored. Specifically, the cytokine expression patterns in the tumor microenvironment (TME) are now recognized as key to understanding immune responsive and resistant phenotypes. Cytokines play an essential role in the regulation of the TME, specifically in modulating the proliferation and differentiation of immune cells. Here, we have studied spatial signatures of various cytokines within the TME of metastatic/recurrent HNSCC tumors treated with Pembrolizumab/Nivolumab. We utilized the PhenoCycler-Fusion to perform whole-slide, single cell resolution spatial phenotyping of the TME of HNSCC tumors from a cohort of n=40 patients. The discovery cohort consisted of patients who had complete vs. partial vs. stable vs. progressive responses to ICI therapy. Transcriptomic profiling of more than 60 RNA targets for various subfamily of chemokines, interleukins, and immune cell lineages was achieved using Akoya’s novel high plex RNA detection technology. Our study identified distinct spatial signatures that implicate certain cytokines in either tumor progression or regression. Specifically, we have identified areas of high and low CXCL9 and CXCL10 expression in several tumor regions that reflect immune-cell landscapes associated with resistance and sensitivity to immunotherapy. Our study demonstrates the power of unbiased spatial phenotyping with whole-slide imaging to identify biomarkers associated with response to ICI therapy in HNSCC.