Spatial relationships and immune subsets in the tumor immune microenvironment of head and neck cancers.

6061 Background: The tumor microenvironment provides important insights into cancer behavior and its response to treatment. In particular, the cellular composition and spatial arrangement of tumor immune infiltrates are associated with patient prognosis and survival. We optimized and employed a novel method using readily available hematoxylin and eosin (H&E) slide images, termed the G-cross score, which reflects immune cell infiltration levels and their proximity to tumor cells. The G-cross score is calculated by estimating the probability distribution of immune cells, of any type, within a certain distance from a tumor cell, with higher scores indicating greater immune cell infiltration. However, because G-cross scores are calculated from H&E slides, the method is unable to distinguish among immune cell types. Using head and neck squamous cell carcinoma (HNSCC) patients having both G-cross scores and bulk RNA-seq data, we determined which subset of tumor-infiltrating immune cell types best correlate with G-cross scores, and its predictive and prognostic value. Methods: G-cross scores were calculated for 425 HNSCC samples from University of Michigan, of which 64 had paired bulk RNA-seq data. We applied the cell-type deconvolution tool, CIBERSORTx, to identify immune cell type proportions based on RNA-seq data. G-cross scores were correlated against cell-type deconvolution results, immune cell activation expression signatures, and validated gene expression-based radiosensitivity index scores. Pearson's correlation coefficient and p-value using HPV status as a covariate in a linear model was calculated for each comparison. For survival and recurrence analysis, Cox proportional hazards multivariate regression was performed using the entire 425 sample cohort. Results: G-cross scores were significantly correlated with total T cells (R = 0.52, p = 4.63✕10 -5 ), B cells (R = 0.33, p = 2.08✕10 -2 ), and dendritic cells (R = 0.46, p = 7.71✕10 -4 ), but not macrophages or mast cells. G-cross scores also had a positive correlation with T cell activation (R = 0.46, p = 2.17✕10 -4 ) and B cell activation (R = 0.53, p = 1.24✕10 -4 ) and were correlated with radiation sensitivity (R = -0.44, p = 6.67✕10 -4 ). Survival analysis showed higher G-cross scores were associated with a longer time to recurrence and improved overall survival (p = 3.0✕10 -4 ). Conclusions: G-cross scores are mainly driven by T cell and dendritic cell levels among tumor-infiltrating lymphocytes and are correlated with B and T cell activation. Importantly, G-cross scores also correlate with gene expression profiles associated with response to radiotherapy as well as time to recurrence and overall survival. G-cross scores may be an important biomarker of radiation response and indicative of protective immune subsets for HNSCC patients.