Phenotyping the tumor-immune microenvironment (TiME) in vivo by cellular-level optical imaging reveals unique combination phenotypes with variable inflammation and endothelial anergy

Immunotherapies, especially immune checkpoint blockade therapy have shown unprecedented clinical benefits in several malignancies, however, responses are variable emphasizing the need for effective biomarkers for patient stratification1. Phenotyping of tumors into hot, altered, or cold2 based on T-lymphocyte infiltration in tumor biopsies fails to explain and/or predict response to immunotherapy seen in a subset of patients3,4. One of the primary reasons for this suboptimal prediction by a single immune marker could be attributed to the fact that additional mechanisms within the tumor microenvironment modulate anti-tumor immunity and outcomes, including dynamic events such as tumor-angiogenesis and leukocyte trafficking2,5,6. We report novel tumor phenotypes through non-invasive spatially-resolved cellular-level analysis of the tumor immune microenvironment (TiME) and major determinants of anti-tumor immunity. Using skin cancers as a model and optical imaging using reflectance confocal microscopy (RCM)7, we determined four major phenotypes based on unsupervised clustering for relative prevalence of vasculature (Vasc) and inflammation (Inf) features: VaschighInfhigh, VaschighInflow, VasclowInf(intratumoral)high and VascmodInflow. The VaschighInfhigh phenotype correlate with high immune and vascular signatures while VaschighInflow with endothelial anergy. Automated quantification of TiME features demonstrates moderate accuracy and high correlation with corresponding gene expression. Prospective testing of TiME features prior to topical immunotherapy response shows highest response in the VasclowInf(IT)high phenotype, and revealing the added value of vascular features in predicting treatment response. This novel in vivo phenotyping combining dynamic immune and vascular features has the potential to advance fundamental understanding of the highly dynamic TiME, identify novel druggable pathways and develop robust predictors for immunotherapy outcomes.