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bioRxivCancer Biology

Cellular-level phenotyping of tumor-immune microenvironment (TiME) in patients in vivo reveals distinct inflammation and endothelial anergy signatures

A. Sahu, T. Tembo, K. Kose, A. Santella, A. Alfonso, M. Li, M. Cordova, M. Gill, C. Fox, S. Gonzalez, A. W. Wang, N. R. Kurtansky, P. Chandrani, P. Kumar, S. Yin, H. Jilani, P. Mehta, C. Navarrete-Dechent, G. Peterson, K. King, S. Dusza, N. Yang, S. Liu, W. Phillip, A. Rossi, , M. Rajadhyaksha

PDFDOIPreprint

Abstract

Immunotherapies have shown unprecedented clinical benefits in several malignancies1-3. However, clinical responses remain variable and unpredictable, indicating the need to develop predictive platforms that can improve patient stratification4. Phenotyping of tumors into hot, altered, or cold5 based on assessment of only T-cell infiltration in static tumor biopsies provides suboptimal prediction of immunotherapy response6,7. In vivo dynamic mechanisms within the tumor microenvironment such as tumor angiogenesis and leukocyte trafficking5,8,9 also play a central role in modulating anti-tumor immunity and therefore immunotherapy response. Here, we report novel tumor immune microenvironment (TiME) phenotyping in vivo in patients with non-invasive spatially-resolved cellular-level imaging based on endogenous contrast. Investigating skin cancers as a model, with reflectance confocal microscopy (RCM) imaging10, we determined four major phenotypes with variable prevalence of vasculature (Vasc) and inflammation (Inf) features: VaschiInfhi, VaschiInflo, VascloInfhi and Vascmed/hiInflo. The VaschiInfhi phenotype correlates with high immune activation, exhaustion, and vascular signatures while VaschiInflo with endothelial anergy and immune exclusion. Automated quantification of TiME features demonstrates moderate-high accuracy and correlation with corresponding gene expression. Prospectively analyzed response to topical immunotherapy show highest response in VascloInfhi, and reveals the added value of vascular features in predicting treatment response. Our novel in vivo cellular-level imaging and phenotyping approach can potentially advance our fundamental understanding of TiME, develop robust predictors for immunotherapy outcomes and identify novel targetable pathways in future.

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