In vivo tumor immune microenvironment phenotypes correlate with inflammation and vasculature to predict immunotherapy response

Aditi Sahu, Kivanc Kose, Lukas Kraehenbuehl, Candice Byers, Aliya Holland, Teguru Tembo, Anthony Santella, Anabel Alfonso, Madison Li, Miguel Cordova, Melissa Gill, Christi Fox, Salvador Gonzalez, Piyush Kumar, Amber Weiching Wang, Nicholas Kurtansky, Pratik Chandrani, Shen Yin, Paras Mehta, Cristian Navarrete-DechentGary Peterson, Kimeil King, Stephen Dusza, Ning Yang, Shuaitong Liu, William Phillips, Pascale Guitera, Anthony Rossi, Allan Halpern, Liang Deng, Melissa Pulitzer, Ashfaq Marghoob, Chih Shan Jason Chen, Taha Merghoub, Milind Rajadhyaksha

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

Response to immunotherapies can be variable and unpredictable. Pathology-based phenotyping of tumors into ‘hot’ and ‘cold’ is static, relying solely on T-cell infiltration in single-time single-site biopsies, resulting in suboptimal treatment response prediction. Dynamic vascular events (tumor angiogenesis, leukocyte trafficking) within tumor immune microenvironment (TiME) also influence anti-tumor immunity and treatment response. Here, we report dynamic cellular-level TiME phenotyping in vivo that combines inflammation profiles with vascular features through non-invasive reflectance confocal microscopic imaging. In skin cancer patients, we demonstrate three main TiME phenotypes that correlate with gene and protein expression, and response to toll-like receptor agonist immune-therapy. Notably, phenotypes with high inflammation associate with immunostimulatory signatures and those with high vasculature with angiogenic and endothelial anergy signatures. Moreover, phenotypes with high inflammation and low vasculature demonstrate the best treatment response. This non-invasive in vivo phenotyping approach integrating dynamic vasculature with inflammation serves as a reliable predictor of response to topical immune-therapy in patients.

Original languageEnglish
Article number5312
JournalNature Communications
Volume13
Issue number1
DOIs
StatePublished - Dec 2022

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