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

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 angio...

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Autores principales: Sahu, Aditi, Kose, Kivanc, Kraehenbuehl, Lukas, Byers, Candice, Holland, Aliya, Tembo, Teguru, Santella, Anthony, Alfonso, Anabel, Li, Madison, Cordova, Miguel, Gill, Melissa, Fox, Christi, Gonzalez, Salvador, Kumar, Piyush, Wang, Amber Weiching, Kurtansky, Nicholas, Chandrani, Pratik, Yin, Shen, Mehta, Paras, Navarrete-Dechent, Cristian, Peterson, Gary, King, Kimeil, Dusza, Stephen, Yang, Ning, Liu, Shuaitong, Phillips, William, Guitera, Pascale, Rossi, Anthony, Halpern, Allan, Deng, Liang, Pulitzer, Melissa, Marghoob, Ashfaq, Chen, Chih-Shan Jason, Merghoub, Taha, Rajadhyaksha, Milind
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9463451/
https://www.ncbi.nlm.nih.gov/pubmed/36085288
http://dx.doi.org/10.1038/s41467-022-32738-7
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author Sahu, Aditi
Kose, Kivanc
Kraehenbuehl, Lukas
Byers, Candice
Holland, Aliya
Tembo, Teguru
Santella, Anthony
Alfonso, Anabel
Li, Madison
Cordova, Miguel
Gill, Melissa
Fox, Christi
Gonzalez, Salvador
Kumar, Piyush
Wang, Amber Weiching
Kurtansky, Nicholas
Chandrani, Pratik
Yin, Shen
Mehta, Paras
Navarrete-Dechent, Cristian
Peterson, Gary
King, Kimeil
Dusza, Stephen
Yang, Ning
Liu, Shuaitong
Phillips, William
Guitera, Pascale
Rossi, Anthony
Halpern, Allan
Deng, Liang
Pulitzer, Melissa
Marghoob, Ashfaq
Chen, Chih-Shan Jason
Merghoub, Taha
Rajadhyaksha, Milind
author_facet Sahu, Aditi
Kose, Kivanc
Kraehenbuehl, Lukas
Byers, Candice
Holland, Aliya
Tembo, Teguru
Santella, Anthony
Alfonso, Anabel
Li, Madison
Cordova, Miguel
Gill, Melissa
Fox, Christi
Gonzalez, Salvador
Kumar, Piyush
Wang, Amber Weiching
Kurtansky, Nicholas
Chandrani, Pratik
Yin, Shen
Mehta, Paras
Navarrete-Dechent, Cristian
Peterson, Gary
King, Kimeil
Dusza, Stephen
Yang, Ning
Liu, Shuaitong
Phillips, William
Guitera, Pascale
Rossi, Anthony
Halpern, Allan
Deng, Liang
Pulitzer, Melissa
Marghoob, Ashfaq
Chen, Chih-Shan Jason
Merghoub, Taha
Rajadhyaksha, Milind
author_sort Sahu, Aditi
collection PubMed
description 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.
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spelling pubmed-94634512022-09-11 In vivo tumor immune microenvironment phenotypes correlate with inflammation and vasculature to predict immunotherapy response Sahu, Aditi Kose, Kivanc Kraehenbuehl, Lukas Byers, Candice Holland, Aliya Tembo, Teguru Santella, Anthony Alfonso, Anabel Li, Madison Cordova, Miguel Gill, Melissa Fox, Christi Gonzalez, Salvador Kumar, Piyush Wang, Amber Weiching Kurtansky, Nicholas Chandrani, Pratik Yin, Shen Mehta, Paras Navarrete-Dechent, Cristian Peterson, Gary King, Kimeil Dusza, Stephen Yang, Ning Liu, Shuaitong Phillips, William Guitera, Pascale Rossi, Anthony Halpern, Allan Deng, Liang Pulitzer, Melissa Marghoob, Ashfaq Chen, Chih-Shan Jason Merghoub, Taha Rajadhyaksha, Milind Nat Commun Article 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. Nature Publishing Group UK 2022-09-09 /pmc/articles/PMC9463451/ /pubmed/36085288 http://dx.doi.org/10.1038/s41467-022-32738-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Sahu, Aditi
Kose, Kivanc
Kraehenbuehl, Lukas
Byers, Candice
Holland, Aliya
Tembo, Teguru
Santella, Anthony
Alfonso, Anabel
Li, Madison
Cordova, Miguel
Gill, Melissa
Fox, Christi
Gonzalez, Salvador
Kumar, Piyush
Wang, Amber Weiching
Kurtansky, Nicholas
Chandrani, Pratik
Yin, Shen
Mehta, Paras
Navarrete-Dechent, Cristian
Peterson, Gary
King, Kimeil
Dusza, Stephen
Yang, Ning
Liu, Shuaitong
Phillips, William
Guitera, Pascale
Rossi, Anthony
Halpern, Allan
Deng, Liang
Pulitzer, Melissa
Marghoob, Ashfaq
Chen, Chih-Shan Jason
Merghoub, Taha
Rajadhyaksha, Milind
In vivo tumor immune microenvironment phenotypes correlate with inflammation and vasculature to predict immunotherapy response
title In vivo tumor immune microenvironment phenotypes correlate with inflammation and vasculature to predict immunotherapy response
title_full In vivo tumor immune microenvironment phenotypes correlate with inflammation and vasculature to predict immunotherapy response
title_fullStr In vivo tumor immune microenvironment phenotypes correlate with inflammation and vasculature to predict immunotherapy response
title_full_unstemmed In vivo tumor immune microenvironment phenotypes correlate with inflammation and vasculature to predict immunotherapy response
title_short In vivo tumor immune microenvironment phenotypes correlate with inflammation and vasculature to predict immunotherapy response
title_sort in vivo tumor immune microenvironment phenotypes correlate with inflammation and vasculature to predict immunotherapy response
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9463451/
https://www.ncbi.nlm.nih.gov/pubmed/36085288
http://dx.doi.org/10.1038/s41467-022-32738-7
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