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Immune cellular patterns of distribution affect outcomes of patients with non-small cell lung cancer

Studying the cellular geographic distribution in non-small cell lung cancer is essential to understand the roles of cell populations in this type of tumor. In this study, we characterize the spatial cellular distribution of immune cell populations using 23 makers placed in five multiplex immunofluor...

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Autores principales: Parra, Edwin Roger, Zhang, Jiexin, Jiang, Mei, Tamegnon, Auriole, Pandurengan, Renganayaki Krishna, Behrens, Carmen, Solis, Luisa, Haymaker, Cara, Heymach, John Victor, Moran, Cesar, Lee, Jack J., Gibbons, Don, Wistuba, Ignacio Ivan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10130161/
https://www.ncbi.nlm.nih.gov/pubmed/37185575
http://dx.doi.org/10.1038/s41467-023-37905-y
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author Parra, Edwin Roger
Zhang, Jiexin
Jiang, Mei
Tamegnon, Auriole
Pandurengan, Renganayaki Krishna
Behrens, Carmen
Solis, Luisa
Haymaker, Cara
Heymach, John Victor
Moran, Cesar
Lee, Jack J.
Gibbons, Don
Wistuba, Ignacio Ivan
author_facet Parra, Edwin Roger
Zhang, Jiexin
Jiang, Mei
Tamegnon, Auriole
Pandurengan, Renganayaki Krishna
Behrens, Carmen
Solis, Luisa
Haymaker, Cara
Heymach, John Victor
Moran, Cesar
Lee, Jack J.
Gibbons, Don
Wistuba, Ignacio Ivan
author_sort Parra, Edwin Roger
collection PubMed
description Studying the cellular geographic distribution in non-small cell lung cancer is essential to understand the roles of cell populations in this type of tumor. In this study, we characterize the spatial cellular distribution of immune cell populations using 23 makers placed in five multiplex immunofluorescence panels and their associations with clinicopathologic variables and outcomes. Our results demonstrate two cellular distribution patterns—an unmixed pattern mostly related to immunoprotective cells and a mixed pattern mostly related to immunosuppressive cells. Distance analysis shows that T-cells expressing immune checkpoints are closer to malignant cells than other cells. Combining the cellular distribution patterns with cellular distances, we can identify four groups related to inflamed and not-inflamed tumors. Cellular distribution patterns and distance are associated with survival in univariate and multivariable analyses. Spatial distribution is a tool to better understand the tumor microenvironment, predict outcomes, and may can help select therapeutic interventions.
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spelling pubmed-101301612023-04-27 Immune cellular patterns of distribution affect outcomes of patients with non-small cell lung cancer Parra, Edwin Roger Zhang, Jiexin Jiang, Mei Tamegnon, Auriole Pandurengan, Renganayaki Krishna Behrens, Carmen Solis, Luisa Haymaker, Cara Heymach, John Victor Moran, Cesar Lee, Jack J. Gibbons, Don Wistuba, Ignacio Ivan Nat Commun Article Studying the cellular geographic distribution in non-small cell lung cancer is essential to understand the roles of cell populations in this type of tumor. In this study, we characterize the spatial cellular distribution of immune cell populations using 23 makers placed in five multiplex immunofluorescence panels and their associations with clinicopathologic variables and outcomes. Our results demonstrate two cellular distribution patterns—an unmixed pattern mostly related to immunoprotective cells and a mixed pattern mostly related to immunosuppressive cells. Distance analysis shows that T-cells expressing immune checkpoints are closer to malignant cells than other cells. Combining the cellular distribution patterns with cellular distances, we can identify four groups related to inflamed and not-inflamed tumors. Cellular distribution patterns and distance are associated with survival in univariate and multivariable analyses. Spatial distribution is a tool to better understand the tumor microenvironment, predict outcomes, and may can help select therapeutic interventions. Nature Publishing Group UK 2023-04-25 /pmc/articles/PMC10130161/ /pubmed/37185575 http://dx.doi.org/10.1038/s41467-023-37905-y Text en © The Author(s) 2023 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
Parra, Edwin Roger
Zhang, Jiexin
Jiang, Mei
Tamegnon, Auriole
Pandurengan, Renganayaki Krishna
Behrens, Carmen
Solis, Luisa
Haymaker, Cara
Heymach, John Victor
Moran, Cesar
Lee, Jack J.
Gibbons, Don
Wistuba, Ignacio Ivan
Immune cellular patterns of distribution affect outcomes of patients with non-small cell lung cancer
title Immune cellular patterns of distribution affect outcomes of patients with non-small cell lung cancer
title_full Immune cellular patterns of distribution affect outcomes of patients with non-small cell lung cancer
title_fullStr Immune cellular patterns of distribution affect outcomes of patients with non-small cell lung cancer
title_full_unstemmed Immune cellular patterns of distribution affect outcomes of patients with non-small cell lung cancer
title_short Immune cellular patterns of distribution affect outcomes of patients with non-small cell lung cancer
title_sort immune cellular patterns of distribution affect outcomes of patients with non-small cell lung cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10130161/
https://www.ncbi.nlm.nih.gov/pubmed/37185575
http://dx.doi.org/10.1038/s41467-023-37905-y
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