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Spatially variant immune infiltration scoring in human cancer tissues
The Immunoscore is a method to quantify the immune cell infiltration within cancers to predict the disease prognosis. Previous immune profiling approaches relied on limited immune markers to establish patients’ tumor immunity. However, immune cells exhibit a higher-level complexity that is typically...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9437065/ https://www.ncbi.nlm.nih.gov/pubmed/36050391 http://dx.doi.org/10.1038/s41698-022-00305-4 |
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author | Allam, Mayar Hu, Thomas Lee, Jeongjin Aldrich, Jeffrey Badve, Sunil S. Gökmen-Polar, Yesim Bhave, Manali Ramalingam, Suresh S. Schneider, Frank Coskun, Ahmet F. |
author_facet | Allam, Mayar Hu, Thomas Lee, Jeongjin Aldrich, Jeffrey Badve, Sunil S. Gökmen-Polar, Yesim Bhave, Manali Ramalingam, Suresh S. Schneider, Frank Coskun, Ahmet F. |
author_sort | Allam, Mayar |
collection | PubMed |
description | The Immunoscore is a method to quantify the immune cell infiltration within cancers to predict the disease prognosis. Previous immune profiling approaches relied on limited immune markers to establish patients’ tumor immunity. However, immune cells exhibit a higher-level complexity that is typically not obtained by the conventional immunohistochemistry methods. Herein, we present a spatially variant immune infiltration score, termed as SpatialVizScore, to quantify immune cells infiltration within lung tumor samples using multiplex protein imaging data. Imaging mass cytometry (IMC) was used to target 26 markers in tumors to identify stromal, immune, and cancer cell states within 26 human tissues from lung cancer patients. Unsupervised clustering methods dissected the spatial infiltration of cells in tissue using the high-dimensional analysis of 16 immune markers and other cancer and stroma enriched labels to profile alterations in the tumors’ immune infiltration patterns. Spatially resolved maps of distinct tumors determined the spatial proximity and neighborhoods of immune-cancer cell pairs. These SpatialVizScore maps provided a ranking of patients’ tumors consisting of immune inflamed, immune suppressed, and immune cold states, demonstrating the tumor’s immune continuum assigned to three distinct infiltration score ranges. Several inflammatory and suppressive immune markers were used to establish the cell-based scoring schemes at the single-cell and pixel-level, depicting the cellular spectra in diverse lung tissues. Thus, SpatialVizScore is an emerging quantitative method to deeply study tumor immunology in cancer tissues. |
format | Online Article Text |
id | pubmed-9437065 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-94370652022-09-03 Spatially variant immune infiltration scoring in human cancer tissues Allam, Mayar Hu, Thomas Lee, Jeongjin Aldrich, Jeffrey Badve, Sunil S. Gökmen-Polar, Yesim Bhave, Manali Ramalingam, Suresh S. Schneider, Frank Coskun, Ahmet F. NPJ Precis Oncol Article The Immunoscore is a method to quantify the immune cell infiltration within cancers to predict the disease prognosis. Previous immune profiling approaches relied on limited immune markers to establish patients’ tumor immunity. However, immune cells exhibit a higher-level complexity that is typically not obtained by the conventional immunohistochemistry methods. Herein, we present a spatially variant immune infiltration score, termed as SpatialVizScore, to quantify immune cells infiltration within lung tumor samples using multiplex protein imaging data. Imaging mass cytometry (IMC) was used to target 26 markers in tumors to identify stromal, immune, and cancer cell states within 26 human tissues from lung cancer patients. Unsupervised clustering methods dissected the spatial infiltration of cells in tissue using the high-dimensional analysis of 16 immune markers and other cancer and stroma enriched labels to profile alterations in the tumors’ immune infiltration patterns. Spatially resolved maps of distinct tumors determined the spatial proximity and neighborhoods of immune-cancer cell pairs. These SpatialVizScore maps provided a ranking of patients’ tumors consisting of immune inflamed, immune suppressed, and immune cold states, demonstrating the tumor’s immune continuum assigned to three distinct infiltration score ranges. Several inflammatory and suppressive immune markers were used to establish the cell-based scoring schemes at the single-cell and pixel-level, depicting the cellular spectra in diverse lung tissues. Thus, SpatialVizScore is an emerging quantitative method to deeply study tumor immunology in cancer tissues. Nature Publishing Group UK 2022-09-01 /pmc/articles/PMC9437065/ /pubmed/36050391 http://dx.doi.org/10.1038/s41698-022-00305-4 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 Allam, Mayar Hu, Thomas Lee, Jeongjin Aldrich, Jeffrey Badve, Sunil S. Gökmen-Polar, Yesim Bhave, Manali Ramalingam, Suresh S. Schneider, Frank Coskun, Ahmet F. Spatially variant immune infiltration scoring in human cancer tissues |
title | Spatially variant immune infiltration scoring in human cancer tissues |
title_full | Spatially variant immune infiltration scoring in human cancer tissues |
title_fullStr | Spatially variant immune infiltration scoring in human cancer tissues |
title_full_unstemmed | Spatially variant immune infiltration scoring in human cancer tissues |
title_short | Spatially variant immune infiltration scoring in human cancer tissues |
title_sort | spatially variant immune infiltration scoring in human cancer tissues |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9437065/ https://www.ncbi.nlm.nih.gov/pubmed/36050391 http://dx.doi.org/10.1038/s41698-022-00305-4 |
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