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Tertiary lymphoid structure stratifies glioma into three distinct tumor subtypes
Objective: Tertiary lymphoid structure (TLS), also known as ectopic lymphoid organs, are found in cancer, chronic inflammation, and autoimmune diseases. However, the heterogeneity of TLS in gliomas is unclear. Therefore, it is necessary to identify TLS differences and define TLS subtypes. Methods: T...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8751592/ https://www.ncbi.nlm.nih.gov/pubmed/34954691 http://dx.doi.org/10.18632/aging.203798 |
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author | Zhou, Xingwang Li, Wenyan Yang, Jie Qi, Xiaolan Chen, Yimin Yang, Hua Chu, Liangzhao |
author_facet | Zhou, Xingwang Li, Wenyan Yang, Jie Qi, Xiaolan Chen, Yimin Yang, Hua Chu, Liangzhao |
author_sort | Zhou, Xingwang |
collection | PubMed |
description | Objective: Tertiary lymphoid structure (TLS), also known as ectopic lymphoid organs, are found in cancer, chronic inflammation, and autoimmune diseases. However, the heterogeneity of TLS in gliomas is unclear. Therefore, it is necessary to identify TLS differences and define TLS subtypes. Methods: The TLS gene profile of 697 gliomas from The Cancer Genome Atlas (TCGA) was used for consensus clustering to identify robust clusters, and the reproducibility of the stratification method was assessed in Chinese Glioma Genome Atlas (CGGA) cohort1, CGGA_cohort2, and GSE16011. Analyses of clinical characteristics, immune infiltration, and potential biological functions were performed for each subtype. Results: Three resulting clusters (A, B, and C) were identified based on consensus clustering on the gene expression profile of TLS genes. There was a significant prognostic difference among the clusters, with a shorter survival for C than B and A. In comparison with the A and B subtypes, the C subtype was significantly enriched in primary immunodeficiency, intestinal immune network for lgG production, antigen processing and presentation, natural killer cell-mediated cytotoxicity, complement and coagulation cascades, cytokine-cytokine receptor interaction, leukocyte transendothelial migration, and some immune-related diseases. The levels of 23 immune cell types were higher in the C subtype than in the A and B subtypes. Finally, we developed and validated a riskscore based on TLS subtypes with better performance of prognosis prediction. Conclusions: This study presents a new stratification method according to the TLS gene profile and highlights TLS heterogeneity in gliomas. |
format | Online Article Text |
id | pubmed-8751592 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
spelling | pubmed-87515922022-01-12 Tertiary lymphoid structure stratifies glioma into three distinct tumor subtypes Zhou, Xingwang Li, Wenyan Yang, Jie Qi, Xiaolan Chen, Yimin Yang, Hua Chu, Liangzhao Aging (Albany NY) Research Paper Objective: Tertiary lymphoid structure (TLS), also known as ectopic lymphoid organs, are found in cancer, chronic inflammation, and autoimmune diseases. However, the heterogeneity of TLS in gliomas is unclear. Therefore, it is necessary to identify TLS differences and define TLS subtypes. Methods: The TLS gene profile of 697 gliomas from The Cancer Genome Atlas (TCGA) was used for consensus clustering to identify robust clusters, and the reproducibility of the stratification method was assessed in Chinese Glioma Genome Atlas (CGGA) cohort1, CGGA_cohort2, and GSE16011. Analyses of clinical characteristics, immune infiltration, and potential biological functions were performed for each subtype. Results: Three resulting clusters (A, B, and C) were identified based on consensus clustering on the gene expression profile of TLS genes. There was a significant prognostic difference among the clusters, with a shorter survival for C than B and A. In comparison with the A and B subtypes, the C subtype was significantly enriched in primary immunodeficiency, intestinal immune network for lgG production, antigen processing and presentation, natural killer cell-mediated cytotoxicity, complement and coagulation cascades, cytokine-cytokine receptor interaction, leukocyte transendothelial migration, and some immune-related diseases. The levels of 23 immune cell types were higher in the C subtype than in the A and B subtypes. Finally, we developed and validated a riskscore based on TLS subtypes with better performance of prognosis prediction. Conclusions: This study presents a new stratification method according to the TLS gene profile and highlights TLS heterogeneity in gliomas. Impact Journals 2021-12-26 /pmc/articles/PMC8751592/ /pubmed/34954691 http://dx.doi.org/10.18632/aging.203798 Text en Copyright: © 2021 Zhou et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Zhou, Xingwang Li, Wenyan Yang, Jie Qi, Xiaolan Chen, Yimin Yang, Hua Chu, Liangzhao Tertiary lymphoid structure stratifies glioma into three distinct tumor subtypes |
title | Tertiary lymphoid structure stratifies glioma into three distinct tumor subtypes |
title_full | Tertiary lymphoid structure stratifies glioma into three distinct tumor subtypes |
title_fullStr | Tertiary lymphoid structure stratifies glioma into three distinct tumor subtypes |
title_full_unstemmed | Tertiary lymphoid structure stratifies glioma into three distinct tumor subtypes |
title_short | Tertiary lymphoid structure stratifies glioma into three distinct tumor subtypes |
title_sort | tertiary lymphoid structure stratifies glioma into three distinct tumor subtypes |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8751592/ https://www.ncbi.nlm.nih.gov/pubmed/34954691 http://dx.doi.org/10.18632/aging.203798 |
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