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A meta-validated immune infiltration-related gene model predicts prognosis and immunotherapy sensitivity in HNSCC
BACKGROUND: Tumor microenvironment (TME) is of great importance to regulate the initiation and advance of cancer. The immune infiltration patterns of TME have been considered to impact the prognosis and immunotherapy sensitivity in Head and Neck squamous cell carcinoma (HNSCC). Whereas, specific mol...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9837972/ https://www.ncbi.nlm.nih.gov/pubmed/36639648 http://dx.doi.org/10.1186/s12885-023-10532-y |
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author | Ding, Yinghe Chu, Ling Cao, Qingtai Lei, Hanyu Li, Xinyu Zhuang, Quan |
author_facet | Ding, Yinghe Chu, Ling Cao, Qingtai Lei, Hanyu Li, Xinyu Zhuang, Quan |
author_sort | Ding, Yinghe |
collection | PubMed |
description | BACKGROUND: Tumor microenvironment (TME) is of great importance to regulate the initiation and advance of cancer. The immune infiltration patterns of TME have been considered to impact the prognosis and immunotherapy sensitivity in Head and Neck squamous cell carcinoma (HNSCC). Whereas, specific molecular targets and cell components involved in the HNSCC tumor microenvironment remain a twilight zone. METHODS: Immune scores of TCGA-HNSCC patients were calculated via ESTIMATE algorithm, followed by weighted gene co-expression network analysis (WGCNA) to filter immune infiltration-related gene modules. Univariate, the least absolute shrinkage and selection operator (LASSO), and multivariate cox regression were applied to construct the prognostic model. The predictive capacity was validated by meta-analysis including external dataset GSE65858, GSE41613 and GSE686. Model candidate genes were verified at mRNA and protein levels using public database and independent specimens of immunohistochemistry. Immunotherapy-treated cohort GSE159067, TIDE and CIBERSORT were used to evaluate the features of immunotherapy responsiveness and immune infiltration in HNSCC. RESULTS: Immune microenvironment was significantly associated with the prognosis of HNSCC patients. Total 277 immune infiltration-related genes were filtered by WGCNA and involved in various immune processes. Cox regression identified nine prognostic immune infiltration-related genes (MORF4L2, CTSL1, TBC1D2, C5orf15, LIPA, WIPF1, CXCL13, TMEM173, ISG20) to build a risk score. Most candidate genes were highly expressed in HNSCC tissues at mRNA and protein levels. Survival meta-analysis illustrated high prognostic accuracy of the model in the discovery cohort and validation cohort. Higher proportion of progression-free outcomes, lower TIDE scores and higher expression levels of immune checkpoint genes indicated enhanced immunotherapy responsiveness in low-risk patients. Decreased memory B cells, CD8+ T cells, follicular helper T cells, regulatory T cells, and increased activated dendritic cells and activated mast cells were identified as crucial immune cells in the TME of high-risk patients. CONCLUSIONS: The immune infiltration-related gene model was well-qualified and provided novel biomarkers for the prognosis of HNSCC. |
format | Online Article Text |
id | pubmed-9837972 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-98379722023-01-14 A meta-validated immune infiltration-related gene model predicts prognosis and immunotherapy sensitivity in HNSCC Ding, Yinghe Chu, Ling Cao, Qingtai Lei, Hanyu Li, Xinyu Zhuang, Quan BMC Cancer Research BACKGROUND: Tumor microenvironment (TME) is of great importance to regulate the initiation and advance of cancer. The immune infiltration patterns of TME have been considered to impact the prognosis and immunotherapy sensitivity in Head and Neck squamous cell carcinoma (HNSCC). Whereas, specific molecular targets and cell components involved in the HNSCC tumor microenvironment remain a twilight zone. METHODS: Immune scores of TCGA-HNSCC patients were calculated via ESTIMATE algorithm, followed by weighted gene co-expression network analysis (WGCNA) to filter immune infiltration-related gene modules. Univariate, the least absolute shrinkage and selection operator (LASSO), and multivariate cox regression were applied to construct the prognostic model. The predictive capacity was validated by meta-analysis including external dataset GSE65858, GSE41613 and GSE686. Model candidate genes were verified at mRNA and protein levels using public database and independent specimens of immunohistochemistry. Immunotherapy-treated cohort GSE159067, TIDE and CIBERSORT were used to evaluate the features of immunotherapy responsiveness and immune infiltration in HNSCC. RESULTS: Immune microenvironment was significantly associated with the prognosis of HNSCC patients. Total 277 immune infiltration-related genes were filtered by WGCNA and involved in various immune processes. Cox regression identified nine prognostic immune infiltration-related genes (MORF4L2, CTSL1, TBC1D2, C5orf15, LIPA, WIPF1, CXCL13, TMEM173, ISG20) to build a risk score. Most candidate genes were highly expressed in HNSCC tissues at mRNA and protein levels. Survival meta-analysis illustrated high prognostic accuracy of the model in the discovery cohort and validation cohort. Higher proportion of progression-free outcomes, lower TIDE scores and higher expression levels of immune checkpoint genes indicated enhanced immunotherapy responsiveness in low-risk patients. Decreased memory B cells, CD8+ T cells, follicular helper T cells, regulatory T cells, and increased activated dendritic cells and activated mast cells were identified as crucial immune cells in the TME of high-risk patients. CONCLUSIONS: The immune infiltration-related gene model was well-qualified and provided novel biomarkers for the prognosis of HNSCC. BioMed Central 2023-01-13 /pmc/articles/PMC9837972/ /pubmed/36639648 http://dx.doi.org/10.1186/s12885-023-10532-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Ding, Yinghe Chu, Ling Cao, Qingtai Lei, Hanyu Li, Xinyu Zhuang, Quan A meta-validated immune infiltration-related gene model predicts prognosis and immunotherapy sensitivity in HNSCC |
title | A meta-validated immune infiltration-related gene model predicts prognosis and immunotherapy sensitivity in HNSCC |
title_full | A meta-validated immune infiltration-related gene model predicts prognosis and immunotherapy sensitivity in HNSCC |
title_fullStr | A meta-validated immune infiltration-related gene model predicts prognosis and immunotherapy sensitivity in HNSCC |
title_full_unstemmed | A meta-validated immune infiltration-related gene model predicts prognosis and immunotherapy sensitivity in HNSCC |
title_short | A meta-validated immune infiltration-related gene model predicts prognosis and immunotherapy sensitivity in HNSCC |
title_sort | meta-validated immune infiltration-related gene model predicts prognosis and immunotherapy sensitivity in hnscc |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9837972/ https://www.ncbi.nlm.nih.gov/pubmed/36639648 http://dx.doi.org/10.1186/s12885-023-10532-y |
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