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Exploration of prognostic biomarkers in head and neck squamous cell carcinoma microenvironment from TCGA database

BACKGROUND: Immune checkpoint blockade (ICB) therapies have redefined human cancer treatment, including for head and neck squamous cell carcinoma (HNSCC). However, clinical responses to various immune checkpoint inhibitors are often accompanied by immune-related adverse events (irAEs). Therefore, it...

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Autores principales: Li, Ying, Bi, Jianping, Pi, Guoliang, He, Hanping, Li, Yanping, Han, Guang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10009575/
https://www.ncbi.nlm.nih.gov/pubmed/36923087
http://dx.doi.org/10.21037/atm-22-6481
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author Li, Ying
Bi, Jianping
Pi, Guoliang
He, Hanping
Li, Yanping
Han, Guang
author_facet Li, Ying
Bi, Jianping
Pi, Guoliang
He, Hanping
Li, Yanping
Han, Guang
author_sort Li, Ying
collection PubMed
description BACKGROUND: Immune checkpoint blockade (ICB) therapies have redefined human cancer treatment, including for head and neck squamous cell carcinoma (HNSCC). However, clinical responses to various immune checkpoint inhibitors are often accompanied by immune-related adverse events (irAEs). Therefore, it is crucial to obtain a comprehensive understanding of the association between different immune tumor microenvironments (TMEs) and the immunotherapeutic response. METHODS: The research data were obtained from The Cancer Genome Atlas (TCGA) database. We applied RNA-seq genomic data from tumor biopsies to assess the immune TME in HNSCC. As the TME is a heterogeneous system that is highly associated with HNSCC progression and clinical outcome, we relied on the Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm to calculate immune and stromal scores that were evaluated based on the immune or stromal components in the TME. Then, the Tumor Immune Dysfunction and Exclusion algorithm (TIDE) was used to predict the benefits of ICB to each patient. Finally, we identified specific prognostic tumor-infiltrating immune cells (TIICs) by quantifying the cellular composition of the immune response in HNSCC and its association to survival outcome, using the CIBERSORT algorithm. RESULTS: Utilizing the HNSCC cohort of the TCGA database and TIDE and ESTIMATE algorithm-derived immune scores, we obtained a list of microenvironment-associated lncRNAs that predicted different clinical outcomes in HNSCC patients. We validated these correlations in a different HNSCC cohort available from the TCGA database and provided insight into the prediction of response to ICB therapies in HNSCC. CONCLUSIONS: This study confirmed that CD8(+) T cells were significantly associated with better survival in HNSCC and verified that the top five significantly mutated genes (SMGs) in the TCGA HNSCC cohort were TP53, TTN, FAT1, CDKN2A, and MUC16. A high level of CD8(+) T cells and high immune and stroma scores corresponded to a better survival probability in HNSCC.
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spelling pubmed-100095752023-03-14 Exploration of prognostic biomarkers in head and neck squamous cell carcinoma microenvironment from TCGA database Li, Ying Bi, Jianping Pi, Guoliang He, Hanping Li, Yanping Han, Guang Ann Transl Med Original Article BACKGROUND: Immune checkpoint blockade (ICB) therapies have redefined human cancer treatment, including for head and neck squamous cell carcinoma (HNSCC). However, clinical responses to various immune checkpoint inhibitors are often accompanied by immune-related adverse events (irAEs). Therefore, it is crucial to obtain a comprehensive understanding of the association between different immune tumor microenvironments (TMEs) and the immunotherapeutic response. METHODS: The research data were obtained from The Cancer Genome Atlas (TCGA) database. We applied RNA-seq genomic data from tumor biopsies to assess the immune TME in HNSCC. As the TME is a heterogeneous system that is highly associated with HNSCC progression and clinical outcome, we relied on the Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm to calculate immune and stromal scores that were evaluated based on the immune or stromal components in the TME. Then, the Tumor Immune Dysfunction and Exclusion algorithm (TIDE) was used to predict the benefits of ICB to each patient. Finally, we identified specific prognostic tumor-infiltrating immune cells (TIICs) by quantifying the cellular composition of the immune response in HNSCC and its association to survival outcome, using the CIBERSORT algorithm. RESULTS: Utilizing the HNSCC cohort of the TCGA database and TIDE and ESTIMATE algorithm-derived immune scores, we obtained a list of microenvironment-associated lncRNAs that predicted different clinical outcomes in HNSCC patients. We validated these correlations in a different HNSCC cohort available from the TCGA database and provided insight into the prediction of response to ICB therapies in HNSCC. CONCLUSIONS: This study confirmed that CD8(+) T cells were significantly associated with better survival in HNSCC and verified that the top five significantly mutated genes (SMGs) in the TCGA HNSCC cohort were TP53, TTN, FAT1, CDKN2A, and MUC16. A high level of CD8(+) T cells and high immune and stroma scores corresponded to a better survival probability in HNSCC. AME Publishing Company 2023-02-28 2023-02-28 /pmc/articles/PMC10009575/ /pubmed/36923087 http://dx.doi.org/10.21037/atm-22-6481 Text en 2023 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Li, Ying
Bi, Jianping
Pi, Guoliang
He, Hanping
Li, Yanping
Han, Guang
Exploration of prognostic biomarkers in head and neck squamous cell carcinoma microenvironment from TCGA database
title Exploration of prognostic biomarkers in head and neck squamous cell carcinoma microenvironment from TCGA database
title_full Exploration of prognostic biomarkers in head and neck squamous cell carcinoma microenvironment from TCGA database
title_fullStr Exploration of prognostic biomarkers in head and neck squamous cell carcinoma microenvironment from TCGA database
title_full_unstemmed Exploration of prognostic biomarkers in head and neck squamous cell carcinoma microenvironment from TCGA database
title_short Exploration of prognostic biomarkers in head and neck squamous cell carcinoma microenvironment from TCGA database
title_sort exploration of prognostic biomarkers in head and neck squamous cell carcinoma microenvironment from tcga database
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10009575/
https://www.ncbi.nlm.nih.gov/pubmed/36923087
http://dx.doi.org/10.21037/atm-22-6481
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