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Establishment and Validation of a Comprehensive Prognostic Model for Patients With HNSCC Metastasis
OBJECTIVE: To identify biomarkers related to head and neck squamous cell carcinoma (HNSCC) metastasis and establish a prognostic model for patients with HNSCC. METHODS: HNSCC mRNA expression data of metastasis and non-metastatic samples were downloaded from The Cancer Genome Atlas (TCGA) and Gene Ex...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8312248/ https://www.ncbi.nlm.nih.gov/pubmed/34322156 http://dx.doi.org/10.3389/fgene.2021.685104 |
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author | Shen, Yajun Li, Lingyu Lu, Yunping Zhang, Min Huang, Xin Tang, Xiaofei |
author_facet | Shen, Yajun Li, Lingyu Lu, Yunping Zhang, Min Huang, Xin Tang, Xiaofei |
author_sort | Shen, Yajun |
collection | PubMed |
description | OBJECTIVE: To identify biomarkers related to head and neck squamous cell carcinoma (HNSCC) metastasis and establish a prognostic model for patients with HNSCC. METHODS: HNSCC mRNA expression data of metastasis and non-metastatic samples were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. After screening the differentially expressed genes (DEGs) in the two datasets, a prognostic model, including clinical factors and biomarkers, was established, and verified in 36 samples of HNSCC by quantitative real-time transcription (qRT)-PCR. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene sets enrichment analysis (GSEA) were consulted to explore the functions of the DEGs. RESULTS: In total, 108 DEGs were identified. GSEA, GO, and KEGG analyses showed that these DEGs were mainly involved in the proliferation and metastasis of HNSCC. Six genes that were significantly related to metastasis, immune cell infiltration and prognosis were further identified to construct a prognostic gene signature. The reliability of the gene signature was verified in 36 samples of HNSCC. A prognostic model, including tumor stage, risk level, and a nomogram for prediction were further established. Receiver operating characteristic (ROC) analysis, decision curve analysis (DCA), C-index, and calibration plots showed that the model and nomogram perform well. CONCLUSION: We constructed a six-gene signature and a nomogram with high performance in predicting the prognosis of patients with HNSCC metastasis. |
format | Online Article Text |
id | pubmed-8312248 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-83122482021-07-27 Establishment and Validation of a Comprehensive Prognostic Model for Patients With HNSCC Metastasis Shen, Yajun Li, Lingyu Lu, Yunping Zhang, Min Huang, Xin Tang, Xiaofei Front Genet Genetics OBJECTIVE: To identify biomarkers related to head and neck squamous cell carcinoma (HNSCC) metastasis and establish a prognostic model for patients with HNSCC. METHODS: HNSCC mRNA expression data of metastasis and non-metastatic samples were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. After screening the differentially expressed genes (DEGs) in the two datasets, a prognostic model, including clinical factors and biomarkers, was established, and verified in 36 samples of HNSCC by quantitative real-time transcription (qRT)-PCR. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene sets enrichment analysis (GSEA) were consulted to explore the functions of the DEGs. RESULTS: In total, 108 DEGs were identified. GSEA, GO, and KEGG analyses showed that these DEGs were mainly involved in the proliferation and metastasis of HNSCC. Six genes that were significantly related to metastasis, immune cell infiltration and prognosis were further identified to construct a prognostic gene signature. The reliability of the gene signature was verified in 36 samples of HNSCC. A prognostic model, including tumor stage, risk level, and a nomogram for prediction were further established. Receiver operating characteristic (ROC) analysis, decision curve analysis (DCA), C-index, and calibration plots showed that the model and nomogram perform well. CONCLUSION: We constructed a six-gene signature and a nomogram with high performance in predicting the prognosis of patients with HNSCC metastasis. Frontiers Media S.A. 2021-07-12 /pmc/articles/PMC8312248/ /pubmed/34322156 http://dx.doi.org/10.3389/fgene.2021.685104 Text en Copyright © 2021 Shen, Li, Lu, Zhang, Huang and Tang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Shen, Yajun Li, Lingyu Lu, Yunping Zhang, Min Huang, Xin Tang, Xiaofei Establishment and Validation of a Comprehensive Prognostic Model for Patients With HNSCC Metastasis |
title | Establishment and Validation of a Comprehensive Prognostic Model for Patients With HNSCC Metastasis |
title_full | Establishment and Validation of a Comprehensive Prognostic Model for Patients With HNSCC Metastasis |
title_fullStr | Establishment and Validation of a Comprehensive Prognostic Model for Patients With HNSCC Metastasis |
title_full_unstemmed | Establishment and Validation of a Comprehensive Prognostic Model for Patients With HNSCC Metastasis |
title_short | Establishment and Validation of a Comprehensive Prognostic Model for Patients With HNSCC Metastasis |
title_sort | establishment and validation of a comprehensive prognostic model for patients with hnscc metastasis |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8312248/ https://www.ncbi.nlm.nih.gov/pubmed/34322156 http://dx.doi.org/10.3389/fgene.2021.685104 |
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