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Identification of Candidate Biomarkers and Analysis of Prognostic Values in Oral Squamous Cell Carcinoma
Objectives: Oral squamous cell carcinoma (OSCC) is the most common oral cancer with a poor prognosis owing to limited understanding of the disease mechanisms. The aim of this study was to explore and identify the potential biomarkers in OSCC by integrated bioinformatics analysis. Materials and Metho...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6813197/ https://www.ncbi.nlm.nih.gov/pubmed/31681590 http://dx.doi.org/10.3389/fonc.2019.01054 |
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author | Huang, Guang-zhao Wu, Qing-qing Zheng, Ze-nan Shao, Ting-ru Lv, Xiao-Zhi |
author_facet | Huang, Guang-zhao Wu, Qing-qing Zheng, Ze-nan Shao, Ting-ru Lv, Xiao-Zhi |
author_sort | Huang, Guang-zhao |
collection | PubMed |
description | Objectives: Oral squamous cell carcinoma (OSCC) is the most common oral cancer with a poor prognosis owing to limited understanding of the disease mechanisms. The aim of this study was to explore and identify the potential biomarkers in OSCC by integrated bioinformatics analysis. Materials and Methods: Expression profiles of long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) were downloaded from The Cancer Genome Atlas (TCGA) and differentially expressed RNAs (DERNAs) were subsequently identified in OSCC by bioinformatics analysis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to analyze DERNAs. Then, the competing endogenous RNA (ceRNA) network was constructed in Cytoscape and the protein -protein interaction (PPI) network was established in the STRING database. We established a risk model to predict the overall survival of OSCC on the basis of DElncRNAs with Kaplan–Meier analysis and combined with logrank p test. Furthermore, we identified potential biomarkers by combining univariate Cox regression with overall survival rate, which were then validated in Gene Expression Omnibus (GEO), OSCC cell lines and OSCC specimens. Results: A total of 1,919 DEmRNAs, 286 DElncRNAs and 111 DEmiRNAs were found to be dysregulated in OSCC. A ceRNA network included 46 DElncRNAs,7 DEmiRNAs and 10 DEmRNAs, and the PPI network included 712 DEmRNAs including 31 hub genes. Moreover, a 7 lncRNAs risk model was established and four genes (CMA1, GNA14, HCG22, HOTTIP) were identified as biomarkers on overall survival in patients with OSCC. Conclusions: This study successfully constructed a ceRNA network and a PPI network which play a crucial role in OSCC. A risk model was established to predict the prognosis, and four DERNAs are revealed with overall survival in patients with OSCC, suggesting that they may be potential biomarkers in tumor diagnosis and treatment. |
format | Online Article Text |
id | pubmed-6813197 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-68131972019-11-01 Identification of Candidate Biomarkers and Analysis of Prognostic Values in Oral Squamous Cell Carcinoma Huang, Guang-zhao Wu, Qing-qing Zheng, Ze-nan Shao, Ting-ru Lv, Xiao-Zhi Front Oncol Oncology Objectives: Oral squamous cell carcinoma (OSCC) is the most common oral cancer with a poor prognosis owing to limited understanding of the disease mechanisms. The aim of this study was to explore and identify the potential biomarkers in OSCC by integrated bioinformatics analysis. Materials and Methods: Expression profiles of long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) were downloaded from The Cancer Genome Atlas (TCGA) and differentially expressed RNAs (DERNAs) were subsequently identified in OSCC by bioinformatics analysis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to analyze DERNAs. Then, the competing endogenous RNA (ceRNA) network was constructed in Cytoscape and the protein -protein interaction (PPI) network was established in the STRING database. We established a risk model to predict the overall survival of OSCC on the basis of DElncRNAs with Kaplan–Meier analysis and combined with logrank p test. Furthermore, we identified potential biomarkers by combining univariate Cox regression with overall survival rate, which were then validated in Gene Expression Omnibus (GEO), OSCC cell lines and OSCC specimens. Results: A total of 1,919 DEmRNAs, 286 DElncRNAs and 111 DEmiRNAs were found to be dysregulated in OSCC. A ceRNA network included 46 DElncRNAs,7 DEmiRNAs and 10 DEmRNAs, and the PPI network included 712 DEmRNAs including 31 hub genes. Moreover, a 7 lncRNAs risk model was established and four genes (CMA1, GNA14, HCG22, HOTTIP) were identified as biomarkers on overall survival in patients with OSCC. Conclusions: This study successfully constructed a ceRNA network and a PPI network which play a crucial role in OSCC. A risk model was established to predict the prognosis, and four DERNAs are revealed with overall survival in patients with OSCC, suggesting that they may be potential biomarkers in tumor diagnosis and treatment. Frontiers Media S.A. 2019-10-18 /pmc/articles/PMC6813197/ /pubmed/31681590 http://dx.doi.org/10.3389/fonc.2019.01054 Text en Copyright © 2019 Huang, Wu, Zheng, Shao and Lv. http://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 | Oncology Huang, Guang-zhao Wu, Qing-qing Zheng, Ze-nan Shao, Ting-ru Lv, Xiao-Zhi Identification of Candidate Biomarkers and Analysis of Prognostic Values in Oral Squamous Cell Carcinoma |
title | Identification of Candidate Biomarkers and Analysis of Prognostic Values in Oral Squamous Cell Carcinoma |
title_full | Identification of Candidate Biomarkers and Analysis of Prognostic Values in Oral Squamous Cell Carcinoma |
title_fullStr | Identification of Candidate Biomarkers and Analysis of Prognostic Values in Oral Squamous Cell Carcinoma |
title_full_unstemmed | Identification of Candidate Biomarkers and Analysis of Prognostic Values in Oral Squamous Cell Carcinoma |
title_short | Identification of Candidate Biomarkers and Analysis of Prognostic Values in Oral Squamous Cell Carcinoma |
title_sort | identification of candidate biomarkers and analysis of prognostic values in oral squamous cell carcinoma |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6813197/ https://www.ncbi.nlm.nih.gov/pubmed/31681590 http://dx.doi.org/10.3389/fonc.2019.01054 |
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