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 Method...

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Main Authors: Guang-zhao Huang, Qing-qing Wu, Ze-nan Zheng, Ting-ru Shao, Xiao-Zhi Lv
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-10-01
Series:Frontiers in Oncology
Subjects:
Online Access:https://www.frontiersin.org/article/10.3389/fonc.2019.01054/full
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spelling doaj-7b9eb26698044e2c92143ca4c90800202020-11-25T00:48:01ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2019-10-01910.3389/fonc.2019.01054483684Identification of Candidate Biomarkers and Analysis of Prognostic Values in Oral Squamous Cell CarcinomaGuang-zhao HuangQing-qing WuZe-nan ZhengTing-ru ShaoXiao-Zhi LvObjectives: 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.https://www.frontiersin.org/article/10.3389/fonc.2019.01054/fullcompeting endogenous RNAprotein-protein interactionlong non-coding RNAbiomarkeroral squamous cell carcinoma
collection DOAJ
language English
format Article
sources DOAJ
author Guang-zhao Huang
Qing-qing Wu
Ze-nan Zheng
Ting-ru Shao
Xiao-Zhi Lv
spellingShingle Guang-zhao Huang
Qing-qing Wu
Ze-nan Zheng
Ting-ru Shao
Xiao-Zhi Lv
Identification of Candidate Biomarkers and Analysis of Prognostic Values in Oral Squamous Cell Carcinoma
Frontiers in Oncology
competing endogenous RNA
protein-protein interaction
long non-coding RNA
biomarker
oral squamous cell carcinoma
author_facet Guang-zhao Huang
Qing-qing Wu
Ze-nan Zheng
Ting-ru Shao
Xiao-Zhi Lv
author_sort Guang-zhao Huang
title 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_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_sort identification of candidate biomarkers and analysis of prognostic values in oral squamous cell carcinoma
publisher Frontiers Media S.A.
series Frontiers in Oncology
issn 2234-943X
publishDate 2019-10-01
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.
topic competing endogenous RNA
protein-protein interaction
long non-coding RNA
biomarker
oral squamous cell carcinoma
url https://www.frontiersin.org/article/10.3389/fonc.2019.01054/full
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