Add like
Add dislike
Add to saved papers

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 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.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

Related Resources

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app