Identification of a six-gene prognostic signature for oral squamous cell carcinoma.
Jiaying WangZhaoyang WangFanzhi KongRui HanWenbin SongDi ChenLingxue BuShuangyi WangJin YueLei MaPublished in: Journal of cellular physiology (2019)
Oral squamous cell carcinoma (OSCC) is one of the most common types of malignancies worldwide, and its morbidity and mortality have increased in the near term. Consequently, the purpose of the present study was to identify the notable differentially expressed genes (DEGs) involved in their pathogenesis to obtain new biomarkers or potential therapeutic targets for OSCC. The gene expression profiles of the microarray datasets GSE85195, GSE23558, and GSE10121 were obtained from the Gene Expression Omnibus (GEO) database. After screening the DEGs in each GEO dataset, 249 DEGs in OSCC tissues were obtained. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology pathway enrichment analysis was employed to explore the biological functions and pathways of the above DEGs. A protein-protein interaction network was constructed to obtain a central gene. The corresponding total survival information was analyzed in patients with oral cancer from The Cancer Genome Atlas (TCGA). A total of six candidate genes (CXCL10, OAS2, IFIT1, CCL5, LRRK2, and PLAUR) closely related to the survival rate of patients with oral cancer were identified, and expression verification and overall survival analysis of six genes were performed based on TCGA database. Time-dependent receiver operating characteristic curve analysis yields predictive accuracy of the patient's overall survival. At the same time, the six genes were further verified by quantitative real-time polymerase chain reaction using samples obtained from the patients recruited to the present study. In conclusion, the present study identified the prognostic signature of six genes in OSCC for the first time via comprehensive bioinformatics analysis, which could become potential prognostic markers for OCSS and may provide potential therapeutic targets for tumors.
Keyphrases
- protein protein
- bioinformatics analysis
- small molecule
- genome wide
- genome wide identification
- gene expression
- dna methylation
- genome wide analysis
- copy number
- transcription factor
- high resolution
- ejection fraction
- poor prognosis
- healthcare
- free survival
- case report
- squamous cell carcinoma
- young adults
- papillary thyroid
- climate change
- lymph node metastasis
- health information
- adverse drug