Project description:Chewing betel nut is an important risk factor for the carcinogenesis of tongue squamous cell carcinoma (TSCC), but the mechanism is still unknown.To screen the lncRNAs associated with betel nut chewing-induced TSCC and identify potential biomarkers for the TSCC, we collected 5 pairs of TSCC and paracancerous tissues and monitored the resultant lncRNA and mRNA expression profiles using an lncRNA microarray. All 5 patients have a history of areca nut chewing.
Project description:circRNA microarrays were performed with 2 pairs of tongue squamous cell carcinoma and their matched adjacent tissues. The statistical significance of the difference was estimated by t-test. circRNAs having fold changes 1.5 and p-values 0.05 are selected as the significantly differentially expressed. The data from microarray indicated that there were 54 upregulated and 70 downregulated circRNAs in TSCC tissues.
Project description:Chemoresistance frequently leads to therapeutic failure in tongue squamous cell carcinoma (TSCC). Increasing evidence has shown that Long noncoding RNAs (lncRNAs) play pivotal roles in biological properties of cancer. However, the roles and mechanisms of lncRNAs in cisplatin resistance are not well understood. In this study, to identify the lncRNAs induced by chemotherapy, we profile the expression of lncRNAs in cisplatin-resistant TSCC cells using LncRNA microarrays.
Project description:Purpose: The purpose of this study was to identify aberrantly expressed lncRNAs, circular RNAs and the associated TF‐mRNA network in TSCC. Methods: Tongue tumor noncoding and mRNA profiles of tongue squamous cell carcinoma and adjacent noncancerous tissues were generated by deep sequencing, using Illumina HiSeq 4000. Results: Using an optimized data analysis workflow. Conclusions: we found a profile of dysregulated lncRNAs, TFs and mRNAs that could serve as prospective clinical biomarkers because of their tissue specificity and association with the tumorigenesis and progression of TSCC.
Project description:The current study analyzed a unique, serum-free medium derived tongue squamous cell carcinoma (TSCC) line termed LK0412 relative to the normal state to elucidate biomarkers at the protein and transcript level. A bioinformatics approach using Gene Ontology categories, gene networks and signature evaluation was applied to combine the protein and transcript data for identification of various gene signatures. The generated signatures were further assessed in public available data sets from normal and tumor tongue tissues. The analysis identified a novel gene signature that may improve the diagnosis and treatment of TSCC.
