Comprehensive analysis of transcriptome data for identifying biomarkers and therapeutic targets in head and neck squamous cell carcinoma

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignancy worldwide. Accumulating evidences have highlighted the importance of transcriptome data during HNSCC tumorigenesis. The aim of this study was to identify significant genes as effective biomarkers for HNSCC and constructed miRNA-mRNA regulatory network for a more comprehensive understanding of the underlying molecular mechanisms. METHODS: A total of four independent microarrays conducted on HNSCC samples were downloaded from the Gene Expression Omnibus (GEO) and analyzed through R software. FunRich was applied to predict potential transcription factors and targeted genes of miRNAs. Protein-protein interaction (PPI) network and miRNA-mRNA regulatory network were constructed in Cytoscape. Additionally, the database for annotation, visualization, and integrated discovery (DAVID) was utilized to perform GO and KEGG pathway enrichment analyses. Validation of gene expression levels was conducted by online databases and qPCR experiments. RESULTS: A total of 35 and 193 differentially expressed miRNAs (DEMs) and mRNAs (DEGs) were screened out by the limma package in R. The interactive network of the overlapping DEGs presented three significant modules and ten hub genes (FN1, MMP3, SPP1, STAT1, LOX, CXCL5, CXCL11, ISG15, IFIT3, and RSAD2). Predicted target genes of DEMs were visualized in Cytoscape and six miRNA-mRNA regulatory pairs were identified. Further validation demonstrated the upregulation of SLC16A1 and COL4A1 in HNSCC. CONCLUSIONS: We performed an integrated and comprehensive bioinformatics analysis of miRNAs and mRNAs in HNSCC, contributing to explore the underlying regulatory mechanisms and to identify genetic biomarkers and therapeutic targets for HNSCC.