Investigation of MicroRNA-Target Gene Regulatory Networks in Oral Squamous Cell carcinoma

Jyotsna Choubey; Tanushree Chatterjee

Authors

Jyotsna Choubey Department of Biotechnology, Raipur Institute of Technology, Raipur- 492001, Chhattisgarh, India
Tanushree Chatterjee Department of Biotechnology, Raipur Institute of Technology, Raipur- 492001, Chhattisgarh, India

Keywords:

Oral cancer, hub genes, transcription factor

Abstract

Oral squamous cell carcinoma (OSCC) is the seventh most common cancer worldwide. Despite improvement in its control, morbidity and mortality, rates have improved little in the past decades. To find differential miRNA and gene expression, GSE98463 and GSE3524 expression profiles were acquired from the Gene Expression Omnibus (GEO) database. Screened DE-miRNAs' transcription factors and target genes were predicted. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to predict biological functions. Using Cytoscape software, protein–protein interaction (PPI) networks and hub genes were found in the miRNA-mRNA regulation network. Further hub gene expression and prognostic functions were examined. We examined 34 DE-miRNAs, 23 upregulated and 11 downregulated. Most screened DE-miRNAs may be regulated by transcription factor SP1. 2190 and 1061 predicted target genes were obtained for upregulated and downregulated DE-miRNAs, respectively. Subsequently, 452 upregulated DEGs and 221 downregulated DEGs were identified. Then, 18 and 58 potential downregulated and upregulated genes commonly appeared in target genes of DE-miRNAs and DEGs were selected for GO annotation and KEGG pathway enrichment analysis. The candidate target genes were significantly enriched for the Protein digestion and absorption, Relaxin signalling pathway, and AGE-RAGE signalling pathway. Construction and analysis of PPI network showed that MMP9 and COL1A1were recognized as hub genes with the highest connectivity degrees. Expression analytic result of the top 10 hub genes in OSCC using GEPIA database was generally identical with previous differential expression analysis for TCGA data and its expression was significantly associated with patients’ overall survival. We constructed a putative oral cancer-related miRNA-mRNA regulation network in this study to better understand molecular mechanisms and find novel treatment targets for OSCC. Further trials are needed to confirm our findings.

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