Integrated Bioinformatics Analysis of mRNAs and miRNAs Identified Potential Biomarkers of Oral Squamous Cell Carcinoma

Abstract

Background: Oral cancer is a frequently encountered neoplasm of the head and neck region, being the eighth most common type of human malignancy worldwide. Despite improvement in its control, morbidity and mortality, rates have improved little in the past decades. The present investigations about gene interaction and pathways still could not clear the appearance and development of oral squamous cell carcinoma (OSCC), completely. The aim of this study is to investigate the key genes and microRNAs interaction in OSCC. Materials and Methods: The microarray datasets GSE13601 and GSE98463, including mRNA and miRNA profiles, were extracted from the GEO database and were analyzed using GEO2R. Functional and pathway enrichment analyses were performed by using the DAVID database. The protein–protein interaction (PPI) network was constructed and analyzed using STRING database and Cytoscape software, respectively. Finally, miRDB was applied to predict the targets of the differentially expressed miRNAs (DEMs). Results: Totally, 97 differentially expressed genes (DEGs) were found in OSCC, including 66 up-regulated and 31 down-regulated genes. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses showed that up-regulated genes were significantly enriched in movement of cell or subcellular component, cell adhesion, biological adhesion, cellular localization, apoptotic signaling pathway, while the down-regulated genes were enriched in muscle system process and oxidation-reduction process. From the PPI network, the top 10 nodes with the highest degree were detected as hub genes. In addition, 18 DEMs were screened, which included 7 up-regulated and 11 down-regulated miRNAs. STAT1 was potentially targeted by three miRNAs, including has-miR-6825-5P, has-miR-4495, and has-miR-5580-3P. Conclusion: The roles of DEMs such as hsa-mir-5580-3p in OSCC through interactions with DEGs CD44, ACLY, ACTR3, STAT1, LAMC2 and YWHAZ may offer a suitable candidate biomarker pattern for diagnosis, prognosis and treatment processes in OSCC.

Identification of Prognosis Associated microRNAs in HNSCC Subtypes Based on TCGA Dataset

“…Enrichment analysis in downregulated and upregulated miRNAs revealed that protein processing in endoplasmic reticulum, proteoglycans in cancer, the Hippo signaling pathway, and the TGF-beta signaling pathway are the most probable pathways based on miRNAs interaction levels. This goes in accordance with our previous analysis of miRNA expression in oral cancer [ 20 ], and other enrichment analysis [ 21 , 22 ]. The alteration of the Hippo signaling mechanism has been reported in different types of cancer, and the altered expression of some of its components has been associated with cell migration and invasion.…”

“…Regarding miRNAs’ over- or under-expressed proportions, in previous microarray studies [ 20 ], we have obtained a greater number of under-expressed than over-expressed miRNAs, and in the results of this study we see that in some locations this trend is maintained (such as in the mouth, floor of the mouth, or tongue), but in other locations the opposite is true (such as in the tonsil, cheek mucosa, lip, or base of the tongue). In other bioinformatics studies we also confirmed this trend [ 21 ]. We cannot forget, however, that in cancer we have other mechanisms of genetic regulation, such as mutations, and epigenetics, such as methylations [ 38 ] or the expression of other non-coding RNAs such as lncRNAs (long non coding RNAs) [ 39 ] or snoRNAs (small nucleolar RNAs) [ 40 ], that influence the formation and progression of the HNSCC.…”

Droplet Digital PCR Analysis of Liquid Biopsy Samples Unveils the Diagnostic Role of hsa-miR-133a-3p and hsa-miR-375-3p in Oral Cancer

“…In order to find novel effective biomarkers, several studies have tried to study the predictive value of several epigenetic factors for oral cancer, including DNA methylation hotspots and the alteration of non-coding RNAs (ncRNAs), however, these identified biomarkers are still under validation [36][37][38][39][40][41]. In this scenario, to the best of our knowledge, our research group was the first to comprehensively analyze all the bioinformatics data about miRNAs expression in oral cancer patients through the integrated analysis of miRNAs expression datasets obtained from Gene Expression Omnibus DataSets and The Cancer Genome Atlas databases [24].…”

An Investigation of Post-radiation Gene Expression Profiles: A System Biology Study

“…Bioinformatics as a useful method is applied to resolve problems which are tied to the complex data of high-throughput investigations. 22,23 Thus, among the large numbers of dysregulated genes 177 DEGs were candidates to be assessed. Pathway analysis is applied to screen and also elucidate the results of such experiments, and findings are published to introduce the limited numbers of important dysregulated genes and critical affected pathways.…”