Bioinformatics analysis: A roadmap to an aggressiveness model for Oral Squamous cell carcinoma key differentiated genes | ||||
| Alexandria Dental Journal | ||||
| Articles in Press, Corrected Proof, Available Online from 16 April 2025 PDF (158.6 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/adjalexu.2025.342797.1570 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Heba R Mady  1; Nefertiti Elnikhely2; Samar El Achy3; Enas M Omar4; Omneya R Ramadan5
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| 1assistant lecturer, oral pathology department, faculty of dentistry, Alexandria university | ||||
| 2Assistant Professor of Biotechnology, Institute of Graduate Studies and Research, Alexandria University | ||||
| 3Assistant Professor General Pathology, Faculty of Medicine, Alexandria University. | ||||
| 4Assistant Professor of Oral Pathology, Faculty of Dentistry, Alexandria University. | ||||
| 5Professor of Oral Pathology, Faculty of Dentistry, Alexandria University. | ||||
| Abstract | ||||
| Introduction Bioinformatics is a cross-disciplinary research field that combines computer science with biological science. The most fundamental yet frequently most impactful application of bioinformatics analysis is identifying variations in gene expression across two or more circumstances in a process known as "differential expression”. Identification of genes involved in oral squamous cell carcinoma initiation, progression and metastasis is a crucial breakthrough aiming at implementing targeted gene therapy as a promising oral cancer therapeutic modality. Objectives To identify key differentially expressed genes (DEGs) related to progression and aggressiveness of oral squamous cell carcinoma using bioinformatics analysis. Material and Methods 1. In the current study differential gene expression analysis has been done between low stage tumor cases (n=73) and high stages tumor cases (n=226) using the (DEseq2) package in R 2. GO enrichment and KEGG enrichment analysis of the significant DEGs were done using DAVID online tool and Enrich R online tool. 3. Selected hub genes of the protein-protein interaction network were obtained using the CytoHubba plugin MCC Algorithm Results A total of 65 significant DEGs were detected Functional enrichment analysis of the significant DEGs showed that: • The most enriched biological processes term was keratinization and defense response to bacteria • The most enriched cellular component term was the extracellular space • The most enriched molecular function term was cysteine-type endopeptidase inhibitor activity, • The most enriched KEGG terms was Salivary secretion. Conclusion In summary, hub genes discovered were the gene sequence of STATH, HTN3, HTN1, CST4, SMRB, LPO, BPIFA2. | ||||
| Keywords | ||||
| OSCC; Differentially expressed genes; Hub genes | ||||
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