Identification of Candidate Biomarkers in Oral Cancer Using Integrated Bioinformatics Analysis: An Insight from Liquid Biopsy Approach

Background: Oral cancer is the sixth most prevalent cancer globally, posing a significant health concern, especially in India, where it accounts for one-third of all cases. The current work aimed to investigate gene signatures and identify their possible causes in OC using bioinformatics. Methods: The Gene Expression Omnibus (GEO) database was used to acquire data for OC. Differentially expressed genes (DEGs) in the control and case groups were determined using GeneSpring analysis. A protein–protein interaction (PPI) network and functional enrichment were built for DEGs. qPCR of four selected hub genes (STAT1, MMP9, CXCL8 and ISG15) was carried out in 20 OC tissues along with their adjacent normal tissue and 10 extracellular vesicle transcripts derived from serum samples of oral cancer patients and a healthy volunteer. Results: Experimental qPCR results of all four hub genes displayed a similar expression pattern as observed using bioinformatics tools. Conclusions: Together, the essential genes that were shortlisted might further increase our comprehension of the molecular processes underlying the etiology of OC and function as a possible candidate biomarker for OC.