Establishing molecular biomarkers for efficient demarcation of tumor and non-tumor tissue in oral squamous cell carcinoma

Abstract

Abstract Oral squamous cell carcinoma (OSCC), which accounts for 90% of head and neck cancers ( HNSC), is a prevalent cancer, especially in India, where it ranks among the top three cancers. Despite treatment advancements, OSCC incidence is rising, and recurrence remains a major concern. To improve patient prognosis, effective biomarkers for tumor demarcation are crucial. RNA isolation, library preparation, and RNA sequencing were performed on tumor and adjacent normal oral tissue samples. Transcriptomic analysis identified differentially expressed genes (DEGs) between tumor and normal tissues, which may serve as potential biomarkers. These findings were subsequently validated using RT-qPCR. The analysis revealed 704 upregulated and 1540 downregulated genes. Among these from the top 100 upregulated and downregulated genes, 15 and 9 genes respectively were also reported in the HNSC database of TCGA (The Cancer Genome Atlas). To identify potential biomarkers, the study evaluated multiple factors, including log2 fold change, average RPKM, ROC curve analysis, protein-protein interaction (PPI) network analysis and gene ontology (GO) analysis. The differential expression across various cancer stages and individual sample comparisons were also assessed. The upregulated genes MMP1 , MMP10 , MMP13 , MMP3 , ADAM12 , IL24 , and ISG15 demonstrated potential as biomarkers, with the highest log2 fold change, average RPKM, and AUC values. These significant genes could be valuable biomarkers for efficient demarcation between tumor and non-tumor tissues in oral cancer. This could lead to improved margin clearance, addressing concerns related to high recurrence rate of OSCC and ultimately enhance patient prognosis.