Journal of the Egyptian National Cancer Institute · 2026
Identification of potential biomarkers for oral squamous cell carcinoma through multi-cohort bioinformatic analysis.
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Kamei Duanreiliu, Kaur Simran, Priya Anjali, Bansal Akshay, Yadav Aarti, Kumar Ray Ashwini, Agrawal Yamini
Аннотация
BACKGROUND: Oral squamous cell carcinoma (OSCC) arises in the context of diverse etiological exposures, such as tobacco, alcohol, areca nut use and viral infections. This etiological heterogeneity drives distinct molecular alterations, contributing to tumor complexity and significant challenges in identifying robust, clinically applicable biomarkers.
METHODS: To resolve this, we employed an integrative bioinformatics approach, analyzing five gene expression datasets retrieved from the GEO repository, which encompass heterogenous clinical samples with diverse clinical stages of OSCC Differentially expressed genes (DEGs) were identified using stringent thresholds (|LogFC|≥ 1.5 to 3.0; p < 0.05), followed by GO and KEGG pathway enrichment analysis. A protein-protein interaction (PPI) connectome was generated, leading to identification of key hub genes using five topological properties. The biological relevance of hub genes was validated via GEPIA, HPA, immune infiltration analysis, and miRNet.
RESULTS: Screening of datasets provided 1764 DEGs. Enrichment analysis revealed dysregulation in immune response, metabolic processes, remodeling of the extracellular matrix, and inflammatory signaling. Five hub genes, EGFR, FN1, IL6, STAT1, and PTPRC, emerged as central regulators with distinct expression-survival profiles and associations with immune infiltration patterns. Notably, STAT1 and IL6 demonstrated context-dependent behavior, reflecting both tumor-intrinsic and microenvironment-derived expression patterns.
CONCLUSION: This study highlights five key genes with potential diagnostic, prognostic, and therapeutic relevance in OSCC, emphasizing their consistency across clinically heterogeneous patient cohorts.
IMPACT: These results extend a mechanistic understanding of OSCC pathobiology, thus promising leads towards the development of clinically robust biomarkers.
METHODS: To resolve this, we employed an integrative bioinformatics approach, analyzing five gene expression datasets retrieved from the GEO repository, which encompass heterogenous clinical samples with diverse clinical stages of OSCC Differentially expressed genes (DEGs) were identified using stringent thresholds (|LogFC|≥ 1.5 to 3.0; p < 0.05), followed by GO and KEGG pathway enrichment analysis. A protein-protein interaction (PPI) connectome was generated, leading to identification of key hub genes using five topological properties. The biological relevance of hub genes was validated via GEPIA, HPA, immune infiltration analysis, and miRNet.
RESULTS: Screening of datasets provided 1764 DEGs. Enrichment analysis revealed dysregulation in immune response, metabolic processes, remodeling of the extracellular matrix, and inflammatory signaling. Five hub genes, EGFR, FN1, IL6, STAT1, and PTPRC, emerged as central regulators with distinct expression-survival profiles and associations with immune infiltration patterns. Notably, STAT1 and IL6 demonstrated context-dependent behavior, reflecting both tumor-intrinsic and microenvironment-derived expression patterns.
CONCLUSION: This study highlights five key genes with potential diagnostic, prognostic, and therapeutic relevance in OSCC, emphasizing their consistency across clinically heterogeneous patient cohorts.
IMPACT: These results extend a mechanistic understanding of OSCC pathobiology, thus promising leads towards the development of clinically robust biomarkers.