Integrated transcriptomic and immunohistochemical profiling of inflammatory biomarkers for early prediction of oral epithelial dysplasia progression

Abstract

Oral epithelial dysplasia represents a clinically important precursor to oral squamous cell carcinoma, yet conventional histopathological grading alone cannot reliably identify lesions that will progress. This comprehensive review examines the value of integrating transcriptomic and immunohistochemical profiling of inflammatory biomarkers for earlier and more accurate risk prediction. Evidence was synthesized across studies addressing molecular progression, cytokine and chemokine signaling, immune-cell infiltration, immune-checkpoint activity, epithelial stress responses, stemness, stromal remodeling, metabolic adaptation, and epithelial–mesenchymal transition. Transcriptomic approaches reveal dysregulated gene-expression programs linked to inflammation, proliferation, immune suppression, and malignant transformation, while immunohistochemistry confirms protein expression and preserves spatial relationships within epithelial and stromal compartments. Biomarkers involving p53, Ki-67, p16, hypoxia-inducible factor 1 alpha, heat-shock proteins, programmed death ligand 1, E-cadherin, vimentin, survivin, podoplanin, and cancer stem-cell markers show potential for distinguishing biologically active dysplasia from more stable lesions. No single marker currently provides sufficient predictive accuracy for routine clinical use. Multimarker models combining molecular signatures with histological grade, lesion phenotype, anatomical site, and patient-related factors appear more clinically relevant. Standardized protocols, prospective multicentre cohorts, longitudinal validation, spatial transcriptomics, multiplex immunohistochemistry, and digital pathology are needed to translate integrated biomarker profiling into personalized surveillance, targeted biopsy, and earlier intervention. Such integration may reduce delayed diagnosis, unnecessary treatment, and uncertainty in clinical decision making.