Transcriptomic landscape of oral potentially malignant disorders: a meta-analysis approach.
Early detection of potentially malignant and malignant lesions in the oral cavity is mandatory for reduction in oral cancer incidence, detection at an early stage and improving survival. The objective of this study was to catalogue the transcriptomic pattern across pre-cancerous stages, identify the major signalling processes, and infiltrating immune cell subtypes using the integrated, multi-dataset, meta-analysis approach. Following a search in the public databases, a total of five datasets were included in the study. The patient samples were stratified to identify the changes in high-grade dysplasia (HGD, moderate/severe dysplasia) as opposed to low-risk lesions (LRL, benign/OPMD) and low-grade dysplasia (LGD). Weighted gene co-expression network analysis (WGCNA; p < 0.05, |Correlation coefficient|:0.3) integrated with differential gene expression (DEG; p < 0.05, Fold change: 1.5) analysis revealed alterations in low-to-high-risk lesions included changes in DNA replication, loss of cell adhesions converging on a hub panel of tumor promoter/suppressors. The shift to high grade dysplasia was marked by enhanced immune/cytokine signalling with hub-gene network driving metabolic regulation, immune evasion, and ECM-stroma interaction. In transformed lesions, the immune-modulatory environment persisted, now accompanied by a notable downregulation of interferon (IFN) signalling. Interferon-inducible network and stemness induction were key hub gene networks. Digital cytometric analysis indicated specific enrichment of T regulatory cells and dendritic cells in differentiating the grades of dysplasia, while T helper cells were specific for malignant transformation. Collectively, these results indicate the role of immune surveillance during oral carcinogenesis. The distinct molecular/immunological shifts during dysplastic progression and malignant transformation represent critical milestones in oral potentially malignant disorder (OPMD) progression, offering actionable insights for prognosis, prevention, and therapeutic intervention.
Authors
Vasudevan Vasudevan, Siddappa Siddappa, Sam Sam, Madhumathi Madhumathi, Thomas Thomas, Sunny Sunny, Shetty Shetty, Bhushan Bhushan, Dokhe Dokhe, Pillai Pillai, Birur Birur, Kuriakose Kuriakose, Suresh Suresh
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