Integrated bioinformatics analysis of common molecular mechanisms and biomarkers in oral squamous cell carcinoma and periodontal disease

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Abstract

Background: Oral Squamous Cell Carcinoma (OSCC) and Periodontal Disease (PD) are two distinct yet interconnected conditions with complex molecular mechanisms. This study aimed to analyze transcriptomic data from both diseases to identify common and unique molecular features, uncover potential biomarkers, and explore therapeutic targets. Method: Transcriptomic data from OSCC and PD were analyzed using WGCNA to construct gene co-expression networks and identify disease-associated modules. Functional enrichment analyses were conducted to reveal shared biological pathways, particularly those related to extracellular matrix organization. Machine learning methods, including Lasso regression, Random Forest, and SVM-RFE, were applied to select key feature genes. The findings were validated using independent datasets. Immune infiltration analysis using CIBERSORT was performed to assess immune cell interactions, while single-cell RNA sequencing was employed to explore the cellular distribution and functional role of the identified biomarker FNDC3B. Result: WGCNA identified key gene modules associated with OSCC and PD, with functional enrichment analyses highlighting shared pathways involved in extracellular matrix organization. Machine learning approaches identified FNDC3B as a central gene in both diseases, and its differential expression was validated in independent datasets. Immune infiltration analysis demonstrated the involvement of FNDC3B in immune cell interactions. Single-cell RNA sequencing further revealed the enrichment of FNDC3B in specific cell types, providing deeper insights into its role in disease progression. Conclusion: This study elucidates the molecular similarities and differences between OSCC and PD, positioning FNDC3B as a critical biomarker for both conditions. The findings enhance our understanding of the shared and distinct mechanisms driving these diseases and provide a foundation for the development of targeted therapeutic strategies.

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Wu, L., She, P., Qiu, C., Sun, H., Kong, F., Wang, H., … Mao, Z. (2025). Integrated bioinformatics analysis of common molecular mechanisms and biomarkers in oral squamous cell carcinoma and periodontal disease. Discover Oncology, 16(1). https://doi.org/10.1007/s12672-025-03728-0

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