OralDB: A Transcriptomic Resource for Mechanistic Exploration in Oral Diseases

Abstract

Oral diseases, including oral cancer, periodontitis, and oral mucosal disorders, pose major global public health challenges and are driven by complex molecular mechanisms. While recent advances in single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) have unraveled the heterogeneity of these diseases, integrative analyses remain hindered by severe batch effects, inconsistent metadata annotations, and the fragmentation of public datasets. To address these challenges, we present OralDB (https://compbio.cn/oraldb/), the first comprehensive, standardized, and interactive multimodal transcriptomic resource dedicated to oral diseases. OralDB integrates 73 high-quality datasets spanning 20 oral diseases and 4 omics types (microarray, RNA-seq, scRNA-seq, ST), covering 2,027 tissue-based samples. The platform applies rigorous processing pipelines, including quality control, dimensionality reduction, clustering, and cell-type annotation, and provides interactive analytical modules for gene expression visualization, differential expression, pathway enrichment, gene correlation, and cell–cell interaction analysis. OralDB enables efficient exploration of molecular and cellular features across disease contexts. We demonstrate the platform’s utility through case studies of SERPINE2-driven epithelial–mesenchymal transition in oral squamous cell carcinoma and fibroblast-derived CXCL1-mediated myeloid cell recruitment in periodontitis. By facilitating mechanistic insights and supporting translational applications, OralDB offers a robust resource to advance precision research and therapeutic development in oral diseases.