Identification of Biomarkers Associated with Cancerous Change in Oral Leukoplakia Based on Integrated Transcriptome Analysis

Abstract

Objective. Oral leukoplakia (OLK) is the most common precancerous lesion in the oral cavity. This study aimed to explore key biomarkers for monitoring OLK for early diagnosis of oral squamous cell carcinoma (OSCC) and screen small-molecule drugs for the prevention of OSCC. Method. The Gene Expression Omnibus (GEO) database was explored to extract two microarray datasets, namely, GSE85195 and GSE25099. The data of the normal group, OLK group, and OSCC group were analyzed by weighted gene coexpression network analysis (WGCNA) to identify the most significant gene module and differentially expressed genes (DEGs). The intersection genes were extracted as the key genes of OLK carcinogenesis. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed in the module. Connectivity Map and molecular docking were used to screen small-molecule drugs. The diagnostic values of four key genes were identified and verified in the GSE26549 dataset. Results. WGCNA obtained the red module (r = −0.91, p < 0.05 ) with the strongest correlation with cancerous phenotype. GO enrichment analysis showed 60 pathways, including 28 biological processes, 11 cell components, and 21 molecular functions, and KEGG enrichment analysis showed 4 pathways ( p < 0.05 ). In the differential expression analysis, there was no intersection between the upregulated genes and the red module genes. However, the intersection of the downregulated genes and the red module genes yielded 4 key genes: dopachrome tautomerase (DCT), keratin 3 (KRT3), keratin 76 (KRT76), and FAM3 metabolic regulation signal molecule B (FAM3B). The area under the curve of the diagnostic model constructed by these four genes was 0.963 (CI = 0.913–1.000). The sensitivity was 0.933, and the specificity was 0.923. The diagnostic model was successfully verified in GSE26549 (AUC = 0.745, CI = 0.638–0.851). Compared with the diagnostic models of the previous studies, the diagnostic efficiency of this model was the highest. The small-molecule drugs, selumetinib and benidipine, were selected according to the gene expression profile and showed binding activity when docking with the above molecules. Conclusions. This study provides new targets and drugs for OLK. These targets could be used as the key diagnostic molecules for long-term follow-up of OLK. The small-molecule drugs selumetinib and benidipine could be used for the prevention and treatment of OSCC.

Multi-Omics Data Integration Reveals Key Variables Contributing to Subgingival Microbiome Dysbiosis-Induced Inflammatory Response in a Hyperglycemic Microenvironment

“…Though the impacts of hyperglycemia on individuals' pro-inflammatory cytokine and MMP secretions have been reported [12,14,22,23], our multi-omics integration model highlighted new relationships between genes, pro-inflammatory cytokines and bacteria genera implicated in periodontitis-induced inflammatory response in a hyperglycemic microenvironment. Highlighted genes have been associated with DNA damage response (znf506) [24], cancer (pnma5) [25] and oral cancer (krt76, rab41) [26][27][28]. We have also identified tm6sf2, which is associated with both the risk and the severity of nonalcoholic fatty liver disease [29] as well as with the regulation of inflammatory responses in atherosclerotic lesions [30].…”

Oral cancers preceded by proliferative verrucous leukoplakia exhibit distinctive molecular features

“…Similarly, associations between NKX2‐3 and prognosis have been reported (Zhu et al, 2020) and Abe et al (2016) described that oral leucoplakias are associated with aberrant promoter methylation of NKX2‐3 . Importantly, KRT3 was also selected as a potential diagnostic biomarker associated with a cancerous change in oral leukoplakia (Li et al, 2022). Lin et al (2016) reported that BARX2 expression is mostly downregulated in OSCC and that its expression suppresses the expansion of OSCC cells.…”

Evolutionary Relationships Between Dysregulated Genes in Oral Squamous Cell Carcinoma and Oral Microbiota

“…The CYP3A4 gene encodes a member of the cytochrome P450 superfamily of enzymes and is involved in the metabolism of sterols, steroid hormones, retinoids, and fatty acids ( Chen et al., 2000 ; Marill et al., 2000 ; Badawi et al., 2001 ). Cytoscape software by the Matthews correlation coefficient (MCC) algorithm was used to predict CYP3A4 at the core position in the network and highlight the first 10 types of OSCC DEGs ( Li et al., 2022 ). It is worth noting that there found 350 homologous proteins including 45 microbes were found by evolutionary analysis in this study.…”