Abstract
Background: Lung adenocarcinoma (LUAD) represents a significant global health issue. Smoking contributes to the development of periodontitis and LUAD. The connections between the two are still ambiguous.
Methods: Based on RNA expression data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, differentially expressed genes (DEGs) in Periodontitis and LUAD were collected. Protein-protein interaction (PPI) networks were produced by mining genes intersecting with crossover DEGs. Genes in the subnetwork and the top 15 genes of the topology score were defined as the crosstalk gene. Feature selection and diagnostic model construction were conducted based on Recursive Feature Elimination (RFE) and support vector machines (SVM). additionally, we analyzed the immune cells and signaling pathways influenced by the crosstalk gene.
Results: A total of 29 crossover DEGs between Periodontitis and LUAD were filtered, with 20 genes interacting with them in the PPI network. Five subnetworks with similar interaction patterns in the PPI network were detected. Based on the network topology analysis, genes ranking in the top 15 were used to take the intersection with those genes in the 5 subnetworks. Twelve intersecting genes were identified. Based on RFE and SVM algorithms, FKBP11 and MMP13 were considered as the Crosstalk genes for both Periodontitis and LUAD. The diagnostic model composed of FKBP11 and MMP13 showed excellent diagnostic potential. In addition, we found that FKBP11 and MMP13 influenced Macrophages, M1, T cells, CD8 activity, immune-related pathways, and cell cycle pathways.
Conclusion: We identified the crosstalk genes (FKBP11 and MMP13) between periodontitis and LUAD. The two genes affected the comorbidity status between the two diseases through immune cell activity.