Identification of potential shared gene signatures between periodontitis and breast cancer by integrating bulk RNA-seq and scRNA-seq data

Studies have shown that patients with periodontitis (PD) have an increased risk of breast cancer (BC). However, the exact mechanism remains to be further investigated. This study aimed to investigate the genes, pathways and immune cells that may interact with PD and BC. From the Gene Expression Omnibus (GEO) and TCGA databases, we retrieved the gene expression profiles of samples with PD and BC, respectively. Common genes between two diseases were found using differential expression analysis and weighted gene co-expression network analysis (WGCNA). Machine learning methods were used to find shared diagnostic genes. Single-sample GSEA (ssGSEA) was performed to study the expression profiles of 28 immune cells in PD and BC, and single-cell RNA sequencing (scRNA-seq) data was used to visualize localization of shared genes. Finally, we employed qRT-PCR and immunohistochemistry staining to confirm the expression of hub genes in two diseases. PD and BC had 21 shared crosstalk genes, which were primarily related to peptide hormone response, organic acid transmembrane transport, and carboxylic acid transmembrane transport. By using machine learning methods, ANKRD29 and TDO2 were the most efficient shared diagnostic biomarkers, which were confirmed by Immunohistochemical staining and qRT-PCR. ssGSEA showed that immunology was involved in both diseases and that ANKRD29 and TDO2 may be involved in both diseases by mediating immune cells. scRNA-seq further confirms the importance of these genes in regulating immunity in both diseases. In brief, our study identified 2 genes that may serve as biomarkers and targets for the diagnosis and treatment of PD and BC.