Wu Erli, Liang Jiahui, Zhao Jingxin, Gu Feihan, Zhang Yuanyuan, Hong Biao, Wang Qingqing, Shao Wei, Sun Xiaoyu
College & Hospital of Stomatology, Key Lab. of Oral Diseases Research of Anhui Province, Anhui Medical University, Hefei, 230032, China.
Department of Breast Surgery, Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, 218 JiXi Avenue, Hefei, 230022, Anhui, People's Republic of China.
Sci Rep. 2025 Apr 2;15(1):11216. doi: 10.1038/s41598-025-95703-6.
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.
研究表明，牙周炎（PD）患者患乳腺癌（BC）的风险增加。然而，确切机制仍有待进一步研究。本研究旨在调查可能与牙周炎和乳腺癌相互作用的基因、信号通路和免疫细胞。我们分别从基因表达综合数据库（GEO）和癌症基因组图谱（TCGA）数据库中检索了牙周炎和乳腺癌样本的基因表达谱。通过差异表达分析和加权基因共表达网络分析（WGCNA）找出两种疾病之间的共同基因。使用机器学习方法寻找共享诊断基因。进行单样本基因集富集分析（ssGSEA）以研究牙周炎和乳腺癌中28种免疫细胞的表达谱，并使用单细胞RNA测序（scRNA-seq）数据来可视化共享基因的定位。最后，我们采用qRT-PCR和免疫组织化学染色来确认两种疾病中关键基因的表达。牙周炎和乳腺癌有21个共享的相互作用基因，主要与肽激素反应、有机酸跨膜转运和羧酸跨膜转运有关。通过机器学习方法，锚蛋白重复结构域29（ANKRD29）和色氨酸2,3-双加氧酶2（TDO2）是最有效的共享诊断生物标志物，免疫组织化学染色和qRT-PCR证实了这一点。ssGSEA表明免疫学参与了这两种疾病，ANKRD29和TDO2可能通过介导免疫细胞参与这两种疾病。scRNA-seq进一步证实了这些基因在调节这两种疾病免疫中的重要性。简而言之，我们的研究确定了2个基因，它们可能作为牙周炎和乳腺癌诊断和治疗的生物标志物和靶点。
