乳腺癌-冠心病共享生物标志物筛选

运用生物信息学方法筛选乳腺癌-冠心病标志物,为乳腺癌诱发的冠心病治疗提供潜在的作用靶点.从基因表达数据库(gene expression omnibus,GEO)中下载乳腺癌和冠心病相关表达谱芯片数据,使用GEO2R筛选差异表达基因,依据Venn图交集获取差异共表达基因,通过DAVID网站进行基因功能注释(gene ontology,GO)及京都基因与基因组百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)生物功能富集分析,STRING网站和Cytoscape 3.7.2软件进行蛋白互作分析.GE-PIA和Kaplan-Meier Plotter进行对乳腺癌患者hub基因mRNA表达水平和预后分析.结果表明:2个数据集筛选得到差异表达基因286个,基于在乳腺癌中mRNA显著性表达水平筛选出45个基因.GO功能富集分析发现差异表达基因主要在泛素蛋白转移酶活性、糖蛋白结合、泛素蛋白连接酶结合等生物学过程发挥作用.KEGG分析显示差异基因主要参与缝隙连接、肾素分泌、5-羟色胺能突触、谷氨酸能突触、血管平滑肌收缩、血小板活化、癌细胞蛋白多糖等多条信号通路.基因mRNA表达水平和预后分析显示NLN、POSTN、MAPT、MYO6、MAP1B、FBXO31、KIT、PIK3R1等8个与冠心病相关的hub基因参与乳腺癌的发生、发展过程.NLN、POSTN、MAPT、MYO6、MAP1B、FBXO31、KIT、PIK3R1可作为检测乳腺癌诱导冠心病的潜在标志物.

Screening and Identification of Common Biomarkers of Breast Cancer and Coronary Heart Disease

Screening biomarkers of breast cancer and coronary heart disease (CHD) by bioinformatics methods, and to provide potential targets for the treatment of coronary heart disease induced by breast cancer. The microarray data related to breast cancer and coronary heart disease were downloaded from geo database. The differentially expressed genes were selected by geo2r, and the differentially co expressed genes were obtained according to the intersection of Venn map. Biological function enrichment of GO and KEGG was analyzed by David website, and protein interaction was analyzed by string website and Cytoscape 3.7.2 software. Kaplan Meier plotter and GEPIA were used to analyze the prognosis and verify the gene expression. The results show that: 286 differentially expressed genes were screened from the two data sets, and 45 genes were screened based on the significant mRNA expression level in breast cancer. GO functional enrichment analysis showed that the differentially expressed genes were mainly involved in ubiquitous protein transferase activity, glycoprotein binding, ubiquity protein ligase binding and other biological processes. KEGG analysis showed that the differentially expressed genes were mainly involved in many signaling pathways, such as gap junction, renin secretion, 5-hydroxytryptaminergic synapses, glutamatergic synapses, vascular smooth muscle contraction, platelet activation, and cancer cell proteoglycan. The mRNA expression level and prognosis analysis showed that NLN, POSTN, MAPT, MYO6, MAP1B, FBXO31, KIT and PIK3R1 were involved in the occurrence and development of breast cancer. Conclusion: NLN, POSTN, MAPT, MYO6, MAP1B, FBXO31, KIT, PIK3R1 can be used as potential markers for detecting breast cancer induced coronary heart disease.