Dai Yong, Jiang Jin-Bo, Wang Yan-Lei, Jin Zu-Tao, Hu San-Yuan
Department of General Surgery, Qilu Hospital of Shandong University, Jinan, Shandong 250012, P.R. China.
Mol Med Rep. 2015 Oct;12(4):4947-58. doi: 10.3892/mmr.2015.4102. Epub 2015 Jul 20.
Colorectal cancer (CRC) is a well‑recognized complication of ulcerative colitis (UC), and patients with UC have a higher incidence of CRC, compared with the general population. However, the properties of CRC induced by UC have not been clarified using an interaction network to analyze and compare gene sets. In the present study, six microarray datasets of CRC and UC were extracted from the Array Express database, and gene signatures were identified using the genome‑wide relative significance (GWRS) method. Functional analysis was performed based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Prediction of the genes and microRNA were performed using a hypergeometric method. A protein‑protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/proteins, and clusters were obtained through the Molecular Complex Detection algorithm. Topological centrality and a novel analyzing method, based on the rank value of GWGS, were used to characterize the biological importance of the clusters. A total of 217 differentially expressed (DE) genes of CRC were identified, 341 DE genes were identified in UC, and 62 common genes existed in the two. Several KEGG pathways were the same in CRC and UC. Collagenase, progesterone, heparin, urokinase, nadh and adenosine drugs demonstrated potential for use in treatment of CRC and UC. In the PPI network of CRC, 210 nodes and 752 edges were observed, wheras 314 nodes and 882 edges were identified in UC. Cluster 3 in UC had the highest GWGS, while the topological centrality of Cluster 3 in UC had the lowest degree and betweenness. PPI network analysis provided an effective way to estimate and understand the likelihood of the potential connections between proteins/genes. The results obtained following the use of GWGS to analyze differences between clusters did not agree with the topological degree and betweenness centrality, which indicated that gene fold change based GWGS was controversial with degree here in CRC and UC.
结直肠癌（CRC）是溃疡性结肠炎（UC）一种公认的并发症，与普通人群相比，UC患者患CRC的发生率更高。然而，尚未通过相互作用网络分析和比较基因集来阐明UC诱发的CRC的特性。在本研究中，从Array Express数据库中提取了六个CRC和UC的微阵列数据集，并使用全基因组相对显著性（GWRS）方法鉴定了基因特征。基于京都基因与基因组百科全书（KEGG）数据库进行功能分析。使用超几何方法对基因和微小RNA进行预测。使用检索相互作用基因/蛋白质的搜索工具构建蛋白质-蛋白质相互作用（PPI）网络，并通过分子复合物检测算法获得聚类。基于GWGS的排名值，使用拓扑中心性和一种新的分析方法来表征聚类的生物学重要性。共鉴定出217个CRC差异表达（DE）基因，341个UC中的DE基因，两者中存在62个共同基因。CRC和UC中的几条KEGG途径相同。胶原酶、孕酮、肝素、尿激酶、烟酰胺腺嘌呤二核苷酸（NADH）和腺苷药物显示出用于治疗CRC和UC的潜力。在CRC的PPI网络中，观察到210个节点和752条边，而在UC中鉴定出314个节点和882条边。UC中的聚类3具有最高的GWGS，而UC中聚类3的拓扑中心性的度和介数最低。PPI网络分析提供了一种有效的方法来估计和理解蛋白质/基因之间潜在连接的可能性。使用GWGS分析聚类之间差异后获得的结果与拓扑度和介数中心性不一致，这表明基于基因倍数变化的GWGS在CRC和UC中与度存在争议。
