基于MetaCoreTM分析维吾尔族宫颈癌患者潜在血浆标志物分析*

  目的   基于维吾尔族宫颈癌蛋白质组学分析数据，借助MetaCoreTM在线生物信息学分析平台构建维吾尔族宫颈癌相关生物信号网络，探讨癌变机理，寻找血浆预警蛋白。   方法   运用MetaCoreTM在线生物信息学软件，针对前期研究中通过蛋白质组学技术筛选分析获得的维吾尔族妇女早期宫颈癌患者血浆中43个核心差异蛋白进行功能注释、细胞内组成以及在机体中所负责的生物学加工进程进行富集分析，并且构建生物信号通路网络、筛选候选生物标志物。   结果  发现宫颈癌患者血浆中的差异蛋白的生物功能主要集中在细胞内构成的负调节、胆固醇反向转运、应激反应的负调节等，涉及的通路主要有脂代谢中的胆汁酸代谢调节和受体依赖的胆汁酸浓缩负调节、炎症补体系统、细胞骨架肌动蛋白纤维、ESR1膜受体转导途径。通过MetaCoreTM最短路径算法分析构建出差异蛋白生物信号网络图，并且筛选出4种候选生物标志性蛋白，分别是抗凝血酶Ⅲ（ATⅢ）、凝集素（CLU）、绒毛蛋白1（VIL1）和免疫球蛋白κ（IGK@）。   结论  ATⅢ、CLU、VIL1、和IGK@可作为宫颈癌的候选标志物蛋白。通过生物信息学MetaCoreTM分析进一步阐述了宫颈癌及癌前病变发生与发展的机理，丰富了宫颈癌早期筛查体系。 

Screening based on MetaCoreTM analysis of potential plasma biomarkers specific for cervical cancer in Uyghur women

  Objective  This study constructs networks and screens potential early-warning plasma biomarkers specific for cervical cancer in Uygur women based on the proteomic data of a previous study by using MetaCoreTM Analysis. This study also explains the canceration mechanism of cervical cancer.   OMethods  A total of 43 plasma differential core proteins, which were analyzed and identified by proteomic techniques, underwent enrichment analysis of protein functional annotation, biological process, cellular component, GeneGo network distribution and network construction, and biomarker assessment by using MetaCoreTM online bioinformatics software.   Results  The result of the MetaCoreTM analysis shows that the negative regulation of cellular component organization, reverse cholesterol transport, and negative regulation of response to stimulus were the most frequently identified functions of the selected differential proteins. The regulation of metabolism, bile acid regulation of lipid metabolism, negative farnesoid X-activated receptor-dependent regulation of bile acid concentration, inflammation complement system, cytoskeleton actin filaments, signal transduction estrogen receptor 1 membrane pathway, and inflammation interleukin-6 signaling were identified as the canonical pathways that are overrepresented in cervical cancer. The MetaCore network of selected proteins, which was constructed using the shortest path algorithm with four plasma proteins (antithrombin Ⅲ (ATⅢ), clusterin (CLU), villin1 (VIL1), and immunoglobulin kappa locus (IGK@)) as candidate biomarkers, was screened.   Conclusion  The proteins ATⅢ, CLU, VIL1, and IGK@ can be considered candidate plasma biomarkers of cervical cancer. The mechanism of occurrence and development of cervical cancer was further explained by MetaCoreTM bioinformatics analysis, thereby enhancing the early-warning system for cervical cancer.