功能基因组学方法筛选卵巢癌风险microRNA  

Screening risk microRNAs of ovarian cancer with functional genomics

作　　者：郭秋艳[1] 张广美[1] 

机构地区：[1]哈尔滨医科大学附属第一临床医学院妇产科,黑龙江哈尔滨150001

出　　处：《中国妇幼保健》2012年第21期3315-3317,共3页Maternal and Child Health Care of China

摘　　要：目的:寻找新的卵巢癌发病相关microRNA并为研究人员提供优化后的卵巢癌风险microRNA参照列表。方法:通过在生物网络中度量microRNA靶基因与卵巢癌基因间的功能相似性设计并实现优化卵巢癌风险microRNA计算学方法。采用留一法交叉证实检测该方法的准确性。应用该方法对人类1 527个microRNA进行优化排序。结果:留一法交叉证实所得ROC曲线下面积0.92,该方法有着较高的灵敏度和特异度。排序后,一些已知的卵巢癌相关microRNA如let-7、miR-34/200排在了优化结果的前20位。与新一代测序数据结果进行比较,发现排序前20位microRNA中的大部分都在正常和卵巢癌组织中呈差异表达。结论:应用计算学方法可筛选出卵巢癌相关microRNA,并提供优化后的风险microRNA列表。miR-449a等7个未被报道与卵巢癌有关的miRNA有望成为新的卵巢癌相关的风险因子。Objective： To find new ovarian cancer related microRNAs, provide optimized reference list of ovarian cancer related microRNAs for the researchers. Methods： The optimized computation method of ovarian cancer related microRNAs was designed and realized by measuring the functional similarity of microRNAs target gene and ovarian cancer gene in biological network. Leave - one - out was used to determine the accuracy of the method. The method was used for optimum ranging of 1 527 human microRNAs. Results： Leave - one - out confirmed that the area under ROC curve was 0. 92, the method had high sensitivity and specificity. After sequencing, some known ovarian cancer related microRNAs were ranked in top 20 of the microRNA list, such as let -7 and miR -34/200. Compared with new sequencing data, the most of top 20 microRNAs expressed in normal ovarian tissue and ovarian cancer tissue differentially. Conclusion： Computation method can screen out ovarian cancer related microRNAs and provide optimized reference list of ovarian cancer related microRNAs. Seven unreported ovarian cancer related microRNAs may be new risk factors of ovarian cancer, such as miR -449a.

关 键 词：卵巢癌 MICRORNA 功能基因组 

分 类 号：R737.31[医药卫生—肿瘤]