期刊论文

Bioinformation analysis of data regarding breast cancer prognosis in European and American populations

中文

癌变·畸变·突变

1004-616X

2018

30

2

103-108

10.3969/j.issn.1004-616x.2018.02.005

2016A030313029:广东省自然科学基金 2017A030313668:广东省自然科学基金 JCYJ20160328161613864:深圳市科技创新项目 JCYJ20150330102720122:深圳市科技创新项目 JSGG20170414104216477:深圳市科技创新项目 GJHZ20160301163138685:国家国际科技合作专项基金

本校为第一机构

目的:通过对肿瘤基因组图谱计划(TCGA)基因表达谱和microRNA测序数据的生物信息学分析,寻找乳腺癌预后相关的关键分子事件。方法:收集并整理TCGA数据库中乳腺癌基因表达谱和microRNA测序数据,通过线性模型和经验贝叶斯方法结合传统t检验筛选乳腺癌中异常表达的基因和microRNA,利用R语言包microRNA-mRNA预测microRNA潜在靶向调控的基因。另外通过基因集富集算法(GAGE)分析预测microRNA及其潜在靶基因在乳腺癌中参与的异常信号调控通路;Cox回归风险模型探讨影响乳腺癌患者预后的关键分子事件。结果:共发现17 533个基因中有344个基因在乳腺癌中异常表达,同时鉴定了135个异常表达的microRNA;通过预测...

OBJECTIVE:To understand key molecular events in prognosis of breast cancer,we analyzed the data published by TCGA,and to study the associations between microRNAs and potential target genes at the pathway level. METHODS:To collect and organize the gene expression profile and microRNA sequencing data of breast cancer in TCGA database,we use multiple t-tests to analyze the differentially expressed microRNAs and target genes,and R language package microRNA-mRNA to predict the potential target regulated genes in microRNA. General Applicable Gene-set Enrichment (GAGE) was applied to discover the key...