Unité Mixte de Génomique du Cancer, Hôpital Laënnec/Institut de Cancérologie de l'Ouest - site René Gauducheau, Bd J. Monod, 44805 Nantes - Saint Herblain Cedex, France.
Database (Oxford). 2013 Jan 15;2013:bas060. doi: 10.1093/database/bas060. Print 2013.
We recently developed a user-friendly web-based application called bc-GenExMiner (http://bcgenex.centregauducheau.fr), which offered the possibility to evaluate prognostic informativity of genes in breast cancer by means of a 'prognostic module'. In this study, we develop a new module called 'correlation module', which includes three kinds of gene expression correlation analyses. The first one computes correlation coefficient between 2 or more (up to 10) chosen genes. The second one produces two lists of genes that are most correlated (positively and negatively) to a 'tested' gene. A gene ontology (GO) mining function is also proposed to explore GO 'biological process', 'molecular function' and 'cellular component' terms enrichment for the output lists of most correlated genes. The third one explores gene expression correlation between the 15 telomeric and 15 centromeric genes surrounding a 'tested' gene. These correlation analyses can be performed in different groups of patients: all patients (without any subtyping), in molecular subtypes (basal-like, HER2+, luminal A and luminal B) and according to oestrogen receptor status. Validation tests based on published data showed that these automatized analyses lead to results consistent with studies' conclusions. In brief, this new module has been developed to help basic researchers explore molecular mechanisms of breast cancer. DATABASE URL: http://bcgenex.centregauducheau.fr
我们最近开发了一个名为 bc-GenExMiner(http://bcgenex.centregauducheau.fr)的用户友好型网络应用程序,它提供了通过“预后模块”评估乳腺癌中基因预后信息量的可能性。在这项研究中,我们开发了一个名为“相关性模块”的新模块,其中包括三种基因表达相关性分析。第一种分析计算 2 个或更多(最多 10 个)选定基因之间的相关系数。第二种分析产生与“测试”基因最相关(正相关和负相关)的两个基因列表。还提出了一个基因本体(GO)挖掘功能,以探索输出最相关基因列表的 GO“生物过程”、“分子功能”和“细胞成分”术语的富集。第三种分析探索了“测试”基因周围的 15 个端粒和 15 个着丝粒基因之间的基因表达相关性。这些相关性分析可以在不同的患者群体中进行:所有患者(不分亚型)、分子亚型(基底样、HER2+、luminal A 和 luminal B)以及根据雌激素受体状态。基于已发表数据的验证测试表明,这些自动化分析得出的结果与研究结论一致。简而言之,这个新模块的开发是为了帮助基础研究人员探索乳腺癌的分子机制。数据库 URL:http://bcgenex.centregauducheau.fr