首页> 外文会议>4th ACM international workshop on data and text mining in bioinformatics 2010 >Context-specific Gene Regulatory Networks Subdivide Intrinsic Subtypes of Breast Cancer
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Context-specific Gene Regulatory Networks Subdivide Intrinsic Subtypes of Breast Cancer

机译:上下文特定的基因调节网络细分乳腺癌的内在亚型。

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Breast cancer is a highly heterogeneous disease with respect to molecular alterations and cellular composition making therapeutic and clinical outcome unpredictable. This diversity creates a significant challenge in developing tumor classifications that are clinically reliable with respect to prognosis prediction. This paper describes an unsupervised context analysis to infer context-specific gene regulatory networks from 1,614 samples obtained frorh publicly available gene expression data, an extension of previously published method. The main focus of the paper, however, is to use the context-specific gene regulatory networks to classify the tumors into clinically relevant sub-groups and providing candidates for a finer sub-grouping of the previously known intrinsic tumors with focus on basal-like tumors. Further analysis of pathway enrichment of the key contexts provides an understanding of the biological mechanism for identified subtypes of breast cancers.
机译:就分子改变和细胞组成而言,乳腺癌是高度异质性疾病,使得治疗和临床结果不可预测。这种多样性在发展对预后预测而言临床上可靠的肿瘤分类方面提出了重大挑战。本文介绍了一种无监督的语境分析方法,以从可公开获得的基因表达数据中获得的1,614个样本中推断特定于语境的基因调控网络,这是先前发表方法的扩展。然而,本文的主要重点是使用特定于情境的基因调控网络将肿瘤分类为临床上相关的亚组,并为先前已知的内在性肿瘤的更精细亚组提供候选,重点是基底样肿瘤。肿瘤。对关键环境的途径富集的进一步分析提供了对识别出的乳腺癌亚型的生物学机制的理解。

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