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Can Systems Biology Understand Pathway Activation? Gene Expression Signatures as Surrogate Markers for Understanding the Complexity of Pathway Activation

机译:系统生物学可以理解通路激活吗?基因表达签名作为替代标记用于理解通路激活的复杂性

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摘要

Cancer is thought to be caused by a sequence of multiple genetic and epigenetic alterations which occur in one or more of the genes controlling cell cycle progression and signaling transduction. The complexity of carcinogenic mechanisms leads to heterogeneity in molecular phenotype, pathology, and prognosis of cancers.Genome-wide mutational analysis of cancer genes in individual tumors is the most direct way to elucidate the complex process of disease progression, although such high-throughput sequencing technologies are not yet fully developed. As a surrogate marker for pathway activation analysis, expression profiling using microarrays has been successfully applied for the classification of tumor types, stages of tumor progression, or in some cases, prediction of clinical outcomes. However, the biological implication of those gene expression signatures is often unclear. Systems biological approaches leverage the signature genes as a representation of changes in signaling pathways, instead of interpreting the relevance between each gene and phenotype. This approach, which can be achieved by comparing the gene set or the expression profile with those of reference experiments in which a defined pathway is modulated, will improve our understanding of cancer classification, clinical outcome, and carcinogenesis. In this review, we will discuss recent studies on the development of expression signatures to monitor signaling pathway activities and how these signatures can be used to improve the identification of responders to anticancer drugs.
机译:人们认为癌症是由一系列遗传和表观遗传学改变引起的,这些改变发生在控制细胞周期进程和信号转导的一个或多个基因中。致癌机制的复杂性导致癌症的分子表型,病理学和预后异质性。尽管如此高通量的测序,但对单个肿瘤中的癌症基因进行全基因组突变分析是阐明疾病进展复杂过程的最直接方法。技术尚未完全开发。作为通路激活分析的替代标记,使用微阵列的表达谱分析已成功地应用于肿瘤类型的分类,肿瘤进展的阶段或在某些情况下的临床结果预测。但是,这些基因表达特征的生物学含义常常不清楚。系统生物学方法利用签名基因作为信号传导途径变化的代表,而不是解释每个基因与表型之间的相关性。这种方法可以通过将基因集或表达谱与调节了确定途径的参考实验的基因集或表达谱进行比较来实现,将改善我们对癌症分类,临床结果和致癌作用的理解。在这篇综述中,我们将讨论有关表达特征的发展以监测信号通路活性的最新研究,以及如何利用这些特征改善对抗癌药物反应者的识别。

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