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首页> 外文期刊>Acta Biotheoretica >Beyond the Oncogene Paradigm: Understanding Complexity in Cancerogenesis
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Beyond the Oncogene Paradigm: Understanding Complexity in Cancerogenesis

机译:超越癌基因范式:了解癌症发生的复杂性

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In the past decades, an enormous amount of precious information has been collected about molecular and genetic characteristics of cancer. This knowledge is mainly based on a reductionistic approach, meanwhile cancer is widely recognized to be a ‘system biology disease’. The behavior of complex physiological processes cannot be understood simply by knowing how the parts work in isolation. There is not solely a matter how to integrate all available knowledge in such a way that we can still deal with complexity, but we must be aware that a deeply transformation of the currently accepted oncologic paradigm is urgently needed. We have to think in terms of biological networks: understanding of complex functions may in fact be impossible without taking into consideration influences (rules and constraints) outside of the genome. Systems Biology involves connecting experimental unsupervised multivariate data to mathematical and computational approach than can simulate biologic systems for hypothesis testing or that can account for what it is not known from high-throughput data sets. Metabolomics could establish the requested link between genotype and phenotype, providing informations that ensure an integrated understanding of pathogenic mechanisms and metabolic phenotypes and provide a screening tool for new targeted drug.
机译:在过去的几十年中,已经收集了大量有关癌症分子和遗传特征的宝贵信息。这些知识主要基于还原论方法,与此同时,癌症被广泛认为是“系统生物学疾病”。仅仅通过了解各个部分如何独立工作就无法理解复杂的生理过程的行为。如何以仍然可以处理复杂性的方式整合所有可用知识,不仅是一个问题,而且我们必须意识到,迫切需要对当前公认的肿瘤学范式进行深刻变革。我们必须从生物网络的角度进行思考:如果不考虑基因组外部的影响(规则和约束),实际上了解复杂功能可能是不可能的。系统生物学涉及将实验无监督的多元数据连接到数学和计算方法,而不是可以模拟用于假设检验的生物系统,或者可以解释高通量数据集中未知的数据。代谢组学可以建立所需的基因型和表型之间的联系,提供确保对致病机制和代谢表型有综合理解的信息,并为新的靶向药物提供筛选工具。

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