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Are we there yet? Genomic profiling and mechanism in cancer research

机译:我们到了吗?癌症研究中的基因组图谱和机制

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The advent of the human genome sequence and genomic profiling technologies has impacted all of biomedical research. The effect has been particularly great on cancer research because cancer is a disease uniformly characterized by disturbed genome function. Studies which take a whole genome view of cancer are transforming the classification of tumors, enhancing understanding of tumorigenesis and promising to affect patient care. However, the development of large sets of genomic data has challenged cancer biologists who as a rule have never encountered data on this scale. Implementation of conventional statistical techniques has brought a level of order to the biologist's desktop, but significant problems remain to be solved. The challenge remains to extract the maximum useful information from genomic data. This requires both new algorithmic approaches which can accommodate the complexity of the underlying rules of genome function and effective strategies for linking different types of genomic data to each other and to external sources of gene and genome annotation. Progress in this arena will be necessary to fully realize the potential of genomics to impact on our ability to intervene in the clinical arena. Of particular importance will be approaches which help identify critical genes and pathways which are essential to tumor growth and survival. Examples will be presented which illustrate the boundaries of conventional analyses based on studies of tumor profiling at the expression and gene copy number level as well as experimental models designed to explore the function of specific pathways.
机译:人类基因组序列和基因组谱分析技术的出现影响了所有生物医学研究。由于癌症是一种以基因组功能紊乱为特征的疾病,因此对癌症的研究效果尤其显着。从癌症的全基因组角度进行的研究正在改变肿瘤的分类,增强对肿瘤发生的理解,并有望影响患者的护理。但是,大量基因组数据的发展对癌症生物学家提出了挑战,这些生物学家通常从未遇到过这种规模的数据。常规统计技术的实施为生物学家带来了一定程度的秩序,但仍需解决重大问题。从基因组数据中提取最大的有用信息仍然是挑战。这既需要能够适应基因组功能的基本规则的复杂性的新算法方法,又需要将不同类型的基因组数据相互关联以及与基因和基因组注释的外部来源建立联系的有效策略。要充分意识到基因组学对我们干预临床领域的能力产生影响的潜力,必须在这一领域取得进展。特别重要的是可以帮助鉴定对于肿瘤生长和存活必不可少的关键基因和途径的方法。将提供实例说明常规分析的边界,这些实例基于在表达和基因拷贝数水平上的肿瘤概况研究以及旨在探索特定途径功能的实验模型,从而研究了常规的分析方法。

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