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[基于DNA微阵列技术的差异基因表达分析及其在分子肿瘤学中的应用]

[Differential gene expression analysis by DNA microarrays technology and its application in molecular oncology].

作者信息

Frolov A E, Godwin A K, Favorova O O

机构信息

Department of Molecular Biology and Medical Biotechnology, Russian State Medical University, Moscow, 117437, Russia.

出版信息

Mol Biol (Mosk). 2003 Jul-Aug;37(4):573-84.

Abstract

Accumulation of genetic and epigenetic aberrations leads to malignant transformation of normal cells. Functional studies of cancer using genomic and proteomic tools will help to reveal the true complexity of the processes leading to cancer development in humans. Until recently, diagnosis and prognosis of cancer was based on conventional pathologic criteria and epidemiological evidence. Certain tumors were divided only into relatively broad histological and morphological subcategories. Rapidly developing methods of differential gene expression analysis promote the search for clinically relevant genes changing their expression levels during malignant transformation. DNA microarrays offer a unique possibility to rapidly assess the global expression picture of thousands genes in any given time point and compare the detailed combinatory analysis results of global expression profiles for normal and malignant cells at various functional stages or separate experimental conditions. Acquisition of such "genetic portraits" allows searching for regularity and difference in expression patterns of certain genes, understanding their function and pathological importance, and ultimately developing the "molecular nosology" of cancer. This review describes the basis of DNA microarray technology and methodology, and focuses on their applications in molecular classification of tumors, drug sensitivity and resistance studies, and identification of biological markers of cancer.

摘要

遗传和表观遗传异常的积累导致正常细胞发生恶性转化。利用基因组和蛋白质组学工具对癌症进行功能研究,将有助于揭示导致人类癌症发生过程的真正复杂性。直到最近,癌症的诊断和预后仍基于传统的病理标准和流行病学证据。某些肿瘤仅被分为相对宽泛的组织学和形态学亚类。快速发展的差异基因表达分析方法促进了对在恶性转化过程中表达水平发生变化的临床相关基因的寻找。DNA微阵列提供了一种独特的可能性,能够在任何给定时间点快速评估数千个基因的整体表达情况,并比较正常细胞和处于不同功能阶段或不同实验条件下的恶性细胞的整体表达谱的详细组合分析结果。获取此类“基因图谱”有助于寻找某些基因表达模式的规律和差异,理解其功能和病理重要性,并最终建立癌症的“分子分类学”。本综述描述了DNA微阵列技术和方法的基础,并重点介绍了它们在肿瘤分子分类、药物敏感性和耐药性研究以及癌症生物标志物鉴定中的应用。

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