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利用细菌人工染色体阵列和比较基因组杂交技术对癌细胞中的遗传事件进行高分辨率分析。

High-resolution analysis of genetic events in cancer cells using bacterial artificial chromosome arrays and comparative genome hybridization.

作者信息

Cowell John K, Nowak Norma J

机构信息

Roswell Park Cancer Institute, Department of Cancer Genetics, Elm and Carlton Streets, Buffalo, New York 14263, USA.

出版信息

Adv Cancer Res. 2003;90:91-125. doi: 10.1016/s0065-230x(03)90003-0.

Abstract

Chromosome analysis of cancer cells has been one of the primary means of identifying key genetic events in the development of cancer. The relatively low resolution of metaphase chromosomes, however, only allows characterization of major genetic events that are defined at the megabase level. The development of the human genome-wide bacterial artificial chromosome (BAC) libraries that were used as templates for the human genome project made it possible to design microarrays containing these BACs that can theoretically span the genome uninterrupted. Competitive hybridization to these arrays using tumor and normal DNA samples reveals numerical chromosome abnormalities (deletions and amplifications) that can be accurately defined depending on the density of the arrays. At present, we are using arrays with 6,000 BACs, which provide an average resolution of less than 700 kb. Analysis of tumor DNA samples using these arrays reveals small deletions and amplifications that were not detectable by chromosome analysis and provides a global view of these genetic changes in a single hybridization experiment in 24 hours. The extent of the genetic changes can then be determined precisely and the gene content of the affected regions established. These arrays have widespread application to the analysis of cancer patients and their tumors and can detect constitutional abnormalities as well. The availability of these high-density arrays now provides the opportunity to classify tumors based on their genetic fingerprints, which will assist in staging, diagnosis, and even prediction of response to therapy. Importantly, subtle genetic changes that occur consistently in tumor cell types may eventually be used to stratify patients for clinical trials and to predict their response to custom therapies.

摘要

癌细胞的染色体分析一直是识别癌症发展过程中关键遗传事件的主要手段之一。然而,中期染色体相对较低的分辨率仅允许对在兆碱基水平定义的主要遗传事件进行表征。用作人类基因组计划模板的人类全基因组细菌人工染色体(BAC)文库的开发,使得设计包含这些BAC的微阵列成为可能,理论上这些微阵列可以不间断地覆盖整个基因组。使用肿瘤和正常DNA样本与这些阵列进行竞争性杂交,可揭示染色体数目异常(缺失和扩增),这些异常可根据阵列的密度精确界定。目前,我们使用的阵列包含6000个BAC,平均分辨率小于700 kb。使用这些阵列分析肿瘤DNA样本,可揭示染色体分析无法检测到的小缺失和扩增,并在24小时内的单次杂交实验中提供这些遗传变化的全局视图。然后可以精确确定遗传变化的程度,并确定受影响区域的基因组成。这些阵列在癌症患者及其肿瘤的分析中具有广泛应用,也可检测染色体异常。这些高密度阵列的可用性现在提供了根据肿瘤的遗传指纹对肿瘤进行分类的机会,这将有助于分期、诊断,甚至预测对治疗的反应。重要的是,在肿瘤细胞类型中一致出现的细微遗传变化最终可能用于对患者进行分层以进行临床试验,并预测他们对定制疗法的反应。

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