Sander Sandrine, Bullinger Lars, Karlsson Asa, Giuriato Sylvie, Hernandez-Boussard Tina, Felsher Dean W, Pollack Jonathan R
Department of Pathology, Stanford University, Stanford, CA 94305-5176, USA.
Oncogene. 2005 Sep 8;24(40):6101-7. doi: 10.1038/sj.onc.1208751.
Microarray-based formats offer a high-resolution alternative to conventional, chromosome-based comparative genomic hybridization (CGH) methods for assessing DNA copy number alteration (CNA) genome-wide in human cancer. For murine tumors, array CGH should provide even greater advantage, since murine chromosomes are more difficult to individually discern. We report here the adaptation and evaluation of a cDNA microarray-based CGH method for the routine characterization of CNAs in murine tumors, using mouse cDNA microarrays representing approximately 14,000 different genes, thereby providing an average mapping resolution of 109 kb. As a first application, we have characterized CNAs in a set of 10 primary and recurrent lymphomas derived from a Myc-induced murine lymphoma model. In primary lymphomas and more commonly in Myc-independent relapses, we identified a recurrent genomic DNA loss at chromosome 3G3-3H4, and recurrent amplifications at chromosome 3F2.1-3G3 and chromosome 15E1/E2-15F3, the boundaries of which we defined with high resolution. Further, by profiling gene expression using the same microarray platform, we identified within CNAs the relevant subset of candidate cancer genes displaying comparably altered expression, including Mcl1 (myeloid cell leukemia sequence 1), a highly expressed antiapoptotic gene residing within the chr 3 amplicon peak. CGH on mouse cDNA microarrays therefore represents a reliable method for the high-resolution characterization of CNAs in murine tumors, and a powerful approach for elucidating the molecular events in tumor development and progression in murine models.
基于微阵列的检测形式为传统的基于染色体的比较基因组杂交（CGH）方法提供了一种高分辨率的替代方法，用于在全基因组范围内评估人类癌症中的DNA拷贝数改变（CNA）。对于鼠类肿瘤，阵列CGH应该具有更大的优势，因为鼠类染色体更难逐个辨别。我们在此报告了一种基于cDNA微阵列的CGH方法的改进和评估，该方法用于鼠类肿瘤中CNA的常规特征分析，使用代表约14,000个不同基因的小鼠cDNA微阵列，从而提供了平均109 kb的定位分辨率。作为首次应用，我们对一组源自Myc诱导的鼠类淋巴瘤模型的10个原发性和复发性淋巴瘤中的CNA进行了特征分析。在原发性淋巴瘤中，更常见于非Myc依赖性复发中，我们在染色体3G3 - 3H4处鉴定出反复出现的基因组DNA缺失，以及在染色体3F2.1 - 3G3和染色体15E1/E2 - 15F3处的反复扩增，我们以高分辨率定义了其边界。此外，通过使用相同的微阵列平台分析基因表达，我们在CNA中鉴定出显示出表达水平相当改变的候选癌症基因的相关子集，包括Mcl1（髓样细胞白血病序列1），这是一个位于chr 3扩增子峰值内的高表达抗凋亡基因。因此，小鼠cDNA微阵列上的CGH代表了一种用于高分辨率表征鼠类肿瘤中CNA的可靠方法，也是阐明鼠类模型中肿瘤发生和进展的分子事件的有力手段。
