Corver Willem E, Middeldorp Anneke, ter Haar Natalja T, Jordanova Ekaterina S, van Puijenbroek Marjo, van Eijk Ronald, Cornelisse Cees J, Fleuren Gert Jan, Morreau Hans, Oosting Jan, van Wezel Tom
Department of Pathology, Leiden University Medical Center, Leiden, the Netherlands.
Cancer Res. 2008 Dec 15;68(24):10333-40. doi: 10.1158/0008-5472.CAN-08-2665.
Chromosomal aberrations are a common characteristic of cancer and are associated with copy number abnormalities and loss of heterozygosity (LOH). Tumor heterogeneity, low tumor cell percentage, and lack of knowledge of the DNA content impair the identification of these alterations especially in aneuploid tumors. To accurately detect allelic changes in carcinomas, we combined flow-sorting and single nucleotide polymorphism arrays. Cells derived from archival cervical and colon cancers were flow-sorted based on differential vimentin and keratin expression and DNA content and analyzed on single nucleotide polymorphism arrays. A new algorithm, the lesser allele intensity ratio, was used to generate a molecular measure of chromosomal aberrations for each case. Flow-sorting significantly improved the detection of copy number abnormalities; 31.8% showed an increase in amplitude and 23.2% were missed in the unsorted fraction, whereas 15.9% were detected but interpreted differently. Integration of the DNA index in the analysis enabled the identification of the allelic state of chromosomal aberrations, such as LOH ([A]), copy-neutral LOH ([AA]), balanced amplifications ([AABB]), and allelic imbalances ([AAB] or [AAAB], etc.). Chromosomal segments were sharply defined. Fluorescence in situ hybridization copy numbers, as well as the high similarity between the DNA index and the allelic state index, which is the average of the allelic states across the genome, validated the method. This new approach provides an individual molecular measure of chromosomal aberrations and will likely have repercussions for preoperative molecular staging, classification, and prognostic profiling of tumors, particularly for heterogeneous aneuploid tumors, and allows the study of the underlying molecular genetic mechanisms and clonal evolution of tumor subpopulations.
染色体畸变是癌症的一个常见特征，与拷贝数异常和杂合性缺失（LOH）相关。肿瘤异质性、低肿瘤细胞百分比以及对DNA含量的了解不足，尤其是在非整倍体肿瘤中，会妨碍对这些改变的识别。为了准确检测癌组织中的等位基因变化，我们将流式分选与单核苷酸多态性阵列相结合。从存档的宫颈癌和结肠癌中获取的细胞，根据波形蛋白和角蛋白表达差异、DNA含量进行流式分选，并在单核苷酸多态性阵列上进行分析。一种新的算法——较小等位基因强度比，用于为每个病例生成染色体畸变的分子测量值。流式分选显著提高了拷贝数异常的检测率；在未分选的部分中，31.8%的异常幅度增加，23.2%的异常被遗漏，而15.9%的异常虽被检测到但解读不同。在分析中整合DNA指数能够识别染色体畸变的等位基因状态，如杂合性缺失（[A]）、拷贝中性杂合性缺失（[AA]）、平衡扩增（[AABB]）以及等位基因失衡（[AAB]或[AAAB]等）。染色体片段得到了清晰界定。荧光原位杂交拷贝数，以及DNA指数与等位基因状态指数（即全基因组等位基因状态的平均值）之间的高度相似性，验证了该方法。这种新方法提供了一种个体的染色体畸变分子测量方法，可能会对肿瘤的术前分子分期、分类和预后分析产生影响，特别是对于异质性非整倍体肿瘤，并允许研究肿瘤亚群的潜在分子遗传机制和克隆进化。
