Tagawa Hiroyuki
Division of Molecular Medicine, Aichi Cancer Center Research Institute.
Gan To Kagaku Ryoho. 2007 Jul;34(7):975-82.
Array-based comparative genomic hybridization (array CGH) enables us to detect the genomic copy number alterations of cancers with high resolution. Our established array CGH platform consists of 2,304 BAC/PAC clones covering the whole genome at 1.3-mega base resolutions. Using this technique, we were thus able to reveal disease-specific genomic alterations and the candidate target genes in various lymphomas. We herein report the characteristic genomic alterations of malignant lymphomas including diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL) and adult T cell lymphoma/leukemia (ATLL). The combined use of the array CGH data with gene expression profiling and specific gene rearrangement analyses further delineated the subtype-specific genomic alterations. For instance, we revealed that activated B-cell-like DLBCL is characterized by a gain of chromosome 3, 18q and loss of 9 p21, whereas the germinal center B-cell-like DLBCL is characterized by a gain of 2p15, 7q, and 12q. Among these genomic alterations,we found the 9 p21 loss (p16INK4a locus) to be the most aggressive type of DLBCL. Comparisons of the genome profiles of FL,both with and without BCL2 rearrangement, also revealed the existence of a unique subgroup: trisomy 3 FL. Comparison of genome profiles between acute type and lymphoma types of adult T cell lymphoma also demonstrated that acute and lymphoma types are genomically distinct subtypes, and thus may develop tumors via distinct genetic pathways. In addition to identifying disease-specific genomic alterations, we also discovered several target genes of the genomic gains and losses. Furthermore,we developed a computer algorithm to classify lymphoma diseases or subtypes on the basis of copy number gains and losses. We applied the algorithm to the classifications of DLBCL and MCL diseases and ABC and GCB subtypes. The method correctly classified the DLBCL and MCL diseases at 89%, and ABC and GCB subtypes at 83%. These results demonstrate that copy number gains and losses detected by array CGH could be used for classifying lymphomas into biologically and clinically distinct diseases or subtypes. The genomic copy number alterations detected by array CGH are therefore considered to have the potential to help diagnose or classify different disease entities and tumor subtypes.
基于芯片的比较基因组杂交技术（芯片比较基因组杂交，array CGH）使我们能够高分辨率地检测癌症的基因组拷贝数改变。我们建立的芯片比较基因组杂交平台由2304个细菌人工染色体/噬菌体P1人工染色体（BAC/PAC）克隆组成，以1.3兆碱基的分辨率覆盖整个基因组。利用这项技术，我们得以揭示各种淋巴瘤中疾病特异性的基因组改变及候选靶基因。我们在此报告恶性淋巴瘤的特征性基因组改变，包括弥漫性大B细胞淋巴瘤（DLBCL）、滤泡性淋巴瘤（FL）和成人T细胞淋巴瘤/白血病（ATLL）。将芯片比较基因组杂交数据与基因表达谱分析及特定基因重排分析相结合，进一步明确了亚型特异性的基因组改变。例如，我们发现活化B细胞样DLBCL的特征是3号染色体、18q增益及9p21缺失，而生发中心B细胞样DLBCL的特征是2p15、7q和12q增益。在这些基因组改变中，我们发现9p21缺失（p16INK4a基因座）是DLBCL中最具侵袭性的类型。对有和无BCL2重排的FL基因组图谱进行比较，也揭示了一个独特亚组的存在：3号染色体三体的FL。对成人T细胞淋巴瘤急性型和淋巴瘤型的基因组图谱进行比较，也表明急性型和淋巴瘤型是基因组上不同的亚型，因此可能通过不同的遗传途径发生肿瘤。除了识别疾病特异性的基因组改变，我们还发现了基因组增益和缺失的几个靶基因。此外，我们开发了一种计算机算法，根据拷贝数的增益和缺失对淋巴瘤疾病或亚型进行分类。我们将该算法应用于DLBCL和套细胞淋巴瘤（MCL）疾病以及ABC和GCB亚型的分类。该方法对DLBCL和MCL疾病的正确分类率为89%，对ABC和GCB亚型的正确分类率为83%。这些结果表明，芯片比较基因组杂交检测到的拷贝数增益和缺失可用于将淋巴瘤分类为生物学和临床上不同的疾病或亚型。因此，芯片比较基因组杂交检测到的基因组拷贝数改变被认为有潜力帮助诊断或分类不同的疾病实体和肿瘤亚型。
