Hicks James, Krasnitz Alexander, Lakshmi B, Navin Nicholas E, Riggs Michael, Leibu Evan, Esposito Diane, Alexander Joan, Troge Jen, Grubor Vladimir, Yoon Seungtai, Wigler Michael, Ye Kenny, Børresen-Dale Anne-Lise, Naume Bjørn, Schlicting Ellen, Norton Larry, Hägerström Torsten, Skoog Lambert, Auer Gert, Månér Susanne, Lundin Pär, Zetterberg Anders
Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA.
Genome Res. 2006 Dec;16(12):1465-79. doi: 10.1101/gr.5460106.
Representational Oligonucleotide Microarray Analysis (ROMA) detects genomic amplifications and deletions with boundaries defined at a resolution of approximately 50 kb. We have used this technique to examine 243 breast tumors from two separate studies for which detailed clinical data were available. The very high resolution of this technology has enabled us to identify three characteristic patterns of genomic copy number variation in diploid tumors and to measure correlations with patient survival. One of these patterns is characterized by multiple closely spaced amplicons, or "firestorms," limited to single chromosome arms. These multiple amplifications are highly correlated with aggressive disease and poor survival even when the rest of the genome is relatively quiet. Analysis of a selected subset of clinical material suggests that a simple genomic calculation, based on the number and proximity of genomic alterations, correlates with life-table estimates of the probability of overall survival in patients with primary breast cancer. Based on this sample, we generate the working hypothesis that copy number profiling might provide information useful in making clinical decisions, especially regarding the use or not of systemic therapies (hormonal therapy, chemotherapy), in the management of operable primary breast cancer with ostensibly good prognosis, for example, small, node-negative, hormone-receptor-positive diploid cases.
代表性寡核苷酸微阵列分析(ROMA)可检测基因组的扩增和缺失,其边界分辨率约为50 kb。我们已使用该技术对两项独立研究中的243例乳腺肿瘤进行了检测,这两项研究都有详细的临床数据。这项技术的超高分辨率使我们能够识别二倍体肿瘤中基因组拷贝数变异的三种特征模式,并测量其与患者生存率的相关性。其中一种模式的特征是多个紧密间隔的扩增子,即“火暴区”,局限于单条染色体臂。即使基因组的其他部分相对稳定,这些多个扩增与侵袭性疾病和低生存率也高度相关。对选定临床材料子集的分析表明,基于基因组改变的数量和邻近性进行的简单基因组计算,与原发性乳腺癌患者总生存概率的生命表估计相关。基于该样本,我们提出一个工作假设,即拷贝数分析可能为临床决策提供有用信息,特别是在表面预后良好的可手术原发性乳腺癌(例如小的、无淋巴结转移的、激素受体阳性的二倍体病例)的管理中,关于是否使用全身治疗(激素治疗、化疗)的决策。