Chin Suet F, Teschendorff Andrew E, Marioni John C, Wang Yanzhong, Barbosa-Morais Nuno L, Thorne Natalie P, Costa Jose L, Pinder Sarah E, van de Wiel Mark A, Green Andrew R, Ellis Ian O, Porter Peggy L, Tavaré Simon, Brenton James D, Ylstra Bauke, Caldas Carlos
Breast Cancer Functional Genomics, Cancer Research UK Cambridge Research Institute and Department of Oncology University of Cambridge, Li Ka-Shing Centre, Robinson Way, Cambridge CB2 0RE, UK.
Genome Biol. 2007;8(10):R215. doi: 10.1186/gb-2007-8-10-r215.
The characterization of copy number alteration patterns in breast cancer requires high-resolution genome-wide profiling of a large panel of tumor specimens. To date, most genome-wide array comparative genomic hybridization studies have used tumor panels of relatively large tumor size and high Nottingham Prognostic Index (NPI) that are not as representative of breast cancer demographics.
We performed an oligo-array-based high-resolution analysis of copy number alterations in 171 primary breast tumors of relatively small size and low NPI, which was therefore more representative of breast cancer demographics. Hierarchical clustering over the common regions of alteration identified a novel subtype of high-grade estrogen receptor (ER)-negative breast cancer, characterized by a low genomic instability index. We were able to validate the existence of this genomic subtype in one external breast cancer cohort. Using matched array expression data we also identified the genomic regions showing the strongest coordinate expression changes ('hotspots'). We show that several of these hotspots are located in the phosphatome, kinome and chromatinome, and harbor members of the 122-breast cancer CAN-list. Furthermore, we identify frequently amplified hotspots on 8q22.3 (EDD1, WDSOF1), 8q24.11-13 (THRAP6, DCC1, SQLE, SPG8) and 11q14.1 (NDUFC2, ALG8, USP35) associated with significantly worse prognosis. Amplification of any of these regions identified 37 samples with significantly worse overall survival (hazard ratio (HR) = 2.3 (1.3-1.4) p = 0.003) and time to distant metastasis (HR = 2.6 (1.4-5.1) p = 0.004) independently of NPI.
We present strong evidence for the existence of a novel subtype of high-grade ER-negative tumors that is characterized by a low genomic instability index. We also provide a genome-wide list of common copy number alteration regions in breast cancer that show strong coordinate aberrant expression, and further identify novel frequently amplified regions that correlate with poor prognosis. Many of the genes associated with these regions represent likely novel oncogenes or tumor suppressors.
乳腺癌中拷贝数改变模式的特征分析需要对大量肿瘤标本进行全基因组高分辨率分析。迄今为止，大多数全基因组阵列比较基因组杂交研究使用的肿瘤样本具有相对较大的肿瘤大小和较高的诺丁汉预后指数（NPI），这些样本并不能很好地代表乳腺癌的人群特征。
我们对171例相对较小肿瘤大小和低NPI的原发性乳腺癌进行了基于寡核苷酸阵列的拷贝数改变高分辨率分析，因此该样本更能代表乳腺癌的人群特征。对常见改变区域进行层次聚类，确定了一种新的高级别雌激素受体（ER）阴性乳腺癌亚型，其特征为基因组不稳定指数较低。我们能够在一个外部乳腺癌队列中验证这种基因组亚型的存在。使用匹配的阵列表达数据，我们还确定了显示最强协同表达变化的基因组区域（“热点”）。我们发现其中几个热点位于磷脂组、激酶组和染色质组中，并包含了乳腺癌CAN列表中的122个成员。此外，我们在8q22.3（EDD1、WDSOF1）、8q24.11 - 13（THRAP6、DCC1、SQLE、SPG8）和11q14.1（NDUFC2、ALG8、USP35）上鉴定出与预后显著较差相关的频繁扩增热点。这些区域中任何一个区域发生扩增都可识别出37个总生存期（风险比（HR）= 2.3（1.3 - 1.4），p = 0.003）和远处转移时间（HR = 2.6（1.4 - 5.1），p = 0.004）显著较差的样本，且与NPI无关。
我们提供了强有力的证据证明存在一种新的高级别ER阴性肿瘤亚型，其特征为基因组不稳定指数较低。我们还提供了一份全基因组范围内乳腺癌常见拷贝数改变区域列表，这些区域显示出强烈的协同异常表达，并进一步鉴定出与预后不良相关的新的频繁扩增区域。与这些区域相关的许多基因可能代表新的癌基因或肿瘤抑制基因。
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