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通过比较基因组杂交对乳腺癌进行分子分类:BRCA1肿瘤的特定体细胞遗传图谱。

Molecular classification of breast carcinomas by comparative genomic hybridization: a specific somatic genetic profile for BRCA1 tumors.

作者信息

Wessels Lodewyk F A, van Welsem Tibor, Hart Augustinus A M, van't Veer Laura J, Reinders Marcel J T, Nederlof Petra M

机构信息

Information and Communication Theory Group, Faculty of Information Technology and Systems, Delft University of Technology.

出版信息

Cancer Res. 2002 Dec 1;62(23):7110-7.

Abstract

In approximately 70% of the families with a high frequency of early-onset breast and/or ovarian cancer, BRCA1 or BRCA2 germline mutations cannot be identified with the current screening regime. Therefore, we used data mining to identify a somatic genetic signature to differentiate BRCA1 mutation carriers from non-BRCA1 carriers based on the genetic characteristics of their breast carcinomas. For this purpose, we developed a molecular classifier, which assigns a given tumor to either the BRCA1 or control group based on somatic genetic profiles as revealed by comparative genomic hybridization. This was performed on breast tumors selected from two groups of patients: 28 proven BRCA1 germline mutation carriers; and a control group consisting of 42 breast tumors from patients with unknown BRCA1 or BRCA2 status. We show that BRCA1 breast carcinomas exhibit specific somatic genetic aberrations and can be distinguished from control tumors with an accuracy of 84% (sensitivity of 96% and specificity of 76%). Chromosomal bands used by this classifier include regions on chromosomes 3p, 3q, and 5q. The classifier miss-assigned one patient with a BRCA1 mutation to the non-BRCA1 class. The germline mutation in this patient is a 62bp deletion in the last exon of BRCA1 (5622del62). Possibly, this mutation may give a different phenotypic effect than do mutations in other regions of the gene. Validation on an independent set of BRCA1 and sporadic tumors showed that the BRCA1 classifier correctly identified all 6 BRCA1 tumors and assigned 4 of the 19 control patients to the BRCA1 class. The resulting accuracy on the validation set is 84%.

摘要

在大约70%早发性乳腺癌和/或卵巢癌高发的家族中,采用当前的筛查方案无法鉴定出BRCA1或BRCA2种系突变。因此,我们利用数据挖掘技术,根据乳腺癌的遗传特征,识别出一种体细胞遗传特征,以区分BRCA1突变携带者和非BRCA1携带者。为此,我们开发了一种分子分类器,根据比较基因组杂交所揭示的体细胞遗传图谱,将给定的肿瘤归为BRCA1组或对照组。这一操作是在选自两组患者的乳腺肿瘤上进行的:28名经证实的BRCA1种系突变携带者;以及一个由42例BRCA1或BRCA2状态未知患者的乳腺肿瘤组成的对照组。我们发现,BRCA1乳腺癌表现出特定的体细胞遗传畸变,与对照肿瘤的区分准确率为84%(敏感性为96%,特异性为76%)。该分类器所使用的染色体带包括3号染色体短臂、3号染色体长臂和5号染色体长臂上的区域。该分类器将一名携带BRCA1突变的患者误分到了非BRCA1组。该患者的种系突变是BRCA1最后一个外显子中的62bp缺失(5622del62)。可能这种突变产生的表型效应与该基因其他区域的突变不同。在一组独立的BRCA1肿瘤和散发性肿瘤上进行验证表明,BRCA1分类器正确识别了所有6例BRCA1肿瘤,并将19例对照患者中的4例归为BRCA1组。验证集的最终准确率为84%。

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