使用高密度 SNP 阵列对原发性乳腺癌进行拷贝数和杂合性丢失的综合分析。

Integrated analysis of copy number and loss of heterozygosity in primary breast carcinomas using high-density SNP array.

机构信息

Department of Pathology, Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Malaysia.

出版信息

Int J Oncol. 2011 Sep;39(3):621-33. doi: 10.3892/ijo.2011.1081. Epub 2011 Jun 15.

Abstract

Breast cancer is a heterogeneous disease, marked by extensive chromosomal aberrations. In this study, we aimed to explicate the underlying chromosomal copy number (CN) alterations and loss of heterozygosity (LOH) implicated in a cohort of Malaysian hospital-based primary breast carcinoma samples using a single nucleotide polymorphism (SNP) array platform. The analysis was conducted by hybridizing the extracted DNA of 70 primary breast carcinomas and 37 normal peripheral blood samples to the Affymetrix 250K Sty SNP arrays. Locus-specific CN aberrations and LOH were statistically summarized using the binary segmentation algorithm and hidden Markov model. Selected genes from the SNP array analysis were also validated using quantitative real-time PCR. The merging of CN and LOH data fabricated distinctive integrated alteration profiles, which were comprised of finely demarcated minimal sites of aberrations. The most prevalent gains (≥ 30%) were detected at the 8q arm: 8q23.1, 8q23.3, 8q24.11, 8q24.13, 8q24.21, 8q24.22, 8q24.23 and 8q24.3, whilst the most ubiquitous losses (≥ 20%) were noted at the 8p12, 8p21.1, 8p21.2, 8p21.1-p21.2, 8p21.3, 8p22, 8p23.1, 8p23.1‑p23.2, 8p23.3, 17p11.2, 17p12, 17p11.2-p12, 17p13.1 and 17p13.2 regions. Copy-neutral LOH was characterized as the most prevailing LOH event, in which the most frequent distributions (≥ 30%) were revealed at 3p21.31, 5q33.2, 12q24.12, 12q24.12‑q24.13 and 14q23.1. These findings offer compre-hensive genome-wide views on breast cancer genomic changes, where the most recurrent gain, loss and copy-neutral LOH events were harboured within the 8q24.21, 8p21.1 and 14q23.1 loci, respectively. This will facilitate the uncovering of true driver genes pertinent to breast cancer biology and the develop-ment of prospective therapeutics.

摘要

乳腺癌是一种具有广泛染色体畸变的异质性疾病。在这项研究中,我们旨在使用单核苷酸多态性(SNP)阵列平台阐明马来西亚医院原发性乳腺癌样本中涉及的潜在染色体拷贝数(CN)改变和杂合性丢失(LOH)。通过将 70 个原发性乳腺癌和 37 个正常外周血样本的提取 DNA 与 Affymetrix 250K Sty SNP 阵列杂交来进行分析。使用二进制分割算法和隐马尔可夫模型对局部 CN 异常和 LOH 进行了统计学总结。还使用定量实时 PCR 验证了 SNP 阵列分析中选择的基因。CN 和 LOH 数据的合并产生了独特的综合改变谱,其中包括精确定义的微小异常部位。最常见的增益(≥30%)发生在 8q 臂:8q23.1、8q23.3、8q24.11、8q24.13、8q24.21、8q24.22、8q24.23 和 8q24.3,而最普遍的缺失(≥20%)发生在 8p12、8p21.1、8p21.2、8p21.1-p21.2、8p21.3、8p22、8p23.1、8p23.1-p23.2、8p23.3、17p11.2、17p12、17p11.2-p12、17p13.1 和 17p13.2 区域。无拷贝数中性 LOH 被描述为最常见的 LOH 事件,其中在 3p21.31、5q33.2、12q24.12、12q24.12-12q24.13 和 14q23.1 区域揭示了最频繁的分布(≥30%)。这些发现提供了对乳腺癌基因组变化的全面全基因组视图,其中最常见的增益、缺失和无拷贝数中性 LOH 事件分别位于 8q24.21、8p21.1 和 14q23.1 基因座中。这将有助于揭示与乳腺癌生物学相关的真正驱动基因,并开发有前途的治疗方法。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索