Integrated Analysis of Gene Expression, CpG Island Methylation, and Gene Copy Number in Breast Cancer Cells by Deep Sequencing

We used deep sequencing technology to profile the transcriptome, gene copy number, and CpG island methylation status simultaneously in eight commonly used breast cell lines to develop a model for how these genomic features are integrated in estrogen receptor positive (ER+) and negative breast cancer. Total mRNA sequence, gene copy number, and genomic CpG island methylation were carried out using the Illumina Genome Analyzer. Sequences were mapped to the human genome to obtain digitized gene expression data, DNA copy number in reference to the non-tumor cell line (MCF10A), and methylation status of 21,570 CpG islands to identify differentially expressed genes that were correlated with methylation or copy number changes. These were evaluated in a dataset from 129 primary breast tumors. Gene expression in cell lines was dominated by ER-associated genes. ER+ and ER− cell lines formed two distinct, stable clusters, and 1,873 genes were differentially expressed in the two groups. Part of chromosome 8 was deleted in all ER− cells and part of chromosome 17 amplified in all ER+ cells. These loci encoded 30 genes that were overexpressed in ER+ cells; 9 of these genes were overexpressed in ER+ tumors. We identified 149 differentially expressed genes that exhibited differential methylation of one or more CpG islands within 5 kb of the 5′ end of the gene and for which mRNA abundance was inversely correlated with CpG island methylation status. In primary tumors we identified 84 genes that appear to be robust components of the methylation signature that we identified in ER+ cell lines. Our analyses reveal a global pattern of differential CpG island methylation that contributes to the transcriptome landscape of ER+ and ER− breast cancer cells and tumors. The role of gene amplification/deletion appears to more modest, although several potentially significant genes appear to be regulated by copy number aberrations.本研究采用深度测序技术，对8种常用乳腺细胞系的转录组（transcriptome）、基因拷贝数（gene copy number）及CpG岛（CpG island）甲基化状态进行同步谱型分析，以构建基因组特征在雌激素受体阳性（estrogen receptor positive, ER+）与阴性乳腺癌中协同调控的模型。本研究采用Illumina基因组分析仪（Illumina Genome Analyzer）开展全mRNA测序、基因拷贝数检测及基因组CpG岛甲基化分析。将测序序列比对至人类参考基因组，以获取数字化基因表达谱数据、以非肿瘤细胞系MCF10A为参照的DNA拷贝数数据，以及21570个CpG岛的甲基化状态，进而筛选出与甲基化或拷贝数改变相关的差异表达基因（differentially expressed genes）。上述差异表达基因在包含129例原发性乳腺肿瘤的数据集内完成验证。细胞系的基因表达谱以ER相关基因为主导，ER+与ER-细胞系可形成两个独立且稳定的聚类簇，两组间共有1873个差异表达基因。所有ER-细胞系均存在8号染色体部分区域缺失，而所有ER+细胞系均存在17号染色体部分区域扩增。上述染色体区域共编码30个在ER+细胞中高表达的基因，其中9个基因在ER+原发性肿瘤中同样呈现高表达。本研究共筛选得到149个差异表达基因，这些基因的5'端上游5kb范围内存在一个或多个CpG岛的甲基化差异，且其mRNA表达丰度与CpG岛甲基化状态呈负相关。在原发性乳腺肿瘤中，我们鉴定出84个基因，它们均为我们在ER+细胞系中发现的甲基化特征的核心组成部分。本研究的分析结果揭示了全局性的CpG岛差异甲基化模式，该模式可塑造ER+与ER-乳腺癌细胞及肿瘤的转录组特征。尽管存在若干受拷贝数异常（copy number aberrations）调控的潜在关键基因，但基因扩增/缺失对转录组的调控作用整体相对有限。