Molecular profiling of breast cancer cell lines defines relevant tumor models and provides a resource for cancer gene discovery.
Molecular profiling of breast cancer cell lines defines relevant tumor models and provides a resource for cancer gene discovery.
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DOI：
10.1371/journal.pone.0006146
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发表时间：
2009-07-03
期刊：
影响因子：
3.7
通讯作者：
Pollack JR
中科院分区：
文献类型：
--
作者：
Kao J;Salari K;Bocanegra M;Choi YL;Girard L;Gandhi J;Kwei KA;Hernandez-Boussard T;Wang P;Gazdar AF;Minna JD;Pollack JR
乳腺癌细胞系已被广泛用于研究乳腺癌的病理生物学和新的治疗方法。乳腺癌是一种分子异质性疾病，重要的是要了解如何以及哪些细胞系最好地模拟这种多样性。特别是，微阵列研究已经确定了分子亚型-管腔A，管腔B，ERBB 2相关，基底样和正常样-与特征性基因表达模式和潜在的DNA拷贝数改变（CNA）。在这里，我们研究了一组乳腺癌细胞系，以分类分子谱并评估它们与乳腺癌亚型的关系。全基因组DNA微阵列被用来分析52个广泛使用的乳腺癌细胞系的基因表达和CNA，并与现有的原发性乳腺肿瘤的基因表达谱进行比较。采用层次聚类分析法鉴定基因表达亚型，采用基因集富集分析法（GSEA）分析基因表达亚型的生物学特征。整合基因组和转录谱以发现高幅度CNA内具有协调改变的基因拷贝数和表达的候选癌症基因。乳腺癌细胞系的转录谱鉴定了一种管腔型和两种基底样（A和B）亚型。管腔细胞系显示雌激素受体（ER）特征，与管腔-A/B肿瘤相似，基底-A细胞系与ETS-通路和BRCA 1特征相关，与基底样肿瘤相似，基底-B细胞系显示间充质和干/祖细胞特征。与肿瘤相比，细胞系表现出相似的CNA模式，但CNA的总体复杂性更高（遗传上简单的腔A肿瘤未被表示），并且仅部分保守亚型特异性CNA。我们鉴定了80个高水平DNA扩增和13个多拷贝缺失，以及伴随基因表达改变的常驻基因，突出了已知和新的候选乳腺癌基因。总体而言，乳腺癌细胞系在遗传上比肿瘤更复杂，但保留了与腔-基底亚型区别相关的表达模式。分子概况纲要定义了适合于亚型特异性病理生物学、癌症干细胞生物学、生物标志物和治疗研究的细胞系，并为发现新的乳腺癌基因提供了资源。
Breast cancer cell lines have been used widely to investigate breast cancer pathobiology and new therapies. Breast cancer is a molecularly heterogeneous disease, and it is important to understand how well and which cell lines best model that diversity. In particular, microarray studies have identified molecular subtypes–luminal A, luminal B, ERBB2-associated, basal-like and normal-like–with characteristic gene-expression patterns and underlying DNA copy number alterations (CNAs). Here, we studied a collection of breast cancer cell lines to catalog molecular profiles and to assess their relation to breast cancer subtypes. Whole-genome DNA microarrays were used to profile gene expression and CNAs in a collection of 52 widely-used breast cancer cell lines, and comparisons were made to existing profiles of primary breast tumors. Hierarchical clustering was used to identify gene-expression subtypes, and Gene Set Enrichment Analysis (GSEA) to discover biological features of those subtypes. Genomic and transcriptional profiles were integrated to discover within high-amplitude CNAs candidate cancer genes with coordinately altered gene copy number and expression. Transcriptional profiling of breast cancer cell lines identified one luminal and two basal-like (A and B) subtypes. Luminal lines displayed an estrogen receptor (ER) signature and resembled luminal-A/B tumors, basal-A lines were associated with ETS-pathway and BRCA1 signatures and resembled basal-like tumors, and basal-B lines displayed mesenchymal and stem/progenitor-cell characteristics. Compared to tumors, cell lines exhibited similar patterns of CNA, but an overall higher complexity of CNA (genetically simple luminal-A tumors were not represented), and only partial conservation of subtype-specific CNAs. We identified 80 high-level DNA amplifications and 13 multi-copy deletions, and the resident genes with concomitantly altered gene-expression, highlighting known and novel candidate breast cancer genes. Overall, breast cancer cell lines were genetically more complex than tumors, but retained expression patterns with relevance to the luminal-basal subtype distinction. The compendium of molecular profiles defines cell lines suitable for investigations of subtype-specific pathobiology, cancer stem cell biology, biomarkers and therapies, and provides a resource for discovery of new breast cancer genes.
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斯坦福微阵列数据库：新分析工具的实现和软件的开源发布。
影响因子：
14.9
作者：
Demeter, Janos;Beauheim, Catherine;Gollub, Jeremy;Hernandez-Boussard, Tina;Jin, Heng;Maier, Donald;Matese, John C.;Nitzberg, Michael;Wymore, Farrell;Zachariah, Zachariah K.;Brown, Patrick O.;Sherlock, Gavin;Ball, Catherine A.
通讯作者：
Ball, Catherine A.
影响因子：
4.8
作者：
Adam, L;Vadlamudi, R;Kumar, R
通讯作者：
Kumar, R
影响因子：
20.3
作者：
Dorsey, JF;Cunnick, JM;Wu, J
通讯作者：
Wu, J
影响因子：
8
作者：
Cho, D.-H.;Lee, H.-J.;Jung, Y.-K.
通讯作者：
Jung, Y.-K.
DOI：
10.1083/jcb.200211048
发表时间：
2003-02-03
期刊：
The Journal of cell biology
影响因子：
--
作者：
Babu JR;Jeganathan KB;Baker DJ;Wu X;Kang-Decker N;van Deursen JM
通讯作者：
van Deursen JM