Estrogen receptor alpha positive breast tumors and breast cancer cell lines share similarities in their transcriptome data structures.
Estrogen receptor alpha positive breast tumors and breast cancer cell lines share similarities in their transcriptome data structures.
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DOI：
10.3892/ijo.29.6.1581
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发表时间：
2006-12
影响因子：
5.2
通讯作者：
Yuelin Zhu;Antai Wang;Minetta C. Liu;A. Zwart;Richard Lee;A. Gallagher;Y. Wang;W. Miller;J. Dixon;R. Clarke
中科院分区：
文献类型：
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作者：
Yuelin Zhu;Antai Wang;Minetta C. Liu;A. Zwart;Richard Lee;A. Gallagher;Y. Wang;W. Miller;J. Dixon;R. Clarke
已建立的人乳腺癌细胞系被广泛用作乳腺癌研究中的实验模型。虽然这些细胞系及其变体与人类乳腺肿瘤具有许多表型特征，但它们反映乳腺癌潜在分子生物学的程度仍然存在争议。我们使用概率而不是启发式方法来探讨这个问题。来自基因表达微阵列的数据用于比较三种雌激素受体α阳性（ER+）人乳腺癌细胞系（MCF-7、T47 D、ZR-75-1）和13种人乳腺肿瘤（11种ER+; 2种ER-）的转录组的整体结构。通过导出捕获每个数据集（MPC）>或=80%累积方差所需的最高主成分（PC），获得相应数据结构的线性表示。然后，我们鉴定了与MPC最高度相关的那些基因（Pearson相关系数r ≥ 0.800），并鉴定了一组通常与细胞系（M = 5个PC）和肿瘤（M = 6个PC）数据结构两者相关的36个基因。所有36个共同基因与乳腺肿瘤数据中的PC 1相关：21/36个基因与PC 1相关，14/36个基因与PC 2相关，1/36个基因与细胞系数据中的PC 3相关。在定义数据结构中重要的基因包括NF κ B p65、IGFBP-6、鸟氨酸脱羧酶-1和桩蛋白。当MDA-MB-435异种移植物（ER-）的数据被纳入分析时，我们无法找到这些异种移植物和乳腺肿瘤之间的任何共同基因。这些数据清楚地表明，MCF-7，T47 D和ZR-75-1细胞和ER+乳腺肿瘤在其各自的转录组结构中具有实质性的全球相似性，并且这些细胞系是鉴定在一些ER+人类乳腺癌中可能重要的分子事件的良好模型。
Established human breast cancer cell lines are widely used as experimental models in breast cancer research. While these cell lines and their variants share many phenotypic characteristics with human breast tumors, the extent to which they reflect the underlying molecular biology of breast cancer remains controversial. We explored this issue using a probabilistic rather than heuristic approach. Data from gene expression microarrays were used to compare the global structures of the transcriptomes of three estrogen receptor alpha positive (ER+) human breast cancer cell lines (MCF-7, T47D, ZR-75-1) and 13 human breast tumors (11 ER+; 2 ER-). Linear representations of the respective data structures were obtained by deriving those top principal components (PCs) required to capture > or =80% of the cumulative variance for each data set (M PCs). We then identified those genes most highly correlated with the M PCs (Pearson's correlation coefficient r > or =0.800) and identified a group of 36 genes commonly correlated with both the cell line (M = 5 PCs) and tumor (M = 6 PCs) data structures. All 36 common genes were correlated with PC1 from the breast tumor data: 21/36 genes were correlated with PC1, 14/36 genes correlated with PC2, and 1/36 genes correlated with PC3 from the cell line data. Genes important in defining the data structures include NFkappaB p65, IGFBP-6, ornithine decarboxylase-1, and paxillin. When data from MDA-MB-435 xenografts (ER-) were included in the analysis, we were unable to find any common genes between these xenografts and the breast tumors. These data clearly imply that MCF-7, T47D, and ZR-75-1 cells and ER+ breast tumors share substantial global similarities in the structures of their respective transcriptomes, and that these cell lines are good models in which to identify molecular events that are likely to be important in some ER+ human breast cancers.