Comprehensive comparison of molecular portraits between cell lines and tumors in breast cancer.
Comprehensive comparison of molecular portraits between cell lines and tumors in breast cancer.
复制标题
DOI：
10.1186/s12864-016-2911-z
复制
发表时间：
2016-08-22
期刊：
影响因子：
4.4
通讯作者：
Cheng L
中科院分区：
文献类型：
--
作者：
Jiang G;Zhang S;Yazdanparast A;Li M;Pawar AV;Liu Y;Inavolu SM;Cheng L
合适的乳腺癌原发肿瘤细胞模型一直是乳腺癌研究的重点。细胞系与肿瘤之间的基因组比较可以研究其相似性和差异性，有助于选择合适的细胞模型来模拟肿瘤组织，以正确地评价体外药物反应。本文对68株乳腺癌细胞系和1375例乳腺原发肿瘤的拷贝数变异（CNV）、突变、mRNA表达和蛋白表达进行了综合比较。使用全基因组表达阵列，在细胞和肿瘤之间观察到强相关性。PAM 50基因表达将其分为四种主要的乳腺癌亚型：Luminal A和B，HER 2amp，以及部分细胞和肿瘤中的基底样。一般而言，在肿瘤和细胞之间跨染色体观察到基因组CNV模式。在细胞和肿瘤中均观察到高C > T和C > G颠换率，而细胞的体细胞突变率略高于肿瘤。对蛋白质表达数据进行聚类分析可以合理地恢复细胞系和肿瘤中的乳腺癌亚型。虽然药物靶向蛋白ER/PR和感兴趣的mTOR/GSK 3/TS 2/PDK 1/ER_P118簇在细胞和肿瘤之间显示出一致的模式，但在细胞和肿瘤之间观察到低蛋白相关性。细胞系与肿瘤组织mRNA与蛋白表达的一致性达0.7076。乳腺癌中的这些重要药物靶标ESR 1、PGR、HER 2、EGFR和AR在肿瘤和细胞系中的mRNA和蛋白质变异具有高度相似性。GATA 3和RP 56 KB 1是两个很有前途的乳腺癌药物靶点。从四种分子谱之间的四种相关性得出的总分表明，细胞系BT483、T47 D和MDAMB 453与肿瘤具有最高的相似性。来自这些多个平台的综合数据表明，乳腺癌肿瘤和细胞系之间存在分子特征的相似性和不相似性。这些细胞系仅反映了原发性肿瘤的部分但非全部分子特性。研究结果为乳腺癌研究选择细胞系模型提供了更多证据。本文的在线版本（doi：10.1186/s12864-016-2911-z）包含补充材料，可供授权用户使用。
Proper cell models for breast cancer primary tumors have long been the focal point in the cancer’s research. The genomic comparison between cell lines and tumors can investigate the similarity and dissimilarity and help to select right cell model to mimic tumor tissues to properly evaluate the drug reaction in vitro. In this paper, a comprehensive comparison in copy number variation (CNV), mutation, mRNA expression and protein expression between 68 breast cancer cell lines and 1375 primary breast tumors is conducted and presented. Using whole genome expression arrays, strong correlations were observed between cells and tumors. PAM50 gene expression differentiated them into four major breast cancer subtypes: Luminal A and B, HER2amp, and Basal-like in both cells and tumors partially. Genomic CNVs patterns were observed between tumors and cells across chromosomes in general. High C > T and C > G trans-version rates were observed in both cells and tumors, while the cells had slightly higher somatic mutation rates than tumors. Clustering analysis on protein expression data can reasonably recover the breast cancer subtypes in cell lines and tumors. Although the drug-targeted proteins ER/PR and interesting mTOR/GSK3/TS2/PDK1/ER_P118 cluster had shown the consistent patterns between cells and tumor, low protein-based correlations were observed between cells and tumors. The expression consistency of mRNA verse protein between cell line and tumors reaches 0.7076. These important drug targets in breast cancer, ESR1, PGR, HER2, EGFR and AR have a high similarity in mRNA and protein variation in both tumors and cell lines. GATA3 and RP56KB1 are two promising drug targets for breast cancer. A total score developed from the four correlations among four molecular profiles suggests that cell lines, BT483, T47D and MDAMB453 have the highest similarity with tumors. The integrated data from across these multiple platforms demonstrates the existence of the similarity and dissimilarity of molecular features between breast cancer tumors and cell lines. The cell lines only mirror some but not all of the molecular properties of primary tumors. The study results add more evidence in selecting cell line models for breast cancer research. The online version of this article (doi:10.1186/s12864-016-2911-z) contains supplementary material, which is available to authorized users.