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Deciphering the Correlation between Breast Tumor Samples and Cell Lines by Integrating Copy Number Changes and Gene Expression Profiles

机译:通过整合拷贝数变化和基因表达谱来解读乳腺癌样品与细胞系之间的相关性

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Breast cancer is one of the most common cancers with high incident rate and high mortality rate worldwide. Although different breast cancer cell lines were widely used in laboratory investigations, accumulated evidences have indicated that genomic differences exist between cancer cell lines and tissue samples in the past decades. The abundant molecular profiles of cancer cell lines and tumor samples deposited in the Cancer Cell Line Encyclopedia and The Cancer Genome Atlas now allow a systematical comparison of the breast cancer cell lines with breast tumors. We depicted the genomic characteristics of breast primary tumors based on the copy number variation and gene expression profiles and the breast cancer cell lines were compared to different subgroups of breast tumors. We identified that some of the breast cancer cell lines show high correlation with the tumor group that agrees with previous knowledge, while a big part of them do not, including the most used MCF7, MDA-MB-231, and T-47D. We presented a computational framework to identify cell lines that mostly resemble a certain tumor group for the breast tumor study. Our investigation presents a useful guide to bridge the gap between cell lines and tumors and helps to select the most suitable cell line models for personalized cancer studies.
机译:乳腺癌是世界范围内高发病率和高死亡率的最常见的癌症之一。尽管在实验室研究中广泛使用了不同的乳腺癌细胞系,但积累的证据表明,在过去的几十年中,癌细胞系和组织样本之间存在基因组差异。癌细胞系百科全书和《癌症基因组图集》中保存的癌细胞系和肿瘤样品的丰富分子图谱现在可以对乳腺癌细胞系与乳腺肿瘤进行系统比较。我们根据拷贝数变异和基因表达谱描述了乳腺原发肿瘤的基因组特征,并将乳腺癌细胞系与乳腺肿瘤的不同亚组进行了比较。我们发现,某些乳腺癌细胞系与与先前知识相符的肿瘤组显示出高度相关性,而其中的大部分却没有,包括最常用的MCF7,MDA-MB-231和T-47D。我们提出了一个计算框架,以鉴定与乳腺癌研究中的某些肿瘤组最相似的细胞系。我们的研究提出了有用的指南,以弥合细胞系和肿瘤之间的鸿沟,并有助于选择最适合的细胞系模型进行个性化癌症研究。

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