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首页> 外文期刊>BioMed research international >Deciphering the Correlation between Breast Tumor Samples and Cell Lines by Integrating Copy Number Changes and Gene Expression Profiles
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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密乳腺肿瘤样品和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:乳腺癌是最常见的癌症之一,发生了很高的入射率和全球性高死亡率。虽然不同的乳腺癌细胞系广泛应用于实验室调查,但积累的证据表明,在过去几十年中癌细胞系和组织样本之间存在基因组差异。癌细胞系和肿瘤样品中沉积在癌细胞系细胞系细胞和癌症基因组Atlas中的丰富分子谱现在允许与乳腺肿瘤的乳腺癌细胞系进行系统比较。我们描绘了基于拷贝数变异的基于拷贝数变异和基因表达谱的基因组特征,并将乳腺癌细胞系与乳腺肿瘤的不同亚组进行比较。我们认为一些乳腺癌细胞系与与以前知识同意的肿瘤组具有高相关性,而其中的大部分则没有,包括最常用的MCF7,MDA-MB-231和T-47D。我们介绍了计算框架,以识别细胞系,这些细胞系大多是乳腺肿瘤研究的某种肿瘤组。我们的调查介绍了弥合细胞系和肿瘤之间的差距的有用指南,并有助于为个性化癌症研究选择最合适的细胞系模型。

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