Cancer Biology Division, Ponce Research Institute, Ponce Health Sciences University, Ponce, Puerto Rico.
Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida.
Cancer Res. 2019 Apr 1;79(7):1263-1273. doi: 10.1158/0008-5472.CAN-18-2747. Epub 2019 Mar 20.
Recent work points to a lack of diversity in genomics studies from genome-wide association studies to somatic (tumor) genome analyses. Yet, population-specific genetic variation has been shown to contribute to health disparities in cancer risk and outcomes. Immortalized cancer cell lines are widely used in cancer research, from mechanistic studies to drug screening. Larger collections of cancer cell lines better represent the genomic heterogeneity found in primary tumors. Yet, the genetic ancestral origin of cancer cell lines is rarely acknowledged and often unknown. Using genome-wide genotyping data from 1,393 cancer cell lines from the Catalogue of Somatic Mutations in Cancer (COSMIC) and Cancer Cell Line Encyclopedia (CCLE), we estimated the genetic ancestral origin for each cell line. Our data indicate that cancer cell line collections are not representative of the diverse ancestry and admixture characterizing human populations. We discuss the implications of genetic ancestry and diversity of cellular models for cancer research and present an interactive tool, Estimated Cell Line Ancestry (ECLA), where ancestry can be visualized with reference populations of the 1000 Genomes Project. Cancer researchers can use this resource to identify cell line models for their studies by taking ancestral origins into consideration.
最近的研究表明,从全基因组关联研究到体细胞(肿瘤)基因组分析,基因组学研究中存在多样性不足的问题。然而,特定人群的遗传变异已被证明会导致癌症风险和结果的健康差异。永生化癌细胞系广泛应用于癌症研究,从机制研究到药物筛选。更大的癌细胞系集合更好地代表了原发性肿瘤中发现的基因组异质性。然而,癌细胞系的遗传祖先起源很少被承认,而且通常是未知的。利用来自 Catalogue of Somatic Mutations in Cancer (COSMIC) 和 Cancer Cell Line Encyclopedia (CCLE) 的 1393 个癌细胞系的全基因组基因分型数据,我们估计了每个细胞系的遗传祖先起源。我们的数据表明,癌细胞系集合不能代表人类群体的多样化祖先和混合特征。我们讨论了遗传祖先和细胞模型多样性对癌症研究的影响,并提出了一个交互式工具,即 Estimated Cell Line Ancestry (ECLA),其中可以使用 1000 Genomes Project 的参考群体来可视化祖先。癌症研究人员可以通过考虑祖先起源来使用此资源来为他们的研究确定细胞系模型。