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细胞分散会影响肿瘤异质性,并导致 NGS 数据解读产生偏差。

Cell Dispersal Influences Tumor Heterogeneity and Introduces a Bias in NGS Data Interpretation.

机构信息

MTA TTK Lendület Cancer Biomarker Research Group, Institute of Enzymology, Budapest, Hungary.

Semmelweis University 2nd Department of Pediatrics, Budapest, Hungary.

出版信息

Sci Rep. 2017 Aug 4;7(1):7358. doi: 10.1038/s41598-017-07487-z.

Abstract

Short and long distance cell dispersal can have a marked effect on tumor structure, high cellular motility could lead to faster cell mixing and lower observable intratumor heterogeneity. Here we evaluated a model for cell mixing that investigates how short-range dispersal and cell turnover will account for mutational proportions. We show that cancer cells can penetrate neighboring and distinct areas in a matter of days. In next generation sequencing runs, higher proportions of a given cell line generated frequencies with higher precision, while mixtures with lower amounts of each cell line had lower precision manifesting in higher standard deviations. When multiple cell lines were co-cultured, cellular movement altered observed mutation frequency by up to 18.5%. We propose that some of the shared mutations detected at low allele frequencies represent highly motile clones that appear in multiple regions of a tumor owing to dispersion throughout the tumor. In brief, cell movement will lead to a significant technical (sampling) bias when using next generation sequencing to determine clonal composition. A possible solution to this drawback would be to radically decrease detection thresholds and increase coverage in NGS analyses.

摘要

短距离和长距离的细胞扩散会对肿瘤结构产生显著影响,高细胞迁移率可能导致更快的细胞混合和更低的肿瘤内异质性。在这里,我们评估了一个细胞混合模型,研究了短距离扩散和细胞更替如何解释突变比例。我们发现,癌细胞可以在几天内穿透相邻和不同的区域。在下一代测序实验中,给定细胞系产生的频率具有更高的精度,而每个细胞系含量较低的混合物具有较低的精度,表现为更高的标准偏差。当多种细胞系共培养时,细胞运动将观察到的突变频率改变高达 18.5%。我们提出,在低等位基因频率下检测到的一些共享突变代表了高度迁移的克隆,由于在整个肿瘤中的扩散,这些克隆出现在肿瘤的多个区域。简而言之,当使用下一代测序来确定克隆组成时,细胞运动将导致显著的技术(采样)偏差。解决这个缺点的一个可能方法是从根本上降低检测阈值并增加 NGS 分析的覆盖范围。

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