Chen Wenhan, Robertson Alan J, Ganesamoorthy Devika, Coin Lachlan J M
Institute for Molecular Bioscience, The University of Queensland, St Lucia, Queensland, 4072, Australia.
Nucleic Acids Res. 2017 Mar 17;45(5):e34. doi: 10.1093/nar/gkw1086.
Accurate identification of copy number alterations is an essential step in understanding the events driving tumor progression. While a variety of algorithms have been developed to use high-throughput sequencing data to profile copy number changes, no tool is able to reliably characterize ploidy and genotype absolute copy number from tumor samples that contain less than 40% tumor cells. To increase our power to resolve the copy number profile from low-cellularity tumor samples, we developed a novel approach that pre-phases heterozygote germline single nucleotide polymorphisms (SNPs) in order to replace the commonly used 'B-allele frequency' with a more powerful 'parental-haplotype frequency'. We apply our tool-sCNAphase-to characterize the copy number and loss-of-heterozygosity profiles of four publicly available breast cancer cell-lines. Comparisons to previous spectral karyotyping and microarray studies revealed that sCNAphase reliably identified overall ploidy as well as the individual copy number mutations from each cell-line. Analysis of artificial cell-line mixtures demonstrated the capacity of this method to determine the level of tumor cellularity, consistently identify sCNAs and characterize ploidy in samples with as little as 10% tumor cells. This novel methodology has the potential to bring sCNA profiling to low-cellularity tumors, a form of cancer unable to be accurately studied by current methods.
准确识别拷贝数改变是理解驱动肿瘤进展事件的关键步骤。虽然已经开发了多种算法来利用高通量测序数据描绘拷贝数变化,但没有一种工具能够可靠地从肿瘤细胞比例低于40%的肿瘤样本中表征倍性和基因型绝对拷贝数。为了提高我们从低细胞含量肿瘤样本中解析拷贝数图谱的能力,我们开发了一种新方法,该方法对杂合子种系单核苷酸多态性(SNP)进行预相位分析,以便用更强大的“亲本单倍型频率”取代常用的“B等位基因频率”。我们应用我们的工具sCNAphase来表征四种公开可用的乳腺癌细胞系的拷贝数和杂合性缺失图谱。与先前的光谱核型分析和微阵列研究相比,结果表明sCNAphase能够可靠地识别总体倍性以及每个细胞系的个体拷贝数突变。对人工细胞系混合物的分析证明了该方法能够确定肿瘤细胞含量水平,在肿瘤细胞比例低至10%的样本中一致地识别体细胞拷贝数改变(sCNA)并表征倍性。这种新方法有可能将sCNA分析应用于低细胞含量肿瘤,这是一种目前方法无法准确研究的癌症形式。