qpure: A Tool to Estimate Tumor Cellularity from Genome-Wide Single-Nucleotide Polymorphism Profiles

Tumour cellularity, the relative proportion of tumour and normal cells in a sample, affects the sensitivity of mutation detection, copy number analysis, cancer gene expression and methylation profiling. Tumour cellularity is traditionally estimated by pathological review of sectioned specimens; however this method is both subjective and prone to error due to heterogeneity within lesions and cellularity differences between the sample viewed during pathological review and tissue used for research purposes. In this paper we describe a statistical model to estimate tumour cellularity from SNP array profiles of paired tumour and normal samples using shifts in SNP allele frequency at regions of loss of heterozygosity (LOH) in the tumour. We also provide qpure, a software implementation of the method. Our experiments showed that there is a medium correlation 0.42 (-value = 0.0001) between tumor cellularity estimated by qpure and pathology review. Interestingly there is a high correlation 0.87 (-value 2.2e-16) between cellularity estimates by qpure and deep Ion Torrent sequencing of known somatic KRAS mutations; and a weaker correlation 0.32 (-value = 0.004) between IonTorrent sequencing and pathology review. This suggests that qpure may be a more accurate predictor of tumour cellularity than pathology review. qpure can be downloaded from https://sourceforge.net/projects/qpure/.

肿瘤细胞纯度（tumour cellularity）指样本中肿瘤细胞与正常细胞的相对占比，其会影响突变检测、拷贝数分析、癌症基因表达及甲基化谱分析的灵敏度。传统上，肿瘤细胞纯度通过对切片标本的病理学检视进行估算；但该方法兼具主观性，且易因病灶内部异质性、病理学检视所用样本与科研用组织间的细胞纯度差异而出现误差。本文提出一种统计模型，可利用肿瘤样本中杂合性缺失（loss of heterozygosity, LOH）区域的单核苷酸多态性（single nucleotide polymorphism, SNP）等位基因频率偏移，从配对肿瘤与正常样本的SNP阵列谱中估算肿瘤细胞纯度。本研究同时提供了该方法的软件实现工具qpure。实验结果表明，qpure估算的肿瘤细胞纯度与病理学检视结果的相关系数为0.42，呈中等程度相关（P值=0.0001）。值得注意的是，qpure的细胞纯度估算结果与已知体细胞KRAS突变的深度Ion Torrent测序（Ion Torrent sequencing）结果的相关系数高达0.87（P值=2.2e-16）；而Ion Torrent测序结果与病理学检视结果的相关系数仅为0.32（P值=0.004）。这表明qpure或许是比病理学检视更为精准的肿瘤细胞纯度预测方法。用户可从https://sourceforge.net/projects/qpure/下载qpure。