Monash Institute of Medical Research, Monash University, Clayton, Victoria, Australia.
PLoS One. 2013 Sep 26;8(9):e74432. doi: 10.1371/journal.pone.0074432. eCollection 2013.
Next-generation sequencing (NGS) studies in cancer are limited by the amount, quality and purity of tissue samples. In this situation, primary xenografts have proven useful preclinical models. However, the presence of mouse-derived stromal cells represents a technical challenge to their use in NGS studies. We examined this problem in an established primary xenograft model of small cell lung cancer (SCLC), a malignancy often diagnosed from small biopsy or needle aspirate samples. Using an in silico strategy that assign reads according to species-of-origin, we prospectively compared NGS data from primary xenograft models with matched cell lines and with published datasets. We show here that low-coverage whole-genome analysis demonstrated remarkable concordance between published genome data and internal controls, despite the presence of mouse genomic DNA. Exome capture sequencing revealed that this enrichment procedure was highly species-specific, with less than 4% of reads aligning to the mouse genome. Human-specific expression profiling with RNA-Seq replicated array-based gene expression experiments, whereas mouse-specific transcript profiles correlated with published datasets from human cancer stroma. We conclude that primary xenografts represent a useful platform for complex NGS analysis in cancer research for tumours with limited sample resources, or those with prominent stromal cell populations.
下一代测序（NGS）在癌症研究中的应用受到组织样本数量、质量和纯度的限制。在这种情况下，原发异种移植已被证明是一种有用的临床前模型。然而，鼠源性基质细胞的存在给它们在 NGS 研究中的应用带来了技术挑战。我们在一个已建立的小细胞肺癌（SCLC）原发异种移植模型中研究了这个问题，小细胞肺癌通常是从小活检或针吸样本中诊断出来的。我们使用一种根据物种来源分配读取的计算策略，前瞻性地比较了原发异种移植模型与匹配的细胞系和已发表数据集的 NGS 数据。我们在这里表明，尽管存在鼠基因组 DNA，但低覆盖度全基因组分析显示了发表的基因组数据与内部对照之间的显著一致性。外显子捕获测序显示，这种富集程序具有高度的物种特异性，只有不到 4%的读取与鼠基因组匹配。使用 RNA-Seq 进行的人类特异性表达谱分析复制了基于阵列的基因表达实验，而与人类癌症基质中发表数据集相关的鼠特异性转录谱。我们得出结论，原发异种移植代表了一种用于癌症研究中具有有限样本资源或具有突出基质细胞群体的肿瘤的复杂 NGS 分析的有用平台。
