Department of Health Data Science, Institute of Population Health, University of Liverpool, Waterhouse Building, Block F, Brownlow Street, Liverpool, L69 3GF, UK.
MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Garscube Campus, 464 Bearsden Road, Glasgow, G61 1QH, UK.
BMC Genomics. 2024 Sep 3;25(1):827. doi: 10.1186/s12864-024-10737-w.
Circulating tumour DNA (ctDNA) is a subset of cell free DNA (cfDNA) released by tumour cells into the bloodstream. Circulating tumour DNA has shown great potential as a biomarker to inform treatment in cancer patients. Collecting ctDNA is minimally invasive and reflects the entire genetic makeup of a patient's cancer. ctDNA variants in NGS data can be difficult to distinguish from sequencing and PCR artefacts due to low abundance, particularly in the early stages of cancer. Unique Molecular Identifiers (UMIs) are short sequences ligated to the sequencing library before amplification. These sequences are useful for filtering out low frequency artefacts. The utility of ctDNA as a cancer biomarker depends on accurate detection of cancer variants.
In this study, we benchmarked six variant calling tools, including two UMI-aware callers for their ability to call ctDNA variants. The standard variant callers tested included Mutect2, bcftools, LoFreq and FreeBayes. The UMI-aware variant callers benchmarked were UMI-VarCal and UMIErrorCorrect. We used both datasets with known variants spiked in at low frequencies, and datasets containing ctDNA, and generated synthetic UMI sequences for these datasets. Variant callers displayed different preferences for sensitivity and specificity. Mutect2 showed high sensitivity, while returning more privately called variants than any other caller in data without synthetic UMIs - an indicator of false positive variant discovery. In data encoded with synthetic UMIs, UMI-VarCal detected fewer putative false positive variants than all other callers in synthetic datasets. Mutect2 showed a balance between high sensitivity and specificity in data encoded with synthetic UMIs.
Our results indicate UMI-aware variant callers have potential to improve sensitivity and specificity in calling low frequency ctDNA variants over standard variant calling tools. There is a growing need for further development of UMI-aware variant calling tools if effective early detection methods for cancer using ctDNA samples are to be realised.
循环肿瘤 DNA（ctDNA）是肿瘤细胞释放到血液中的无细胞 DNA（cfDNA）的一个子集。循环肿瘤 DNA 作为一种生物标志物，具有很大的潜力，可以为癌症患者的治疗提供信息。采集 ctDNA 具有微创性，并且反映了患者癌症的整个遗传构成。由于 ctDNA 变体丰度低，尤其是在癌症的早期阶段，在 NGS 数据中与测序和 PCR 伪影区分开来可能具有挑战性。独特分子标识符（UMI）是在扩增前连接到测序文库的短序列。这些序列对于过滤低频伪影很有用。ctDNA 作为癌症生物标志物的效用取决于对癌症变体的准确检测。
在这项研究中，我们对六种变体调用工具进行了基准测试，包括两种用于检测 ctDNA 变体的 UMI 感知调用者。测试的标准变体调用者包括 Mutect2、bcftools、LoFreq 和 FreeBayes。基准测试的 UMI 感知变体调用者包括 UMI-VarCal 和 UMIErrorCorrect。我们使用了具有已知低频掺入变体的两个数据集和包含 ctDNA 的数据集，并为这些数据集生成了合成的 UMI 序列。变体调用者对灵敏度和特异性有不同的偏好。Mutect2 显示出高灵敏度，同时在没有合成 UMIs 的数据中比任何其他调用者返回更多的私有变体——这是假阳性变体发现的指标。在带有合成 UMIs 的数据中，UMI-VarCal 在合成数据集中检测到的假定假阳性变体比所有其他调用者都少。Mutect2 在带有合成 UMIs 的数据中显示出高灵敏度和特异性之间的平衡。
我们的结果表明，与标准变体调用工具相比，UMI 感知变体调用者有可能提高对低频 ctDNA 变体的灵敏度和特异性。如果要使用 ctDNA 样本实现癌症的有效早期检测方法，则需要进一步开发 UMI 感知变体调用工具。
