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肿瘤突变负荷估计中的偏倚和不一致性。

Bias and inconsistency in the estimation of tumour mutation burden.

机构信息

School of Mathematical & Statistical Sciences, National University of Ireland, Galway, Ireland.

出版信息

BMC Cancer. 2022 Aug 2;22(1):840. doi: 10.1186/s12885-022-09897-3.

Abstract

BACKGROUND

Tumour mutation burden (TMB), defined as the number of somatic mutations per megabase within the sequenced region in the tumour sample, has been used as a biomarker for predicting response to immune therapy. Several studies have been conducted to assess the utility of TMB for various cancer types; however, methods to measure TMB have not been adequately evaluated. In this study, we identified two sources of bias in current methods to calculate TMB.

METHODS

We used simulated data to quantify the two sources of bias and their effect on TMB calculation, we down-sampled sequencing reads from exome sequencing datasets from TCGA to evaluate the consistency in TMB estimation across different sequencing depths. We analyzed data from ten cancer cohorts to investigate the relationship between inferred TMB and sequencing depth.

RESULTS

We found that TMB, estimated by counting the number of somatic mutations above a threshold frequency (typically 0.05), is not robust to sequencing depth. Furthermore, we show that, because only mutations with an observed frequency greater than the threshold are considered, the observed mutant allele frequency provides a biased estimate of the true frequency. This can result in substantial over-estimation of the TMB, when the cancer sample includes a large number of somatic mutations at low frequencies, and exacerbates the lack of robustness of TMB to variation in sequencing depth and tumour purity.

CONCLUSION

Our results demonstrate that care needs to be taken in the estimation of TMB to ensure that results are unbiased and consistent across studies and we suggest that accurate and robust estimation of TMB could be achieved using statistical models that estimate the full mutant allele frequency spectrum.

摘要

背景

肿瘤突变负荷(TMB)定义为肿瘤样本中测序区域内每兆碱基的体细胞突变数,已被用作预测免疫治疗反应的生物标志物。已经进行了几项研究来评估 TMB 在各种癌症类型中的效用;然而,测量 TMB 的方法尚未得到充分评估。在这项研究中,我们确定了当前计算 TMB 的方法中存在的两种偏差来源。

方法

我们使用模拟数据来量化这两种偏差及其对 TMB 计算的影响,我们从 TCGA 的外显子组测序数据集中对测序reads 进行了下采样,以评估在不同测序深度下 TMB 估计的一致性。我们分析了来自十个癌症队列的数据,以研究推断的 TMB 与测序深度之间的关系。

结果

我们发现,通过计数高于阈值频率(通常为 0.05)的体细胞突变数量来估计的 TMB 对测序深度不稳健。此外,我们表明,由于只有观察到的频率大于阈值的突变才被考虑,因此观察到的突变等位基因频率提供了对真实频率的有偏差的估计。当癌症样本中包含大量低频的体细胞突变时,这可能导致 TMB 的大量高估,并加剧了 TMB 对测序深度和肿瘤纯度变化的不稳健性。

结论

我们的结果表明,在估计 TMB 时需要小心谨慎,以确保结果在研究之间是无偏的且一致的,我们建议使用可以估计完整突变等位基因频率谱的统计模型来实现 TMB 的准确和稳健估计。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ca3/9347149/d0968b1ad9ec/12885_2022_9897_Fig1_HTML.jpg

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