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首页> 外文期刊>Clinical and Translational Medicine >Influence of low tumor content on tumor mutational burden estimation by whole‐exome sequencing and targeted panel sequencing
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Influence of low tumor content on tumor mutational burden estimation by whole‐exome sequencing and targeted panel sequencing

机译：低肿瘤含量对全外末端测序和靶线测序肿瘤突变沉重估算的影响

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Background Tumor mutational burden (TMB) is a promising biomarker for stratifying patient subpopulation who would benefit from immune checkpoint blockade (ICB) therapies. Although great efforts have been made for standardizing TMB measurement, mutation calling and TMB quantification can be challenging in samples with low tumor content including liquid biopsies. The effect of varying tumor content on TMB estimation by different assay methods has never been systematically investigated. Method We established a series of reference standard DNA samples derived from 11 pairs of tumor–normal matched human cell lines across different cancer types. Each tumor cell line was mixed with its matched normal at 0% (control), 1%, 2%, 5%, and 10% mass‐to‐mass ratio to mimic the clinical samples with low tumor content. TMB of these reference standards was evaluated by both ～1000× whole‐exome sequencing (wesTMB) and targeted panel sequencing (psTMB) at four different vendors. Both regression and classification analyses of TMB were performed for theoretical investigation and clinical practice purposes. Results Linear regression model was established that demonstrated in silico psTMB determined by regions of interest (ROI) as a great representative of wesTMB based on TCGA dataset. It was also true in our reference standard samples as the predicted psTMB interval based on the observed wesTMB captured the intended 90% of the in silico psTMB values. Although ～1000× deep WES was applied, reference standard samples with less than 5% of tumor proportions are below the assay limit of detection (LoD) of wesTMB quantification. However, predicted wesTMB based on observed psTMB accurately classify (&0.97 AUC) for TMB high and low patient stratification even in samples with 2% of tumor content, which is more clinically relevant, as TMB determination should be a qualitative assay for TMB high and low patient classification. One targeted panel sequencing vendor using an optimized blood psTMB pipeline can further classify TMB status accurately (&0.82 AUC) in samples with only 1% of tumor content. Conclusions We developed a linear model to establish the quantitative correlation between wesTMB and psTMB. A set of DNA reference standards was produced in aid to standardize TMB measurements in samples with low tumor content across different targeted sequencing panels. This study is a significant contribution aiming to harmonize TMB estimation and extend its future application in clinical samples with low tumor content including liquid biopsy. Established 11 sets of reference standard samples with variable tumor proportions for evaluating TMB estimation. In silico and experimentally verified the linear regression model between the TMB analyzed by deep whole‐exome sequencing and targeted panel sequencing in reference standard samples. Targeted panel sequencing method might outperform WES for TMB estimation and categorization in samples with low tumor proportion.
机译：背景技术肿瘤突变负担（TMB）是针对分层患者群的有前途的生物标志物，其将从免疫检查点封闭（ICB）疗法中受益。尽管已经进行了标准化TMB测量的巨大努力，但是突变呼叫和TMB定量可以在具有低肿瘤含量的样品中具有挑战性，包括液体活组织检查。从未系统地研究了不同测定方法对不同测定方法进行TMB估计的影响。方法我们建立了一系列参考标准DNA样品，其衍生自不同癌症类型的11对肿瘤正常匹配的人细胞系。将每根肿瘤细胞系与其匹配的正常相匹配为0％（对照），1％，2％，5％和10％质量比以模拟肿瘤含量低的临床样品。在四个不同的供应商处，通过〜1000×全exome测序（Westmb）和目标面板测序（PSTMB）评估了这些参考标准的TMB。对TMB的回归和分类分析进行了理论调查和临床实践。结果建立了线性回归模型，该模型在硅PSTMB中展示，由利息地区（ROI）确定为基于TCGA数据集的Westmb的伟大代表。在我们的参考标准样本中也是如此，因为基于观察到的WestMB的预测PSTMB间隔捕获了Silico PSTMB值中的预期90％。虽然施加〜1000×深，但具有少于5％的肿瘤比例的参考标准样品低于Westmb定量检测（LOD）的测定极限。然而，即使在具有2％的肿瘤含量的样品中，基于观察到的PSTMB的Westmb基于观察到的PSTMB，即使在具有2％的肿瘤含量的样品中，该分层也在具有更高临床相关的样品中，因为TMB测定应该是定性测定TMB高低患者分类。使用优化的血液PSTMB管道的一个有针对性的面板测序供应商可以在仅具有1％的肿瘤含量的样品中准确地（＆amp; 0.82 AUC）进一步分类TMB状态。结论我们开发了一种线性模型，以确定Westmb和Pstmb之间的定量相关性。制备了一组DNA参考标准，辅助在不同靶向测序板上的肿瘤含量低的样品中标准化TMB测量。本研究是旨在协调TMB估计的重要贡献，并扩展其未来在具有低肿瘤含量的临床样本中的应用，包括液体活组织检查。建立了11组参考标准样品，具有可变肿瘤比例，用于评估TMB估计。在硅中，通过参考标准样品中深度全外末端测序和靶线测序分析的TMB之间的线性回归模型。有针对性的面板测序方法可能占TMB估计和肿瘤比例低的样品中的TMB估计和分类。

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