Influence of low tumor content on tumor mutational burden estimation by whole‐exome sequencing and targeted panel sequencing. Issue 5 (6th May 2021)

• Record Type: Journal Article
• Authors: Zhang, Wenxin; Wang, Ruixia; Fang, Huan; Ma, Xiangyuan; Li, Dan; Liu, Tao; Chen, Zhenxi; Wang, Ke; Hao, Shiguang; Yu, Zicheng; Chang, Zhili; Na, Chenglong; Wang, Yin; Bai, Jian; Zhang, Yanyan; Chen, Fang; Li, Miao; Chen, Chao; Wei, Liangshen; Li, Jinghua; Chang, Xiaoyan; Qu, Shoufang; Yang, Ling; Huang, Jie
• Is Part Of: Clinical and translational medicine. Volume 11:Issue 5(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-05-06
• Subjects: biomarker -- targeted panel sequencing -- tumor mutational burden -- whole‐exome sequencing; Clinical medicine -- Periodicals; Medicine, Experimental -- Periodicals; Medical innovations -- Periodicals; Molecular biology -- Periodicals; Pathology, Molecular -- Periodicals; 616.027
• DOI: 10.1002/ctm2.415
• Languages: English
• ISSNs: 2001-1326

Abstract

Abstract: 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. Abstract : 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.