Influence of low tumor content on tumor mutational burden estimation by whole‐exome sequencing and targeted panel sequencing

• Published in: Clinical and translational medicine 2021-05, Vol.11 (5), p.e415-n/a
• Main 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
• Format: Article
• Language: English
• Subjects: biomarker; Biopsy; Cancer; Cell Line, Tumor; Clinical medicine; Exome Sequencing - methods; Genomes; High-Throughput Nucleotide Sequencing - methods; Humans; Liquid Biopsy; Medical research; Mutation; Neoplasms - genetics; Neoplasms - pathology; targeted panel sequencing; Tumor Burden - genetics; tumor mutational burden; whole‐exome sequencing
• ISSN: 2001-1326; 2001-1326
• DOI: 10.1002/ctm2.415

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