Consistency and reproducibility of large panel next-generation sequencing: Multi-laboratory assessment of somatic mutation detection on reference materials with mismatch repair and proofreading deficiency

Introduction: Clinical precision oncology increasingly relies on accurate genome-wide profiling using large panel next generation sequencing; however, difficulties in accurate and consistent detection of somatic mutation from individual platforms and pipelines remain an open question.Objectives: To obtain paired tumor-normal reference materials that can be effectively constructed and interchangeable with clinical samples, and evaluate the performance of 56 panels under routine testing conditions based on the reference samples.Methods: Genes involved in mismatch repair and DNA proofreading were knocked down using the CRISPR-Cas9 technology to accumulate somatic mutations in a defined GM12878 cell line. They were used as reference materials to comprehensively evaluate the reproducibility and accuracy of detection results of oncopanels and explore the potential influencing factors.Results: In total, 14 paired tumor-normal reference DNA samples from engineered cell lines were pre-pared, and a reference dataset comprising 168 somatic mutations in a high-confidence region of 1.8 Mb were generated. For mutations with an allele frequency (AF) of more than 5% in reference samples, 56 panels collectively reported 1306 errors, including 729 false negatives (FNs), 179 false positives (FPs) and 398 reproducibility errors. The performance metric varied among panels with precision and recall ranging from 0.773 to 1 and 0.683 to 1, respectively. Incorrect and inadequate filtering accounted for a large proportion of false discovery (including FNs and FPs), while low-quality detection, cross -contamination and other sequencing errors during the wet bench process were other sources of FNs and FPs. In addition, low AF (<5%) considerably influenced the reproducibility and comparability among panels.Conclusions: This study provided an integrated practice for developing reference standard to assess onco-panels in detecting somatic mutations and quantitatively revealed the source of detection errors. It will promote optimization, validation, and quality control among laboratories with potential applicability in clinical use.(c) 2022 The Authors. Published by Elsevier B.V. on behalf of Cairo University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

This study developed paired tumor-normal reference materials using CRISPR-Cas9 technology and evaluated the performance of 56 panels in detecting somatic mutations. The results showed variations in accuracy and reproducibility among different panels, with filtering errors, low-quality detection, cross-contamination, and other sequencing errors as major sources of false discoveries. The study provides an integrated practice to assess onco-panels and quantitatively reveals the sources of detection errors.