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

Reference Materials for Improving Reliability of Multiomics Profiling

High-throughput technologies for multiomics or molecular phenomics profiling have been extensively adopted in biomedical research and clinical applications, offering a more comprehensive understanding of biological processes and diseases. Omics reference materials play a pivotal role in ensuring the accuracy, reliability, and comparability of laboratory measurements and analyses. However, the current application of omics reference materials has revealed several issues, including inappropriate selection and underutilization, leading to inconsistencies across laboratories. This review aims to address these concerns by emphasizing the importance of well-characterized reference materials at each level of omics, encompassing (epi-)genomics, transcriptomics, proteomics, and metabolomics. By summarizing their characteristics, advantages, and limitations along with appropriate performance metrics pertinent to study purposes, we provide an overview of how omics reference materials can enhance data quality and data integration, thus fostering robust scientific investigations with omics technologies.

Enhancing the quality of panel-based tumor mutation burden assessment: a comprehensive study of real-world and in-silico outcomes

Targeted panel-based tumor mutation burden (TMB) assays are widely employed to guide immunotherapy for patients with solid tumors. However, the accuracy and consistency of this method can be compromised due to the variability in technical details across different laboratories, particularly in terms of panel size, somatic mutation detection and TMB calculation rules. Currently, systematic evaluations of the impact of these technical factors on existing assays and best practice recommendations remain lacking. We assessed the performance of 50 participating panel-based TMB assays involving 38 unique methods using cell line samples. In silico experiments utilizing TCGA MC3 datasets were performed to further dissect the impact of technical factors. Here we show that the panel sizes beyond 1.04 Mb and 389 genes are necessary for the basic discrete accuracy, as determined by over 40,000 synthetic panels. The somatic mutation detection should maintain a reciprocal gap of recall and precision less than 0.179 for reliable psTMB calculation results. The inclusion of synonymous, nonsense and hotspot mutations could enhance the accuracy of panel-based TMB assay. A 5% variant allele frequency cut-off is suitable for TMB assays using tumor samples with at least 20% tumor purity. In conclusion, this multicenter study elucidates the major technical factors as sources of variability in panel-based TMB assays and proposed comprehensive recommendations for the enhancement of accuracy and consistency. These findings will assist clinical laboratories in optimizing the methodological details through bioinformatic experiments to enhance the reliability of panel-based methods.

Validation and benchmarking of targeted panel sequencing for cancer genomic profiling

OBJECTIVES

To validate a large next-generation sequencing (NGS) panel for comprehensive genomic profiling and improve patient access to more effective precision oncology treatment strategies.

METHODS

OncoPanScan was designed by targeting 825 cancer-related genes to detect a broad range of genomic alterations. A practical validation strategy was used to evaluate the assay's analytical performance, involving 97 tumor specimens with 25 paired blood specimens, 10 engineered cell lines, and 121 artificial reference DNA samples.

RESULTS

Overall, 1107 libraries were prepared and the sequencing failure rate was 0.18%. Across alteration classes, sensitivity ranged from 0.938 to more than 0.999, specificity ranged from 0.889 to more than 0.999, positive predictive value ranged from 0.867 to more than 0.999, repeatability ranged from 0.908 to more than 0.999, and reproducibility ranged from 0.832 to more than 0.999. The limit of detection for variants was established based on variant frequency, while for tumor mutation burden and microsatellite instability, it was based on tumor content, resulting in a minimum requirement of 20% tumor content. Benchmarking variant calls against validated NGS assays revealed that variations in the dry-bench processes were the primary cause of discordances.

CONCLUSIONS

This study presents a detailed validation framework and empirical recommendations for large panel validation and elucidates the sources of discordant alteration calls by comparing with "gold standard measures."