Circulating tumor DNA (ctDNA) sequencing is being rapidly adopted in precision oncology, but the accuracy, sensitivity, and reproducibility of ctDNA assays is poorly understood. Here we report the findings of a multi-site, cross-platform evaluation of the analytical performance of five industry-leading ctDNA assays. We evaluated each stage of the ctDNA sequencing workflow with simulations, synthetic DNA spike-in experiments, and proficiency testing on standardized cell line–derived reference samples. Above 0.5% variant allele frequency, ctDNA mutations were detected with high sensitivity, precision and reproducibility by all five assays, whereas below this limit detection became unreliable and varied widely between assays, especially when input material was limited. Missed mutations (false-negatives) were more common than erroneous candidates (false-positives), indicating that the reliable sampling of rare ctDNA fragments is the key challenge for ctDNA assays. This comprehensive evaluation of the analytical performance of ctDNA assays serves to inform best-practice guidelines and provides a resource for precision oncology.
Background Targeted sequencing using oncopanels requires comprehensive assessments of accuracy and detection sensitivity to ensure analytical validity. By employing reference materials characterized by the U.S. Food and Drug Administration-led SEquence Quality Control project phase2 (SEQC2) effort, we perform a cross-platform multi-lab evaluation of eight Pan-Cancer panels to assess best practices for oncopanel sequencing. Results All panels demonstrate high sensitivity across targeted high-confidence coding regions and variant types for the variants previously verified to have variant allele frequency (VAF) in the 5–20% range. Sensitivity is reduced by utilizing VAF thresholds due to inherent variability in VAF measurements. Enforcing a VAF threshold for reporting has a positive impact on reducing false positive calls. Importantly, the false positive rate is found to be significantly higher outside the high-confidence coding regions, resulting in lower reproducibility. Thus, region restriction and VAF thresholds lead to low relative technical variability in estimating promising biomarkers and tumor mutational burden. Conclusion This comprehensive study provides actionable guidelines for oncopanel sequencing and clear evidence that supports a simplified approach to assess the analytical performance of oncopanels. It will facilitate the rapid implementation, validation, and quality control of oncopanels in clinical use.
Poster #3732 * expected fold changes measured by orthogonal methods No CNV called in 24 normal samples (in duplicates) CNV specificity = 100% *excluding known polymorphism sites For Research Use Only. Not for use in diagnostic procedures.
Recent studies have highlighted the importance of gene fusions and splice variants in solid tumor profiling1. Next-generation sequencing can be an effective means of detecting these alterations in FFPE samples using RNA rather than DNA, as a single chimeric RNA transcript could result from numerous alterations in DNA2. To that end, Illumina developed TruSight® Tumor 1703, a comprehensive, hybrid capture-based NGS assay targeting 170 key cancer genes. Along with a DNA workflow, the assay includes a RNA workflow for the identification of splice variants and gene fusions. Following sequencing on the NextSeq® or HiSeq® instruments, TruSight® Tumor 170 offers an analytical pipeline which initiates variant calling. These algorithms were first optimized against the simulated read data from >350 fusions and splice variants reported in the RNA content of the gene panel. A hybrid approach of read alignment and assembly was used to enhance the fusion calling sensitivity. Deliberate filters were designed to reduce false positive calling from sequence homologs, polymerase read-through, or FFPE artifacts. For splice variant calling, a panel of FFPE non-cancerous samples were used to capture false positive mutation calls. With endogenous RNA splicing in cellular physiology, exon-boundary probes were added in the hybrid capture to enhance enrichment efficiency. To the best of our knowledge, there is not yet a standard definition for the limit of detection (LoD) in detecting gene fusions and splice variants from NGS data. We propose to define the LoD of a fusion calling and splice variant NGS panel as the lowest molecule count of a chimeric transcript that could be reliably detected with a sufficient number of supporting sequencing reads. To determine the LoD of TruSight® Tumor 170 using this definition, we mixed cell lines expressing a panel of known fusions and splice variants to measure the copy number of each chimeric transcript. Using these samples we examined the ability of the assay to confidently detect the alterations using 40 ng of RNA input. To demonstrate the analytical sensitivity and specificity of this NGS based assay, we compiled a panel of 49 mixed samples and validated the molecule count to be near the LoD of 5 copies per ng RNA input by PCR. The sensitivity was >98% for fusions and 100% for splice variants. For understanding the limit of blank (LoB) of the assay, another panel of 40 samples not harboring fusions and splice variants was also assessed by TruSight® Tumor 170. These samples demonstrated a ~97% specificity for fusion calling and >95% specificity for splice variant calling. These results indicate that the TruSight® Tumor 170 panel analysis can identify lowly expressed fusions and splice variants from a small amount of compromised RNA from solid tumor samples at high analytical sensitivity and specificity. 1 Klijn et al. (2015) 2 Maher et al. (2009) 3 For Research Use Only. Citation Format: Tingting Du, June Snedecor, Jennifer S. LoCoco, Xiao Chen, Laurel Ball, Allan Castaneda, Danny Chou, Katie Clark, Brian Crain, Anthony Daulo, Manh Do, Sarah Dumm, Yonmee Han, Mike Havern, Chia-Ling Hsieh, Tingting Jiang, Suzanne Johansen, Scott Lang, Rachel Liang, Jaime McLean, Yousef Nassiri, Austin Purdy, Jason Rostron, Jennifer Silhavy, Natasha Talago, Li Teng, Kevin Wu, Clare Zlatkov, Chen Zhao, Ali Kuraishy, Karen Gutekunst, Sohela De Rozieres, Matthew Friedenberg, Anne C. Jager, Han-Yu Chuang. Analytical performance of TruSight® Tumor 170 in the detection of gene fusions and splice variants using RNA from formalin-fixed, paraffin-embedded (FFPE) solid tumor samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 565. doi:10.1158/1538-7445.AM2017-565
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.