e15584 Background: Comprehensive tumor profiling using NGS is fundamentally transforming oncology research. However, converting archival tissue samples into libraries is often challenging due to the low quantity and quality of DNA. Here we present accurate detection of variants in the human exome using the novel chemistry of the xGen Prism DNA library preparation kit, optimized for low-input and degraded samples, with xGen Research Exome v2.0 hybrid-capture enrichment. Methods: The IDT Exome v2 panel was used to carry out targeted sequencing of Prism DNA libraries generated from archival FFPE samples. The unique library preparation is enabled by an engineered mutant ligase and proprietary adapters that prevent chimeras and suppress dimer-formation, thereby maximizing the conversion of input DNA to sequencing libraries. Results: We achieved high yields of library (300-400 ng) from input amounts as low as 25 ng for severely damaged FFPE samples (DIN 1-3), > 90% on-target rates and uniform depth of coverage ( > 96% bases covered at > 20X and > 98% bases covered at > 10X) for FFPE samples across a wide range in quality. We also observed minimal exon drop-outs in difficult-to-target genes for severely damaged FFPE material. To validate the variant calling performance of the Prism-Exome workflow, we used the Horizon OncoSpan FFPE reference control which contains 1-92% AF SNVs and Indels and achieved > 98% sensitivity across ~250 SNVs and Indels. Conclusions: This study demonstrates that the xGen Exome Research v2, when combined with xGen Prism DNA library preparation, provides researchers with a complete human exome FFPE-sequencing solution with robust performance across FFPE samples of varying quality.
Diagnostic tools based on next generation sequencing are fundamentally transforming clinical oncology. However, there is a lack of adequate library preparation strategies for highly degraded, clinically relevant samples, such as cell-free DNA (cfDNA) and formalin-fixed paraffin-embedded (FFPE) DNA. Due to the extreme heterogeneity of these sample types, targeted sequencing is often used to achieve deep coverage of genomic loci and enable detection of low-frequency variants. Commercially available protocols for library preparation require stringent size-selection to remove adapter-dimers, which reduces library complexity and variant detection power. Achieving high specificity can be challenging because low-frequency artifacts arise from a variety of sources, including DNA extraction, library construction, PCR, hybrid selection, and sequencing. These artifacts can be identified by "duplex sequencing", where strand-specific unique molecular identifiers (UMIs) are used to confirm the presence of an alteration on both strands of an input molecule. However, duplex sequencing typically delivers low conversion rates with degraded samples due to poor ligation efficiency and template loss during size-selection. Here, we present the IDT library preparation kit optimized for low-input and degraded samples. Our novel library construction chemistry relies on an engineered DNA ligase and proprietary duplexed sequencing adapters that prevent chimeras, suppress dimer-formation (negating the need for size-selection), and enhance variant calling sensitivity. We adapted the workflow for both DNA and RNA applications and demonstrated efficacy using diverse sample types. To assess sensitivity, we created libraries with varied inputs using mixtures of Genome in a Bottle gDNA (NA12878 and NA24385) and performed hybrid capture using a 52 kb custom panel targeting: single nucleotide variants (SNVs), copy number variants (CNVs), and gene fusions. When compared to commercially available methods, our approach yielded a 1.5- to 4-fold increase in library complexity with improved sensitivity to 0.25% variants using 1-25 ng of cfDNA, and 0.5% using 25-250 ng FFPE DNA. We also obtained 100% specificity using duplexed UMI correction, which removed all false-positive calls. RNA libraries were constructed from FFPE NGS reference standards to evaluate the detection of ALK, RET, ROS, NTRK1, and NTRK3 fusions and sequenced to an average target depth of 10,000X. Our method provides superior sensitivity and specificity for detection of low-frequency variants, even with highly degraded DNA.Citation Format: Ariel Royall, Ushati Das Chakravarty, Katharine Dilger, Manqing Hong, Kevin Lai, Kristina Giorda, Keith Bryan, Yu Wang, Lynette Lewis, Scott Rose, Yu Zheng. Detection of low-frequency variants in highly degraded DNA and RNA samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3520.
Abstract Most circulating tumor DNA (ctDNA)-based molecular residual disease (MRD) detection methods leverage a limited genomic footprint, restricting detection sensitivity to 10-4 ~ 10-5 tumor fraction and thus their utility in many clinical settings. For example, early-stage, low tumor mutational burden (TMB) cancers may lack sufficient variants in these limited footprints to produce detectable signals. Further, insights into tumor evolution, including actionable mutations may be missed.Here we report a performance update of the NeXT Personal™️ platform. Utilizing whole genome sequencing of tumor and normal DNA to guide design of bespoke MRD assays, we select up to 1800 high signal, low noise MRD targets and up to 400 exonic variants. Along with proprietary algorithms, this achieves high sensitivity with a limit of detection of 1 ~ 3 parts per million, and targets high specificity (99.99%). Specificity was demonstrated with healthy donor plasma samples and > 200 cancer patient panels from a broad range of solid tumors. Sensitivity and linearity of MRD measurements were determined using dilution series from cell lines and clinical samples, which were orthogonally confirmed (R2 = 0.909, PPA = 100%, NPA = 100%) by digital droplet PCR (ddPCR).In addition, NeXT Personal simultaneously surveys tumor-agnostic content in the same workflow, providing detection of actionable mutations, markers of drug resistance, and mechanisms of tumor evolution from a curated set of variants in 90 clinically-relevant genes. Patient plasma (1 ~ 8 mL; 2 ~ 50 ng of cfDNA) can be rapidly queried to provide mutation-level information about tumor biology, longitudinal trajectory, and clinical actionability. The specificity of NeXT Personal variant detection is > 99.99% with 100% PPV, while individual variant content demonstrates high sensitivity at allele fractions of 0.1% and above, with high accuracy and signal linearity as confirmed by ddPCR (R2 = 0.998).To explore the utility of NeXT Personal in a clinical setting, a retrospective analysis was undertaken in an advanced liver cancer (low TMB) cohort of 11 patients undergoing immunotherapy. Our results demonstrated that changes in ctDNA levels during therapy correlated highly with disease status (6wk vs. baseline, p = 0.017; 9wk vs. baseline, p = 0.004), and were detected prior to clinical response confirmation by RECIST 1.1. Examination of the clinical content provided useful insights into the potential of the assay.Our data demonstrate high analytical performance of the NeXT Personal platform in both MRD and individual variant detection. The assay is sufficiently sensitive for early stage, low shedding, and low TMB cancers, early time points or samples with limited input. The addition of clinically relevant tumor-agnostic actionable content makes NeXT Personal unique in its ability to detect MRD and to ultimately help guide clinicians. Citation Format: Rui Chen, Gábor Bartha, John Lyle, Jason Harris, Sean M. Boyle, Josette Northcott, Dan Norton, Rachel M. Pyke, Fábio C. Navarro, Charles W. Abbott, Christian Haudenschild, Rose Santiago, Darren Nichols, Stephanie Huang, Christopher Nelson, Manju Chinnappa, Yi Chen, Yuker Wang, Laurie Goodman, Qi Zhang, Manqing Hong, Xiaoji Chen, Erin Ayash, Nitin Udar, Sebastian Saldivar, Jian Yan, John West, Richard O. Chen. Analytical performance of an ultra-sensitive, tumor-informed liquid biopsy platform for molecular residual disease detection and clinical guidance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3381.
Abstract Consisting of only ~2% of the human genome, the exome accounts for ~85% of genetic disorders. Efficient sequencing of the human exome with complete and high coverage depth at low cost is invaluable for furthering research in clinical applications. IDT's xGen Exome Panel has proven to be a high performing option. Here, we present the updated xGen Exome Research Panel v2.0 in direct comparison with two other leading commercial human exome panels, using workflows per manufacturer's specifications. NA12878 genomic DNA libraries were pooled together for 8-plex captures for all three platforms and sequenced on the Illumina NextSeq 500. Equivalent number of reads per sample were analyzed against a universal human exome target space to compare across the different exome panels. IDT's Exome NGS solution provided significantly highest on-target percentage at >90% as well as the greatest depth of coverage at >96% bases covered at >20X and >98% bases covered at >10X. Importantly, IDT's platform also reported the most complete gene-level coverage, demonstrated by minimal exon drop-outs in difficult-to-target genes. While 8-plex is the upper limit supported by other suppliers, IDT's platform supports 12-plex workflow. The higher multiplex in combination with high coverage and on-target performance enables IDT to present the lowest total sequencing cost per sample. Since IDT hybridization capture baits are individually synthesized and qualified with the same high standards as standalone oligonucleotide products, lot-to-lot variability is negligible. This presents researchers with an option they can rely on for long-term use and places the focus on the true variabilities of the sample. In conclusion, this study demonstrates xGen Exome Research Panel v2.0, when combined with IDT's DNA Library Prep Kit, provides researchers with a complete Exome NGS solution that is competitive both in performance and sequencing cost. Citation Format: Manqing Hong, Bosun Min, Nicole Roseman, Ekaterina Star, Timothy Rusch, Krishnalekha Datta, Steve Groenewold, Longhui Ren, Jinglie Zhou, Kevin Lai, Xiaohui Wang, Nick Downey, Kristina Giorda, Alexandra Wang, Yu Wang, Lynette A. Lewis, Patrick J. Lau, Steven Henck. Improved human exome sequencing workflow with the most complete coverage [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1349.
Abstract Monitoring of circulating tumor DNA (ctDNA) levels has demonstrated utility in the detection of residual and recurrent disease after tumor resection, and as a prognostic indicator of patient outcome following initial therapy, in a wide range of cancers. Here we describe the analytic validation of the NeXT Personal® assay, an ultra-sensitive, quantitative, tumor-informed ctDNA assay for use in patients diagnosed with solid tumors. NeXT Personal utilizes whole genome sequencing (WGS) of tumor and normal samples and advanced noise suppression to accurately identify somatic variants and generate a patient-specific diagnostic panel based on up to ~1,800 single nucleotide variants. This personalized panel is used to test for the presence of ctDNA in the patient’s blood samples. The NeXT Personal validation was performed using 123 matched tumor, normal and plasma clinical sample sets representing 9 cancer types. The assay achieved 100% specificity on donor normal plasma samples with an in silico approach giving us a confidence interval of 99.87% to 100%. The analytical range measurements were performed using two paired tumor and normal cell lines, one of which is a commercially available MRD control. The detection threshold for the analytical range measurement was 1.68 parts per million (PPM) with a limit of detection at 95% (LOD95) of 3.52 PPM. Furthermore, NeXT Personal showed linearity over a range of 0.8 PPM to 300,000 PPM (Pearson correlation coefficient= 0.9998) with a limit of quant (LOQ) of 10 PPM. The assay also demonstrated strong performance across varying cfDNA input amounts from 2 ng to 30 ng. These studies demonstrate that NeXT Personal is an ultra-sensitive, highly specific, quantitative and robust assay, giving it the potential to detect residual disease and recurrence earlier than less sensitive assays. Citation Format: Josette Northcott, Gabor Bartha, Jason Harris, Shuyuan Ma, Manqing Hong, Qi Zhang, Richard Chen, John Lyle. Analytic validation of an ultra-sensitive tumor-informed circulating tumor DNA assay based on whole genome sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5034.
Abstract RNA-seq is a powerful tool to detect tissue-specific gene expression, splicing, and genetic variations associated with disease states. However, current RNA-seq approaches have limitations due to poor signal from low-abundant transcripts. Furthermore, tissue-derived RNA samples are often highly degraded, thereby limiting gene detection and suffering from potential sequencing artifacts. Here we show that target capture of sequencing libraries tagged with unique molecular identifiers (UMIs) using the xGen™ Prism DNA library prep kit, optimized for low-input and degraded samples, can overcome these obstacles. Directional and UMI-tagged RNA-seq libraries were constructed with RNA extracted from a FFPE RNA Fusion Reference Standard and captured with different designs of the xGen Pan-Cancer Panel spiked with probes for fusion genes. The first design strategy used IDT's stocked Pan Cancer V1.5 panel targeted to gDNA coordinates. The second design involved extracting all associated RefSeq NM transcripts associated with the gene list. Probes were designed to each transcript and duplicate probes were removed based on exact sequence match. The third strategy leveraged a multi-strain design, which created probes from fasta inputs, but removed probes with 90% or greater homology. Normalized expression was highly correlated (> 85%) between captured and uncaptured samples regardless of rRNA depletion prior to library prep. Captured samples had a greater depth of coverage with over 90% on target bases. In addition, our panel design strategies identified low frequency fusions with deep sequencing regardless of rRNA depletion prior to library prep. The multi-strain design was more effective in reducing redundant capture probes compared the other design strategies. Enhanced coverage and PCR de-duplication with UMIs allowed us to reproducibly measure expression over a wide range of RNA inputs (5-500 ng). We show that target capture of RNA-seq libraries reliably maintains expression information present in uncaptured libraries while increasing coverage for poorly expressed genes and low frequency fusions. In addition, the target captured libraries without rRNA depletion prior to library prep have comparable on-target rate and target coverage with rRNA-depleted, target captured libraries. The addition of UMIs to differentiate between PCR duplicates and unique starting molecules also makes it possible to reliably analyze even highly amplified libraries. (For research use only). Citation Format: Tzu-Chun Chen, Katelyn Larkin, Shale Dames, Hsiao-Yun Huang, Kevin Lai, Jessica Sheu, Timothy Barnes, Katia Star, Manqing Hong, Bosun Min, Ryan Demeter, Ashley Dvorak, Ushati Das Chakravarty, Patrick Lau, Steven Henck. High conversion library preparation with optimal hybridization capture panel design strategy in RNA-seq [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 327.
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