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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., Editorial summary: Reliable detection of mutations below 0.5% variant allele frequency remains a key challenge for circulating tumor DNA sequencing assays.

Sequencing circulating tumor DNA (ctDNA) from liquid biopsies may better assess tumor heterogeneity than limited sampling of tumor tissue. Here, we explore ctDNA-based heterogeneity and its correlation with treatment outcome in STEAM, which assessed efficacy and safety of concurrent and sequential FOLFOXIRI-bevacizumab (BEV) vs. FOLFOX-BEV for first-line treatment of metastatic colorectal cancer. We sequenced 146 pre-induction and 89 post-induction patient plasmas with a 198-kilobase capture-based assay, and applied Mutant-Allele Tumor Heterogeneity (MATH), a traditionally tissue-based calculation of allele frequency distribution, on somatic mutations detected in plasma. Higher levels of MATH, particularly in the post-induction sample, were associated with shorter progression-free survival (PFS). Patients with high MATH vs. low MATH in post-induction plasma had shorter PFS (7.2 vs. 11.7 months; hazard ratio, 3.23; 95% confidence interval, 1.85–5.63; log-rank p < 0.0001). These results suggest ctDNA-based tumor heterogeneity may have potential prognostic value in metastatic cancers.

With advances in NGS technologies, transcriptional profiling of human tissue across many diseases is becoming more routine, leading to the generation of petabytes of data deposited in public repositories. There is a need for bench scientists with little computational expertise to be able to access and mine this data to understand disease pathology, identify robust biomarkers of disease and the effect of interventions (

With advances in NGS technologies, transcriptional profiling of human tissue across many diseases is becoming more routine, leading to the generation of petabytes of data deposited in public repositories. There is a need for bench scientists with little computational expertise to be able to access and mine this data to understand disease pathology, identify robust biomarkers of disease and the effect of interventions (in vivo or in vitro). To this end we release an open source analytics and visualization platform for expression data called OmicsView, http://omicsview.org.This platform comes preloaded with 1000s of samples across many disease areas and normal tissue, including the GTEx database, all processed with a harmonized pipeline. We demonstrate the power and ease-of-use of the platform by means of a Crohn’s disease data mining exercise where we can quickly uncover disease pathology and identify strong biomarkers of disease and response to treatment.

The lipopolysaccharide biosynthesis pathway is considered an attractive drug target against the rising threat of multi-drug-resistant Gram-negative bacteria. Here, we report two novel small-molecule inhibitors (compounds 1 and 2) of the acyltransferase LpxA, the first enzyme in the lipopolysaccharide biosynthesis pathway. We show genetically that the antibacterial activities of the compounds against efflux-deficient Escherichia coli are mediated by LpxA inhibition. Consistently, the compounds inhibited the LpxA enzymatic reaction in vitro. Intriguingly, using biochemical, biophysical, and structural characterization, we reveal two distinct mechanisms of LpxA inhibition; compound 1 is a substrate-competitive inhibitor targeting apo LpxA, and compound 2 is an uncompetitive inhibitor targeting the LpxA/product complex. Compound 2 exhibited more favorable biological and physicochemical properties than compound 1 and was optimized using structural information to achieve improved antibacterial activity against wild-type E. coli. These results show that LpxA is a promising antibacterial target and imply the advantages of targeting enzyme/product complexes in drug discovery.

Induced pluripotent stem cell (iPSC) derived cell types are increasingly employed as in vitro model systems for drug discovery. For these studies to be meaningful, it is important to understand the reproducibility of the iPSC-derived cultures and their similarity to equivalent endogenous cell types. Single-cell and single-nucleus RNA sequencing (RNA-seq) are useful to gain such understanding, but they are expensive and time consuming, while bulk RNA-seq data can be generated quicker and at lower cost. In silico cell type decomposition is an efficient, inexpensive, and convenient alternative that can leverage bulk RNA-seq to derive more fine-grained information about these cultures. We developed CellMap, a computational tool that derives cell type profiles from publicly available single-cell and single-nucleus datasets to infer cell types in bulk RNA-seq data from iPSC-derived cell lines.

In recent years High-Throughput Sequencing (HTS) based methods to detect mutations in biotherapeutic transgene products have become a key quality step deployed during the development of manufacturing cell line clones. Previously we reported on a higher throughput, rapid mutation detection method based on amplicon sequencing (targeting transgene RNA) and detailed its implementation to facilitate cell line clone selection. By gaining experience with our assay in a diverse set of cell line development programs, we improved the computational analysis as well as experimental protocols. Here we report on these improvements as well as on a comprehensive benchmarking of our assay. We evaluated assay performance by mixing amplicon samples of a verified mutated antibody clone with a non-mutated antibody clone to generate spike-in mutations from ∼60% down to ∼0.3% frequencies. We subsequently tested the effect of 16 different sample and HTS library preparation protocols on the assay's ability to quantify mutations and on the occurrence of false-positive background error mutations (artifacts). Our evaluation confirmed assay robustness, established a high confidence limit of detection of ∼0.6%, and identified protocols that reduce error levels thereby significantly reducing a source of false positives that bottlenecked the identification of low-level true mutations. This article is protected by copyright. All rights reserved.

SummaryWe developed Quickomics, a feature-rich R Shiny-powered tool to enable biologists to fully explore complex omics statistical analysis results and perform advanced analysis in an easy-to-use interactive interface. It covers a broad range of secondary and tertiary analytical tasks after primary analysis of omics data is completed. Each functional module is equipped with customizable options and generates both interactive and publication-ready plots to uncover biological insights from data. The modular design makes the tool extensible with ease.AvailabilityResearchers can experience the functionalities with their own data or demo RNA-Seq and proteomics datasets by using the app hosted at http://quickomics.bxgenomics.com and following the tutorial, https://bit.ly/3rXIyhL. The source code under GPLv3 license is provided at https://github.com/interactivereport/Quickomics for local installation.Supplementary informationSupplementary materials are available at https://bit.ly/37HP17g.

In recent years Next-Generation Sequencing (NGS) based methods to detect mutations in biotherapeutic transgene products have become a key quality step deployed during the development of manufacturing cell line clones. Previously we reported on a higher throughput, rapid mutation detection method based on amplicon sequencing (targeting transgene RNA) and detailed its implementation to facilitate cell line clone selection. By gaining experience with our assay in a diverse set of cell line development programs, we improved the computational analysis as well as experimental protocols. Here we report on these improvements as well as on a comprehensive benchmarking of our assay. We evaluated assay performance by mixing amplicon samples of a verified mutated antibody clone with a non-mutated antibody clone to generate spike-in mutations from ~60% down to ~0.3% frequencies. We subsequently tested the effect of 16 different sample and NGS library preparation protocols on the assay’s ability to quantify mutations and on the occurrence of false-positive background error mutations (artifacts). Our evaluation confirmed assay robustness, established a high confidence limit of detection of ~0.6%, and identified protocols that reduce error levels thereby significantly reducing a source of false positives that bottlenecked the identification of low-level true mutations.

BK virus (BKV)-associated nephropathy is the second leading cause of graft loss in kidney transplant recipients. Due to the high prevalence of persistent infection with BKV in the general population, it is possible that either the transplant recipient or donor may act as the source of virus resulting in viruria and viremia. Although several studies suggest a correlation between donor-recipient serostatus and the development of BK viremia, specific risk factors for BKV-related complications in the transplant setting remain to be established.We retrospectively determined the pretransplant BKV neutralizing serostatus of 116 donors (D)-recipient (R) pairs using infectious BKV neutralization assays with representatives from the 4 major viral serotypes. The neutralizing serostatus of donors and recipients was then correlated with the incidence of BK viremia during the first year posttransplantation.There were no significant differences in baseline demographics or transplant data among the 4 neutralizing serostatus groups, with the exception of calculated panel-reactive antibody which was lowest in the D+/R- group. Recipients of kidneys from donors with significant serum neutralizing activity (D+) had elevated risk for BK viremia, regardless of recipient serostatus (D+ versus D-: odd ratio, 5.0; 95% confidence interval, 1.9-12.7]; P = 0.0008). Furthermore, donor-recipient pairs with D+/R- neutralizing serostatus had the greatest risk for BK viremia (odds ratio, 4.9; 95% confidence interval, 1.7-14.6; P = 0.004).Donor neutralizing serostatus correlates significantly with incidence of posttransplant BK viremia. Determination of donor-recipient neutralizing serostatus may be useful in assessing the risk of BKV infection in kidney transplant recipients.

The lipopolysaccharide biosynthesis pathway is considered an attractive drug target against the rising threat of multidrug-resistant Gram-negative bacteria. Here, we report two novel small-molecule inhibitors (compounds 1 and 2) of the acyltransferase LpxA, the first enzyme in the lipopolysaccharide biosynthesis pathway. We show genetically that the antibacterial activities of the compounds against efflux-deficient Escherichia coli are mediated by LpxA inhibition. Consistently, the compounds inhibited the LpxA enzymatic reaction in vitro. Intriguingly, using biochemical, biophysical, and structural characterization, we reveal two distinct mechanisms of LpxA inhibition; compound 1 is a substrate-competitive inhibitor targeting apo LpxA and compound 2 is an uncompetitive inhibitor targeting the LpxA-product complex. Compound 2 exhibited more favorable biological and physicochemical properties than compound 1, and was optimized using structural information to achieve improved antibacterial activity against wild type E. coli. These results show that LpxA is a promising antibacterial target and imply the advantages of targeting enzyme-product complexes in drug discovery.

Tight coordination of inner and outer membrane biosynthesis is very important in Gram-negative bacteria. Biosynthesis of the lipid A moiety of lipopolysaccharide, which comprises the outer leaflet of the outer membrane has garnered interest for Gram-negative antibacterial discovery. In particular, several potent inhibitors of LpxC (the first committed step of the lipid A pathway) are described. Here we show that serial passaging of Klebsiella pneumoniae in increasing levels of an LpxC inhibitor yielded mutants that grew only in the presence of the inhibitor. These strains had mutations in fabZ and lpxC occurring together (encoding either FabZR121L/LpxCV37G or FabZF51L/LpxCV37G). K. pneumoniae mutants having only LpxCV37G or LpxCV37A or various FabZ mutations alone were less susceptible to the LpxC inhibitor and did not require LpxC inhibition for growth. Western blotting revealed that LpxCV37G accumulated to high levels, and electron microscopy of cells harboring FabZR121L/LpxCV37G indicated an extreme accumulation of membrane in the periplasm when cells were subcultured without LpxC inhibitor. Significant accumulation of detergent-like lipid A pathway intermediates that occur downstream of LpxC (e.g., lipid X and disaccharide monophosphate [DSMP]) was also seen. Taken together, our results suggest that redirection of lipid A pathway substrate by less active FabZ variants, combined with increased activity from LpxCV37G was overdriving the lipid A pathway, necessitating LpxC chemical inhibition, since native cellular maintenance of membrane homeostasis was no longer functioning. IMPORTANCE Emergence of antibiotic resistance has prompted efforts to identify and optimize novel inhibitors of antibacterial targets such as LpxC. This enzyme catalyzes the first committed step of lipid A synthesis, which is necessary to generate lipopolysaccharide and ultimately the Gram-negative protective outer membrane. Investigation of this pathway and its interrelationship with inner membrane (phospholipid) biosynthesis or other pathways is therefore highly important to the fundamental understanding of Gram-negative bacteria and by extension to antibiotic discovery. Here we exploited the availability of a novel LpxC inhibitor to engender the generation of K. pneumoniae resistant mutants whose growth depends on chemical inhibition of LpxC. Inhibitor dependency resulted from the interaction of different resistance mutations and was based on loss of normal cellular mechanisms required to establish membrane homeostasis. This study provides new insights into the importance of this process in K. pneumoniae and how it may be linked to novel biosynthetic pathway inhibitors.

The monobactam scaffold is attractive for the development of new agents to treat infections caused by drug-resistant Gram-negative bacteria because it is stable to metallo-β-lactamases (MBLs). However, the clinically used monobactam aztreonam lacks stability to serine β-lactamases (SBLs) that are often coexpressed with MBLs. LYS228 is stable to MBLs and most SBLs. LYS228 bound purified Escherichia coli penicillin binding protein 3 (PBP3) similarly to aztreonam (derived acylation rate/equilibrium dissociation constant [k(2)/K(d)] of 367,504 s(−1) M(−1) and 409,229 s(−1) M(−1), respectively) according to stopped-flow fluorimetry. A gel-based assay showed that LYS228 bound mainly to E. coli PBP3, with weaker binding to PBP1a and PBP1b. Exposing E. coli cells to LYS228 caused filamentation consistent with impaired cell division. No single-step mutants were selected from 12 Enterobacteriaceae strains expressing different classes of β-lactamases at 8× the MIC of LYS228 (frequency

Profiling candidate therapeutics with limited cancer models during preclinical development hinders predictions of clinical efficacy and identifying factors that underlie heterogeneous patient responses for patient-selection strategies. We established ∼1,000 patient-derived tumor xenograft models (PDXs) with a diverse set of driver mutations. With these PDXs, we performed in vivo compound screens using a 1 × 1 × 1 experimental design (PDX clinical trial or PCT) to assess the population responses to 62 treatments across six indications. We demonstrate both the reproducibility and the clinical translatability of this approach by identifying associations between a genotype and drug response, and established mechanisms of resistance. In addition, our results suggest that PCTs may represent a more accurate approach than cell line models for assessing the clinical potential of some therapeutic modalities. We therefore propose that this experimental paradigm could potentially improve preclinical evaluation of treatment modalities and enhance our ability to predict clinical trial responses.

Background Microsatellite instability (MSI) is a hypermutable phenotype resulting from DNA mismatch repair deficiency and is observed in up to 10-15% of early-stage colorectal cancers (CRC). It manifests as abnormal lengthening or shortening of DNA repeats at specific genomic loci. MSI-High (MSI-H) CRC patients have been shown to respond favorably towards both chemotherapy and immunotherapy and have different prognosis than MSS patients and the FDA has approved Pembrolizumab as the first cancer therapy based on a class of biomarkers rather than a cancer type. With increasing options for targeted therapy in solid tumors, being able to combine MSI testing with other cancer biomarkers for approved therapies is beneficial. We show proof of concept of a pan-cancer gene panel using an NGS-based assay and bioinformatics workflow that enables classification of MSI status along with detection of SNVs, fusions, indels and CNVs from tumor tissue samples. Unlike the gold standard PCR-based test, our method does not require a matched normal sample, thus enabling MSI detection based on tumor tissue alone. Methods Our workflow combines whole genome library preparation, hybrid capture target enrichment, high-throughput sequencing and a proprietary analysis algorithm. We expanded the number of genomic loci to improve the sensitivity of MSI detection. The analysis algorithm was trained using DNA from pure and mixed cell lines, tumor tissue and normal samples with known MSI status to classify the molecular alterations between MSI-H and MSS genotypes from sequencing reads. The algorithm leverages repeat lengths in homopolymeric MSI loci in order to predict instability of individual loci followed by aggregation using a statistical framework to make the final call on MSI status. Results The above algorithm was evaluated on a cohort of 134 stage II and stage III CRC subjects who underwent curative intent surgery. MSI status for these samples was orthogonally tested using a PCR-based MSI Analysis System (31 positives, 103 negatives) and a dMMR system. Using a pre-determined threshold, the algorithm yielded 100% sensitivity and 100% specificity on the above cohort without using matched normal tissue. A second cohort evaluated includes 47 CRC patients that are enriched for MSI positive status by virtue of their selection criteria (BRAF positive). Very high concordance on MSI status with an orthogonal method was observed. Data demonstrating high concordance with a PCR_based MSI system will be available at the presentation. Conclusions Here we present an NGS-based assay and bioinformatics workflow with robust analytical performance for MSI detection in FFPE tissue samples without a paired normal. Citation Format: Amrita Pati, Hao Wang, Hamid Mirebrahim, Seng Saelee, Joshua Lefkowitz, Sean Chien, Ashla Singh, Fergal Casey, Vera Rapoport, Xiaoju Max Ma, John Lee, Alex Lovejoy, Daniel Klass, Hans-Peter Adams. Detecting microsatellite instability in ffpe tissue from crc subjects using next generation sequencing [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 4252.

e14530 Background: Somatic variants found in plasma cell-free DNA (cfDNA) may derive from either solid tumors or clonal hematopoiesis (CH). Little is known about how this may impact plasma-based longitudinal disease monitoring using targeted sequencing of circulating tumor DNA (ctDNA). Methods: To assess the potential impact of CH in disease monitoring, we evaluated monitoring algorithms by targeted sequencing with and without matched peripheral blood mononuclear cells (PBMC). Samples were collected from a prospective observational study, where 62 late stage lung adenocarcinoma subjects were treated with first-line chemo or chemoradiation therapy. Pre-treatment plasma cfDNA and matched PBMC were analyzed with the AVENIO ctDNA Surveillance Kit (For Research Use Only, not for use in diagnostic procedures), a sequencing panel of 198 kilobases targeting cancer genes. Median input amounts of 25 ng cfDNA and 50 ng PBMC DNA were sequenced to median deduplicated depths of 4582 and 6134, respectively. Results: A median of 120 single nucleotide variants were detected per cfDNA sample, with 93.1% of these identified in matched PBMC. Most PBMC-matched cfDNA variants were germline SNPs, with allele frequency (AF) ~ 50% or 100%. A median of 1 (range 0-5) PBMC-matched cfDNA variants per sample were detected with an AF < 10%, consistent with CH. The number of these variants was positively associated with age (p-value = 0.0039) and the most frequently mutated gene was TP53. The remaining somatic variants (i.e., in cfDNA and not PBMC) had an AF range 0.03-40.9%. These PBMC-informed variants (median of 7 per sample) were used in longitudinal monitoring in the first post-treatment plasma sample to assess early response to therapy. Association between ctDNA level and progression-free survival using the same monitoring algorithm yielded nearly identical results on somatic variants derived from filtering approaches independent of matched PBMC (HR 0.32; 95% CI 0.16 - 0.65; log-rank P = 0.0009) and the PBMC-informed method (HR 0.31; 95% CI 0.14 - 0.66; log-rank P = 0.0013). Conclusions: A targeted panel focused on solid tumors by design has limited impact from CH. For disease monitoring applications in a non-MRD setting, measuring multiple variants instead of a single variant further enables robust classifiers that can moderate the impact of variants, if any, from CH.

9050 Background: Somatic mutations derived from the expansion of clonal populations of blood cells (clonal hematopoiesis of indeterminate potential, or CHIP) may be detected in sequencing of cell-free DNA (cfDNA) samples. We evaluated the potential implications of CHIP in targeted sequencing of lung cancer plasma samples using matched peripheral blood mononuclear cells (PBMC) to identify CHIP. Methods: Samples were evaluated from OAK, a phase 3 trial of atezolizumab in locally advanced or metastatic NSCLC following failure with platinum-based therapy. 94 samples from Cycle 1 Day 1 (C1D1) plasma and matched PBMC were analyzed with the AVENIO ctDNA Surveillance Kit (For Research Use Only, not for use in diagnostic procedures), a 198-kb next-generation sequencing panel targeting cancer genes. Plasma samples from subsequent cycles of therapy (C2D1, C3D1, and C4D1) were also sequenced with the same panel. Using median input amounts of 22.8 ng cfDNA and 50 ng PBMC DNA, we obtained median deduplicated depths of 5413 and 5070, respectively. Results: In C1D1 cfDNA, a median of 120 single nucleotide variants were detected per sample, with 5.13% of variants not identified in matched PBMC (i.e., putative tumor-derived somatic variants) versus 94.87% of variants identified in matched PBMC (i.e., germline or CHIP variants). While the majority of PBMC-matched variants were SNPs with allele frequency (AF) around 50% or 100% as expected, there was a median of 1 (range 0-8) PBMC-matched cfDNA variants per sample with AF below 10%. Consistent with CHIP, the number of PBMC-matched cfDNA variants per subject below AF 10% were positively associated with age (p-value = 0.0145), and TP53 was the most frequently mutated gene. We found similar results in plasma samples from subsequent cycles. Conclusions: Plasma and PBMC sequencing analysis identified potential mutations derived from CHIP. However, 39% of cfDNA samples had zero potential CHIP mutations identified in the study, possibly due to the specific regions targeted by the AVENIO assay. While this study suggests that only a small percentage of variants detected by the AVENIO Surveillance panel in lung cancer are derived from CHIP, further studies are warranted to assess the impact and removal of these variants.

This essay takes up the challenge of Joe Cleary's provocative characterisation of John McGahern's work as naturalism that retreats into pessimistic fatalism by instead considering Rising Sun as the end-point of a career-long journey fraught with Kierkegaardean implications. Kierkegaard's concept of infinite resignation in Fear and Trembling is noted in McGahern's characters Bill Evans and Johnny Murphy, but John Quinn raises ethical problems soluble only by considering the co-existent presence of precepts from Marcus Aurelius’ Meditations. This Stoicism, it is argued, is Aurelian through the prism of O Criomhthain's An tOileanach, which McGahern greatly admired, so the characters are religiously Catholic and simultaneously philosophically Stoic in response to the harsh landscapes that order their lives. The inhabitants of this lakeside community lead messy spiritual lives that are Stoic and Kierkegaardean, with the Catholic Church continuing to be an important source of ritual. This eclectic but harmonious combination represents a hopeful new mode of life as play, exemplified by Jamesie, which is worth passing on. Rising Sun can thus be read as the end of a Kierkegaardean transition from infinite resignation to exulting in finitude through a vision of the absurd.

Introduction: Molecular profiling of tumor samples is becoming routine practice in the clinic, particularly for therapy selection. However, in some cases, tumor tissue is not available for testing. Liquid biopsy, which enables the analysis of circulating tumor DNA (ctDNA) shed from the tumor into the blood, can be used as a surrogate for conventional tissue based testing to detect somatic mutations. Furthermore, ctDNA profiling can have potential applications in tumor burden monitoring. Some technical challenges must be overcome to accurately and sensitively detect the often low amount of ctDNA present in plasma. The AVENIO ctDNA Analysis Kits (Targeted, Expanded and Surveillance Kits; Research Use Only) were developed to sensitively detect all 4 major mutation classes: single nucleotide variants, insertions/deletions, fusions, and copy number variations, using a hybrid capture target enrichment workflow, molecular barcoding, and next generation sequencing. We previously presented a comprehensive study of 370+ samples demonstrating analytical performance of the assays on the Illumina NextSeq 500. As ctDNA based analysis becomes more prevalent in the clinical research community, there is great desire for high performing and cost-effective assays that are easy to implement and available across multiple sequencing platforms. Methods: We used the commercially available AVENIO ctDNA Analysis Kits (Expanded, Target and Surveillance Kits; Research Use Only) pre-sequencing workflow to process a panel of cell line blends and plasma-derived ctDNA samples in order to compare the performance of the assays on multiple Illumina sequencing platforms: NextSeq 500, HiSeq 4000 and HiSeq 2500. Ninety samples were tested across all platforms. The samples contain SNVs at 0.5% minor allele frequency (MAF), deletions at 1% MAF, selected fusions at 1% MAF, and MET amplification at 2.3 copies. Analysis was done using the AVENIO ctDNA analysis pipeline for all sequencing runs across the sequencing platforms. Results: On the NextSeq 500, the AVENIO ctDNA Analysis Kits achieve sensitivities of >99% for 0.5% SNVs, >99% for 1% deletions, >96% for 1% fusions, and >99% for 2.3 copies of MET amplification, with 96% to >99% specificity for all mutations. Similar performance is observed across additional Illumina platforms, HighSeq 4000 and HiSeq 2500. Across all platforms, key sequencing metrics are consistent to achieve required sequencing depths, on-target rates, and uniformity. Also, it is noted that in order to achieve required depths, each platform requires different levels of sample multiplexing. We demonstrated that the AVENIO ctDNA Analysis Kits achieve high sensitivity and specificity across multiple high throughput sequencing platforms. We also will highlight the key performance differences and considerations when performing the assay across these sequencing platforms. Citation Format: Jonathan Choi, Richard Dannebaum, Ashla Singh, Rob Foley, Jorge Dinis, Cindy Choi, Bosun Min, Jingchuan Li, Liang Feng, Fergal Casey, Janet Jin. Performance of the AVENIO ctDNA assays across multiple high-throughput next-generation sequencing platforms [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3648.

3545Background: STEAM (clinical trial NCT01765582) assessed efficacy and safety of concurrent and sequential FOLFOXIRI-bevacizumab (BEV) vs FOLFOX-BEV for first-line treatment of mCRC. The AVENIO c...

The discovery of circulating tumor DNA (ctDNA) and the development of highly sensitive technologies have made the utility of liquid biopsies in clinical practice more feasible. Potential applications for liquid biopsies include early cancer detection, tumor genotyping in the absence of tissue biopsies, disease monitoring, and identification of drug resistance markers. However, there is a multitude of technical challenges to accurately detect ctDNA with high sensitivity and reproducibility. Various methods have been established by research centers and companies, each with its advantages and limitations. We have developed a sensitive NGS-based liquid biopsy assay, called the AVENIO ctDNA Analysis Kits (research use only), which includes three panels targeting biomarkers for solid tumors. The AVENIO ctDNA Analysis Kits include cfDNA extraction from up to 5ml plasma input, optimized reagents and workflow for NGS library preparation and target enrichment. It is accompanied with an intuitive software and data analysis package to easily obtain results. The assay sensitively detects 4 cancer relevant mutation classes - single nucleotide variations (SNVs), insertions/deletions, copy number variations and structural rearrangements. We conducted a study with 200+ samples of plasma-derived cfDNA, cell line blends containing relevant cancer mutations, and clinical samples, with which we demonstrate the analytical sensitivity of the three distinct AVENIO gene panels (covering 17, 77 and 197 genes). We demonstrate >95% sensitivity for SNVs at 0.5% mutant allele frequency; >95% sensitivity for 1% indels; >95% sensitivity for 1% structural variants. We also demonstrate assay robustness through multiple replicates, day-to-day, and operator-to-operator reproducibility. In conclusion, the AVENIO ctDNA Analysis Kits for solid tumors encompasses a comprehensive assay and analysis workflow aimed to provide researchers with robust, reliable, highly sensitive and ease to use liquid biopsy assays to conduct the necessary studies to demonstrate the utility of circulating biomarkers in routine clinical testing. Citation Format: Jonathan Choi, Cindy Choi, Jorge Dinis, Jingchuan Li, Sean Chien, Bosun Min, Abraham Munoz, Janet Jin, Amrita Pati, Liang Feng, Johnny Wu, Ashla Singh, Fergal Casey. Performance of a robust and sensitive liquid biopsy workflow for mutation detection in plasma [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 5677. doi:10.1158/1538-7445.AM2017-5677

The combination of liquid biopsies and ultra-sensitive next-generation sequencing (NGS) holds tremendous promise in oncology for the detection and surveillance of somatic mutations that correlate with diagnosis, prognosis, response prediction, resistance monitoring and tumor burden. We have developed a capture-based NGS workflow that provides ultra-sensitive detection of 4 mutation classes - single nucleotide variants (SNVs), insertions/deletions, copy number amplifications (CNAs) and fusions - from low input cell-free DNA isolated from plasma. Sensitivity and specificity of 2 different AVENIO ctDNA Analysis Kits (for Research Use Only) across 3 sites for 48 samples that included contrived DNA blends with known mutations validated by digital PCR and normal reference plasma samples were assessed. The AVENIO ctDNA Targeted Kit (Targeted) was designed to detect mutations in 17 genes, across 80kb, included in NCCN Guidelines for solid tumors plus additional variants relevant for therapy selection. The AVENIO ctDNA Expanded Kit (Expanded) was designed to detect mutations in 77 genes, across 200kb, associated with solid tumor including variants relevant for clinical trial research. Testing sites achieved 100% sensitivity for SNVs and fusions at 0.5% and 1% allelic frequency, respectively, from 30 ng of input DNA for both kits. Median coverage of 4,200-6,400X was greater with the Targeted kit relative to that of 2,700-3,800X with the Expanded kit. Specificity was 100% for the Targeted kit either by sample or variant. The Expanded kit had a specificity of 91.7-100% by sample and 99.7-100% by variant. At an expected 5X or 8X copy number amplification for multiple genes, both the Targeted and Expanded kits were 100% sensitive and 93.1-98.4% specific per gene. The specificity for fusion detection was 100% for both kits down to 1% mutant allele frequency. The AVENIO ctDNA Analysis Kits for plasma and NGS applications provide exquisite sensitivity and specificity for the simultaneous detection of 4 different mutation classes. Citation Format: Stephanie Yaung, Alex Lovejoy, Dan Klass, Fergal Casey, Aruna Arcot, Melissa Loyzer, William Chiu, Nabil Azhar, Sophie Beckert, Maria Lange, Sandra Siemann, Sebastian Froehler, Shelly Gunn, John F. Palma. Inter-site comparison of performance of an ultra-sensitive sequencing technology for circulating tumor DNA [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 2744. doi:10.1158/1538-7445.AM2017-2744