1142P Improved duplex sequencing-based method suitable for detection of hypermutator phenotype in FFPE-derived tumor samples

Abstract Duplex sequencing is currently the most reliable method to identify ultra-low frequency DNA variants by grouping sequence reads derived from the same DNA molecule into families with information on the forward and reverse strand. However, only a small proportion of reads are assembled into duplex consensus sequences (DCS), and reads with potentially valuable information are discarded at different steps of the bioinformatics pipeline, especially reads without a family. We developed a bioinformatics toolset that analyses the tag and family composition with the purpose to understand data loss and implement modifications to maximize the data output for the variant calling. Specifically, our tools show that tags contain polymerase chain reaction and sequencing errors that contribute to data loss and lower DCS yields. Our tools also identified chimeras, which likely reflect barcode collisions. Finally, we also developed a tool that re-examines variant calls from raw reads and provides different summary data that categorizes the confidence level of a variant call by a tier-based system. With this tool, we can include reads without a family and check the reliability of the call, that increases substantially the sequencing depth for variant calling, a particular important advantage for low-input samples or low-coverage regions.

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Duplex Sequencing with Patient-Specific Hybrid Capture Panels Reveals Ultra-Low Frequency Measurable Residual Disease in Pediatric Acute Myeloid Leukemia

Blood ◽

10.1182/blood-2020-143062 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 31-32

Author(s):

Jacob Higgins ◽

Fang Yin Lo ◽

Michael J. Hipp ◽

Charles C. Valentine ◽

Lindsey N. Williams ◽

...

Keyword(s):

Myeloid Leukemia ◽

Residual Disease ◽

Limit Of Detection ◽

Low Frequency ◽

Patient Specific ◽

Pediatric Acute Myeloid Leukemia ◽

Hybrid Capture ◽

Pediatric Aml ◽

Duplex Sequencing ◽

Measurable Residual Disease

Sensitive and specific detection of measurable residual disease (MRD) after treatment in pediatric acute myeloid leukemia (AML) is prognostic of relapse and is important for clinical decision making. Mutation-based methods are increasingly being used, but are hampered by the limited number of common driver gene mutations to target as clone markers. Additional targets would greatly increase MRD detection power. However, even in cases with many AML-defining mutations, it is the limited accuracy of current molecular methods which establishes the lower bounds of sensitivity. Here we describe an ultrasensitive approach for disease monitoring with personalized hybrid capture panels targeting hundreds of somatic mutations identified by whole genome sequencing (WGS), and using extremely accurate Duplex Sequencing (DS) in longitudinal samples. In a pilot cohort of 13 patients we demonstrate detection sensitivities several orders of magnitude beyond currently available single locus testing or less accurate sequencing. With multi-target panels, overall power for MRD detection is cumulative across sites. For example, if a patient has MRD at a true frequency of 1/30,000, sequencing a single mutant site to 10,000x molecular depth would be unlikely to detect MRD. However, sequencing 10 sites each to 10,000x would effectively total 100,000x informative site depth, increasing power to >95%. However, standard sequencing assays are insufficiently accurate to achieve this theoretical limit of detection (LOD). DS enables accurate detection of individual variants to <10-5 with an error rate <10-7 and, thus, can achieve MRD sensitivities below one-in-one-million. Marrow aspirates were collected from 13 uniformly treated pediatric AML patients at time of diagnosis (TOD), during treatment (end of induction, EOI), in remission (end of therapy, EOT), and at relapse. 9/13 patients relapsed. DNA from TOD was analyzed by WGS. Germline variants were excluded and somatic single nucleotide variants (SNVs) were targeted by a custom probe panel designed for each patient. An average of 170 SNVs were targeted per patient (range 53-200). More than 90% of the SNVs were noncoding. Longitudinal samples were then analyzed with DS, which compares sequences from both strands of each DNA molecule to eliminate technical noise and reveal biological mutation signal with extreme accuracy and sensitivity. A median of 82% of WGS SNVs were validated by DS in the TOD DNA, and the vast majority of those were also present at relapse. Relapsers had more SNVs at diagnosis than non-relapsers. EOT samples were sequenced to an average Duplex molecular depth of 29,400x, with a maximum of 61,283x. The figure below shows time course plots tracking SNVs at diagnosis, EOT and relapse for 2 patients. Among mutations validated in TOD samples, a median of only 8 (5%) were detected per EOT sample (range 0-66 mutations). MRD was detected in 8/9 relapsers. Targeting 1 or even 10 SNVs would therefore have missed MRD in the majority of these patients. Among relapsers, median EOT SNV VAF was 0.069%. The lowest single VAF detected per EOT sample ranged from 0.036% to 0.002%. The presence of an SNV at diagnosis and relapse implies that it must truly be present at EOT, whether or not it is detected. Therefore, if a small minority of leukemic mutations are detected at EOT, the true overall MRD frequency is much lower than the LOD at any single site. In the only relapser where MRD was not detected, targeted SNVs were present at diagnosis and relapse, so additional sequencing depth at EOT would eventually reveal ultra-low frequency mutations. Among patients that did not relapse by the end of the study, median VAF at EOI (the latest time point DNA available) was 0.0258%. Therefore, non-relapsers have a lower median VAF at EOI than relapsers do even later at EOT, potentially indicating very early on that treatment is more successful. This study shows excellent performance of DS-based assays for detecting MRD with patient-specific panels. We have demonstrated that among large panels of validated somatic SNVs present at time of diagnosis, a median of 5% are identified at EOT in eventual relapsers. DS detected MRD in 8/9 patients, and at a median VAF well below the limit of detection of any other sequencing technology. Comprehensive personalized hybrid selection panels coupled with DS represents a powerful option for MRD monitoring in pediatric AML and potentially other cancers. Figure Disclosures Higgins: TwinStrand Biosciences: Current Employment. Lo:TwinStrand Biosciences: Current Employment. Hipp:TwinStrand Biosciences: Current Employment. Valentine:TwinStrand Biosciences: Current Employment. Williams:TwinStrand Biosciences: Current Employment. Radich:TwinStrand Biosciences: Research Funding. Salk:TwinStrand Biosciences: Current Employment.

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Somatic mutation landscapes at single-molecule resolution

10.21203/rs.3.pex-1298/v1 ◽

2021 ◽

Author(s):

Stefanie V. Lensing ◽

Peter Ellis ◽

Federico Abascal ◽

Iñigo Martincorena ◽

Robert J. Osborne

Keyword(s):

Single Molecule ◽

Single Cells ◽

Error Rates ◽

Dna Molecules ◽

Base Pairs ◽

Single Dna Molecules ◽

Sequencing Library ◽

Somatic Mutagenesis ◽

Qpcr Quantification ◽

Duplex Sequencing

Abstract Somatic mutations drive cancer development and may contribute to ageing and other diseases. Yet, the difficulty of detecting mutations present only in single cells or small clones has limited our knowledge of somatic mutagenesis to a minority of tissues. To overcome these limitations, we introduce nanorate sequencing (NanoSeq), a new duplex sequencing protocol with error rates <5 errors per billion base pairs in single DNA molecules from cell populations. The version of the protocol described here uses clean genome fragmentation with a restriction enzyme to prevent end-repair-associated errors and ddBTPs/dATPs during A-tailing to prevent nick extension. Both changes reduce the error rate of standard duplex sequencing protocols by preventing the fixation of DNA damage into both strands of DNA molecules during library preparation. We also use qPCR quantification of the library prior to amplification to optimise the complexity of the sequencing library given the desired sequencing coverage, maximising duplex coverage. The sample preparation protocol takes between 1 and 2 days, depending on the number of samples processed. The bioinformatic protocol is described in:https://github.com/cancerit/NanoSeqhttps://github.com/fa8sanger/NanoSeq_Paper_Code

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Abstract 3041: Duplex Sequencing detects cancer-associated mutations arising during normal aging: Clonal evolution over a century of human lifetime

10.1158/1538-7445.am2017-3041 ◽

2017 ◽

Cited By ~ 1

Author(s):

Jesse J. Salk ◽

Elisabeth Maritschnegg ◽

Paul Speiser ◽

Robert Zeillinger ◽

Rosana Risques ◽

...

Keyword(s):

Clonal Evolution ◽

Normal Aging ◽

Duplex Sequencing

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Abstract A29: Detection of ultra-rare mutations during breast stem cell tumor progression by Duplex Sequencing

10.1158/1557-3125.advbc15-a29 ◽

2016 ◽

Author(s):

Eun Hyun Ahn ◽

Kensen Hirohata ◽

Seung Hyuk Lee ◽

Joon Yup Kim ◽

Brendan F. Kohrn ◽

...

Keyword(s):

Stem Cell ◽

Tumor Progression ◽

Cell Tumor ◽

Rare Mutations ◽

Breast Stem Cell ◽

Duplex Sequencing

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Duplex Sequencing Identifies Low Level ABL1 Kinase Domain Mutations in Untreated Philadelphia Chromosome-Positive Acute Lymphoblastic Leukemia

Clinical Lymphoma Myeloma & Leukemia ◽

10.1016/j.clml.2019.07.025 ◽

2019 ◽

Vol 19 ◽

pp. S186

Author(s):

Nicholas Short ◽

Hagop Kantarjian ◽

Koji Sasaki ◽

Rashmi Kanagal-Shamanna ◽

Farhad Ravandi ◽

...

Keyword(s):

Acute Lymphoblastic Leukemia ◽

Lymphoblastic Leukemia ◽

Philadelphia Chromosome ◽

Kinase Domain ◽

Low Level ◽

Kinase Domain Mutations ◽

Duplex Sequencing ◽

Philadelphia Chromosome Positive

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Family reunion via error correction: An efficient analysis of duplex sequencing data

10.1101/469106 ◽

2018 ◽

Cited By ~ 1

Author(s):

Nicholas Stoler ◽

Barbara Arbeithuber ◽

Gundula Povysil ◽

Monika Heinzl ◽

Renato Salazar ◽

...

Keyword(s):

Error Correction ◽

Dynamic Range ◽

Pcr Amplification ◽

Cost Effective ◽

Sequencing Data ◽

Nucleotide Substitutions ◽

Low Frequencies ◽

Family Reunion ◽

Sequencing Errors ◽

Duplex Sequencing

AbstractDuplex sequencing is the most accurate approach for identification of sequence variants present at very low frequencies. Its power comes from pooling together multiple descendants of both strands of original DNA molecules, which allows distinguishing true nucleotide substitutions from PCR amplification and sequencing artifacts. This strategy comes at a cost—sequencing the same molecule multiple times increases dynamic range but significantly diminishes coverage, making whole genome duplex sequencing prohibitively expensive. Furthermore, every duplex experiment produces a substantial proportion of singleton reads that cannot be used in the analysis and are, technically, thrown away. In this paper we demonstrate that a significant fraction of these reads contains PCR or sequencing errors within duplex tags. Correction of such errors allows “reuniting” these reads with their respective families increasing the output of the method and making it more cost effective. Additionally, we combine error correction strategy with a number of algorithmic improvements in a new version of the duplex analysis software, Du Novo 2.0, readily available through Galaxy, Bioconda, and as the source code.

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High Interpatient Variability in Molecular MRD Response to Consolidation Chemotherapy in Acute Myeloid Leukemia

Blood ◽

10.1182/blood-2019-122890 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 1424-1424

Author(s):

Tracy Murphy ◽

Jinfeng Zou ◽

Ting Ting Wang ◽

Yangqiao Zheng ◽

Zhen Zhao ◽

...

Keyword(s):

Board Of Directors ◽

Research Funding ◽

Interpatient Variability ◽

Newly Diagnosed ◽

Consolidation Chemotherapy ◽

Advisory Committees ◽

Hybrid Capture ◽

Log Reduction ◽

Definitive Therapy ◽

Duplex Sequencing

Introduction: Although induction chemotherapy results in a complete remission (CR) in ~70% of newly diagnosed AML patients, post-remission therapies are needed to eliminate minimal residual disease (MRD) and prevent relapse. Consolidation chemotherapy, either as definitive therapy or bridge to bone marrow transplantation (BMT), is currently the most common form of post-remission therapy. Yet, our understanding of its impact on MRD remains limited. In this study, we investigated the effects of consolidation chemotherapy on molecular MRD (mMRD) burden using ultra-deep next generation sequencing (NGS) and correlated treatment response with disease characteristics and survival outcomes in AML patients. Patients and Methods: 91 newly diagnosed AML patients who achieved CR following standard induction chemotherapy were evaluated. Targeted conventional NGS using a 54-gene panel was performed on whole blood (PB) or bone marrow samples collected at diagnosis. PB samples were collected during remission at two consecutive time points (T1 and T2), before and after 1 (n=79) or 2 (n=12) cycles of consolidation chemotherapy, for each patient. To detect mMRD, we used a custom 37-gene hybrid-capture panel and error-corrected NGS based on the duplex sequencing approach with a variant allele frequency (VAF) detection limit of ~1x10-4. For 10 patients, we also performed duplex sequencing analysis on their relapsed samples. Results: NGS of the diagnostic samples identified a total of 298 putative oncogenic mutations in 92% (n=84) of the 91 patients. Ninety percent of these mutations (n=267) were trackable by the custom hybrid-capture panel. Duplex sequencing detected persistence of 56% (n=149) of the trackable mutations in T1 samples; 34% (n=50) of which were clonal hematopoiesis-associated DTA mutations (those involving DNMT3A, TET2, or ASXL1), and the remaining 66% (n=99) were non-DTA mutations. Analysis of T2 samples showed that consolidation chemotherapy reduced the VAF of non-DTA mutations by a median of 73% and cleared 27% (n=27) of them at T2. In contrast, the burden of DTA mutations increased by 0.5% (P < 0.0001 by Mann-Whitney test), and only 2% (n=1) of the mutations was cleared (P = 0.0001 by Fisher's exact test). These findings are consistent with prior studies demonstrating that non-DTA mutations are more reliable markers of leukemic burden than DTA mutations. To study the impact of consolidation chemotherapy at the level of individual patients, the mean VAF of all persistent non-DTA mutations was calculated for each sample and used as a composite measure of mMRD burden (henceforth referred to as "cmMRD"). Analysis of the 10 patients with relapsed samples showed that cmMRD levels tracked well with achievement of remission and disease progression (Fig. 1). In the subset of patients with persistent non-DTA mutations at T1 (n=61), consolidation chemotherapy decreased cmMRD levels by a median of 36% at T2. However, we observed high interpatient variability (Fig. 2); 36% (n=22) of the patients experienced an increase in cmMRD burden after consolidation chemotherapy, and 36% (n=22) had less than a 1 log reduction. Only 28% (n=17) of the patients achieved a log reduction of greater than 1. The likelihood and magnitude of cmMRD response were significantly associated with cytogenetic risk (P = 0.026 by 3x3 Chi-square test; Fig. 3). The proportion of patients with favorable, intermediate, and poor-risk cytogenetics who experienced cmMRD expansion was 17%, 27%, and 71%, respectively. Consistent with these findings, a suboptimal response (defined as cmMRD ratio [T2/T1] > 0.4) was associated with inferior overall survival (HR = 3.29, P = 0.007 by log-rank test; Fig. 4). Conclusions: Our analysis showed that mMRD response to consolidation chemotherapy was highly variable among patients. Although consolidation chemotherapy was effective in deepening the remission for a subset of patients, it failed to lower MRD levels for a substantial proportion of patients, especially those with poor risk cytogenetics. These findings challenge the practice of using consolidation chemotherapy to achieve a deeper remission prior to BMT for high-risk patients and indicate that the opposite outcome may occur instead. NGS-based monitoring of mMRD can potentially be used to distinguish between patients who can remain on consolidation chemotherapy as definitive therapy and those who require a switch in post-remission therapy. Disclosures Gupta: Sierra Oncology: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Incyte: Honoraria, Research Funding. Maze:Pfizer Inc: Consultancy; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees. McNamara:Novartis Pharmaceutical Canada Inc.: Consultancy. Minden:Trillium Therapetuics: Other: licensing agreement. Schimmer:Medivir Pharmaceuticals: Research Funding; Jazz Pharmaceuticals: Consultancy; Novartis Pharmaceuticals: Consultancy; Otsuka Pharmaceuticals: Consultancy. Schuh:Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Jazz: Honoraria, Membership on an entity's Board of Directors or advisory committees; Agios: Honoraria; Astellas: Honoraria, Membership on an entity's Board of Directors or advisory committees; Teva Canada Innovation: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Yee:Novartis, Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Astellas, Celgene, Otsuka, Shire, Takeda: Membership on an entity's Board of Directors or advisory committees; Agensys, Astex, Hoffman La Roche, MedImmune, Merck, Millenium, Roche/Genentech: Research Funding. Bratman:SVB: Other: is co-inventor of a patent relating to circulating tumor DNA detection technology, which has been licensed to Roche Molecular Diagnostics.. Chan:Agios: Honoraria; AbbVie Pharmaceuticals: Research Funding; Celgene: Honoraria, Research Funding.

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Abstract 4649: Duplex Sequencing detects rare subclonal variants that mark early carcinogenesis and preneoplastic clonal evolution

10.1158/1538-7445.sabcs18-4649 ◽

2019 ◽

Author(s):

Charles C. Valentine ◽

Mark Fielden ◽

Robert Young ◽

Jake Higgins ◽

Lindsey Williams ◽

...

Keyword(s):

Clonal Evolution ◽

Duplex Sequencing ◽

Early Carcinogenesis

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Ultrasensitive Duplex Sequencing of Pretreatment ABL1 Kinase Domain Mutations in Patients with Newly Diagnosed Philadelphia Chromosome-Positive Acute Lymphoblastic Leukemia

Blood ◽

10.1182/blood-2018-99-115369 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 1548-1548 ◽

Cited By ~ 2

Author(s):

Nicholas J Short ◽

Hagop M. Kantarjian ◽

Koji Sasaki ◽

Farhad Ravandi ◽

Jorge E. Cortes ◽

...

Keyword(s):

Acute Lymphoblastic Leukemia ◽

Research Funding ◽

Lymphoblastic Leukemia ◽

Philadelphia Chromosome ◽

Kinase Domain ◽

Newly Diagnosed ◽

Resistance Mutations ◽

Genetics Research ◽

Duplex Sequencing ◽

Philadelphia Chromosome Positive

Abstract Background: Kinase domain (KD) mutations in ABL1 are the dominant mechanism of relapse in patients (pts) with Philadelphia chromosome-positive acute lymphoblastic leukemia (Ph+ ALL). Previous studies in Ph+ ALL have suggested that some pts harbor subclonal T315I mutations prior to tyrosine kinase inhibitor (TKI) treatment. However, nearly all reports have relied upon inherently error prone RT-PCR to generate template cDNA prior to mutation analysis. We hypothesized that conventional assays might over-estimate the incidence of pre-existing resistance mutations, and that improved sequencing accuracy might yield important information for risk stratification and TKI selection. Methods: Duplex sequencing (DS) is a molecular tagging method that improves the accuracy of conventional next-generation sequencing by more than 10,000-fold, by comparing the nucleotide sequences of each strand of double-stranded molecules. ABL1 DS was performed on genomic DNA from 64 pts with newly diagnosed Ph+ ALL treated with hyper-CVAD plus a TKI. DS of exons 4-10 of ABL1 was performed to an average molecular depth of >10,000x. Among pts who relapsed, using RNA extracted from relapse samples, the KD (codons 221 through 500) of the BCR-ABL1 fusion transcript was sequenced by the Sanger method using a nested PCR approach, with a detection limit of 10-20%. Results: The median age of the cohort was 54 years (range, 20-80 years). The TKI used was imatinib in 5 pts, dasatinib in 38 pts, and ponatinib in 21 pts. All pts achieved complete remission, and 12 pts (19%) underwent allogeneic stem cell transplantation in first remission. A total of 115 pretreatment ABL1 KD mutations were detected among 47 pts (73%). The median number of pretreatment ABL1 KD mutations was 2 (range, 0-6 mutations). The median variant allelic frequency (VAF) of the detected somatic mutations was 0.008% (range, 0.004%-0.649%). Five mutations (4%) and 40 mutations (35%) were present at a VAF ≥0.1% and ≥0.01%, respectively. Eleven mutations known to confer resistance to at least one TKI were detected in 7 pts (11%), and included: F317L in 4 pts, E225K in 2 pts, and E225V, L384M, M244V, Q252H and T315I in 1 pt each. Five mutations were detected in ≥1 pretreatment sample (F317L in 4 pts, M244V in 3 pts, and E255K, E459K and V355V in 2 pts each). Of these 7 pts with pretreatment resistance mutations, 5 pts received a TKI known not to be sensitive to the mutation(s); 2 pts who received ponatinib had mutations at least intermediately sensitive to ponatinib (1 pt with F317L and 1 pt with both E255K and M244V mutations). With a median duration of follow-up of 54 months (range, 1-124 months), 18 pts have relapsed. None of the 7 pts with known pretreatment resistance mutations relapsed. There was no difference in the number of pretreatment mutations between pts who relapsed and those who did not (median mutations: 1 [range, 0-4] and 2 [range, 0-6], respectively; P=0.26). Of the 18 pts who relapsed, 14 underwent Sanger sequencing for ABL1 KD mutations at the time of relapse. Clonal resistance mutations were detected at relapse in 9 pts (64% of sequenced samples): T315I in 6 pts, and F317I, V229L and V338G in 1 pt each (all in pts treated with dasatinib, except V338G in pt on imatinib). Relapse mutations were not observed in pretreatment samples in any of the pts. Conclusions: DS identified very low level pretreatment ABL1 KD mutations in a majority of pts with newly diagnosed Ph+ ALL but these appear inconsequential. Ninety percent of mutations identified have not been described as resistance mutations, suggesting that they may be either synonymous or functionally neutral amino acid changes resulting from normal aging. There was no apparent association of these mutations and risk of relapse, even in the minority of cases in which known resistance mutations were detected at baseline. These data suggest that pretreatment testing for ABL1 KD mutations in Ph+ ALL is unlikely to affect treatment decisions. Disclosures Short: Takeda Oncology: Consultancy. Sasaki:Otsuka Pharmaceutical: Honoraria. Ravandi:Jazz: Honoraria; Orsenix: Honoraria; Orsenix: Honoraria; Seattle Genetics: Research Funding; Sunesis: Honoraria; Xencor: Research Funding; Bristol-Myers Squibb: Research Funding; Amgen: Honoraria, Research Funding, Speakers Bureau; Abbvie: Research Funding; Astellas Pharmaceuticals: Consultancy, Honoraria; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; Astellas Pharmaceuticals: Consultancy, Honoraria; Amgen: Honoraria, Research Funding, Speakers Bureau; Macrogenix: Honoraria, Research Funding; Jazz: Honoraria; Abbvie: Research Funding; Xencor: Research Funding; Macrogenix: Honoraria, Research Funding; Sunesis: Honoraria. Cortes:Pfizer: Consultancy, Research Funding; Astellas Pharma: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Arog: Research Funding. Konopleva:Stemline Therapeutics: Research Funding. Radich:TwinStrand Biosciences: Research Funding. Jabbour:Takeda: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Novartis: Research Funding; Pfizer: Consultancy, Research Funding; Abbvie: Research Funding.

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