Quantifying ultra-rare pre-leukemic clones via targeted error-corrected sequencing.
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ABSTRACT:
SUBMITTER: Young AL
PROVIDER: S-EPMC4497921 | biostudies-literature | 2015 Jul
REPOSITORIES: biostudies-literature
Publications
Quantifying ultra-rare pre-leukemic clones via targeted error-corrected sequencing.
Young A L AL Wong T N TN Hughes A E O AE Heath S E SE Ley T J TJ Link D C DC Druley T E TE
Leukemia 20150203 7
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Project description:BackgroundPediatric leukemias have a diverse genomic landscape associated with complex structural variants, including gene fusions, insertions and deletions, and single nucleotide variants. Routine karyotype and fluorescence in situ hybridization (FISH) techniques lack sensitivity for smaller genomic alternations. Next-generation sequencing (NGS) assays are being increasingly utilized for assessment of these various lesions. However, standard NGS lacks quantitative sensitivity for minimal residual disease (MRD) surveillance due to an inherently high error rate.MethodsPrimary bone marrow samples from pediatric leukemia (n = 32) and adult leukemia subjects (n = 5), cell line MV4-11, and an umbilical cord sample were utilized for this study. Samples were sequenced using molecular barcoding with targeted DNA and RNA library enrichment techniques based on anchored multiplexed PCR (AMP®) technology, amplicon based error-corrected sequencing (ECS) or a human cancer transcriptome assay. Computational analyses were performed to quantitatively assess limit of detection (LOD) for various DNA and RNA lesions, which could be systematically used for MRD assays.ResultsMatched leukemia patient samples were analyzed at three time points; diagnosis, end of induction (EOI), and relapse. Similar to flow cytometry for ALL MRD, the LOD for point mutations by these sequencing strategies was ≥0.001. For DNA structural variants, FLT3 internal tandem duplication (ITD) positive cell line and patient samples showed a LOD of ≥0.001 in addition to previously unknown copy number losses in leukemia genes. ECS in RNA identified multiple novel gene fusions, including a SPANT-ABL gene fusion in an ALL patient, which could have been used to alter therapy. Collectively, ECS for RNA demonstrated a quantitative and complex landscape of RNA molecules with 12% of the molecules representing gene fusions, 12% exon duplications, 8% exon deletions, and 68% with retained introns. Droplet digital PCR validation of ECS-RNA confirmed results to single mRNA molecule quantities.ConclusionsCollectively, these assays enable a highly sensitive, comprehensive, and simultaneous analysis of various clonal leukemic mutations, which can be tracked across disease states (diagnosis, EOI, and relapse) with a high degree of sensitivity. The approaches and results presented here highlight the ability to use NGS for MRD tracking.
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Project description:Error-corrected sequences (ECSs) that utilize double-stranded DNA sequences are useful in detecting mutagen-induced mutations. However, relatively higher frequencies of G:C > T:A (1 × 10-7 bp) and G:C > C:G (2 × 10-7 bp) errors decrease the accuracy of detection of rare G:C mutations (approximately 10-7 bp). Oxidized guanines in single-strand (SS) overhangs generated after shearing could serve as the source of these errors. To remove these errors, we first computationally discarded up to 20 read bases corresponding to the ends of the DNA fragments. Error frequencies decreased proportionately with trimming length; however, the results indicated that they were not sufficiently removed. To efficiently remove SS overhangs, we evaluated three mechanistically distinct SS-specific nucleases (S1 Nuclease, mung bean nuclease, and RecJf exonuclease) and found that they were more efficient than computational trimming. Consequently, we established Jade-Seq™, an ECS protocol with S1 Nuclease treatment, which reduced G:C > T:A and G:C > C:G errors to 0.50 × 10-7 bp and 0.12 × 10-7 bp, respectively. This was probably because S1 Nuclease removed SS regions, such as gaps and nicks, depending on its wide substrate specificity. Subsequently, we evaluated the mutation-detection sensitivity of Jade-Seq™ using DNA samples from TA100 cells exposed to 3-methylcholanthrene and 7,12-dimethylbenz[a]anthracene, which contained the rare G:C > T:A mutation (i.e., 2 × 10-7 bp). Fold changes of G:C > T:A compared to the vehicle control were 1.2- and 1.3-times higher than those of samples without S1 Nuclease treatment, respectively. These findings indicate the potential of Jade-Seq™ for detecting rare mutations and determining the mutagenicity of environmental mutagens.
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Project description:BackgroundCirculating free DNA sequencing (cfDNA-Seq) can portray cancer genome landscapes, but highly sensitive and specific technologies are necessary to accurately detect mutations with often low variant frequencies.MethodsWe developed a customizable hybrid-capture cfDNA-Seq technology using off-the-shelf molecular barcodes and a novel duplex DNA molecule identification tool for enhanced error correction.ResultsModeling based on cfDNA yields from 58 patients showed that this technology, requiring 25 ng of cfDNA, could be applied to >95% of patients with metastatic colorectal cancer (mCRC). cfDNA-Seq of a 32-gene, 163.3-kbp target region detected 100% of single-nucleotide variants, with 0.15% variant frequency in spike-in experiments. Molecular barcode error correction reduced false-positive mutation calls by 97.5%. In 28 consecutively analyzed patients with mCRC, 80 out of 91 mutations previously detected by tumor tissue sequencing were called in the cfDNA. Call rates were similar for point mutations and indels. cfDNA-Seq identified typical mCRC driver mutations in patients in whom biopsy sequencing had failed or did not include key mCRC driver genes. Mutations only called in cfDNA but undetectable in matched biopsies included a subclonal resistance driver mutation to anti-EGFR antibodies in KRAS, parallel evolution of multiple PIK3CA mutations in 2 cases, and TP53 mutations originating from clonal hematopoiesis. Furthermore, cfDNA-Seq off-target read analysis allowed simultaneous genome-wide copy number profile reconstruction in 20 of 28 cases. Copy number profiles were validated by low-coverage whole-genome sequencing.ConclusionsThis error-corrected, ultradeep cfDNA-Seq technology with a customizable target region and publicly available bioinformatics tools enables broad insights into cancer genomes and evolution.Clinicaltrialsgov identifierNCT02112357.
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