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. 2019 Feb;104(2):288-296.
doi: 10.3324/haematol.2018.194712. Epub 2018 Aug 9.

A novel deep targeted sequencing method for minimal residual disease monitoring in acute myeloid leukemia

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A novel deep targeted sequencing method for minimal residual disease monitoring in acute myeloid leukemia

Esther Onecha et al. Haematologica. 2019 Feb.

Abstract

A high proportion of patients with acute myeloid leukemia who achieve minimal residual disease negative status ultimately relapse because a fraction of pathological clones remains undetected by standard methods. We designed and validated a high-throughput sequencing method for minimal residual disease assessment of cell clonotypes with mutations of NPM1, IDH1/2 and/or FLT3-single nucleotide variants. For clinical validation, 106 follow-up samples from 63 patients in complete remission were studied by sequencing, evaluating the level of mutations detected at diagnosis. The predictive value of minimal residual disease status by sequencing, multiparameter flow cytometry, or quantitative polymerase chain reaction analysis was determined by survival analysis. The sequencing method achieved a sensitivity of 10-4 for single nucleotide variants and 10-5 for insertions/deletions and could be used in acute myeloid leukemia patients who carry any mutation (86% in our diagnostic data set). Sequencing-determined minimal residual disease positive status was associated with lower disease-free survival (hazard ratio 3.4, P=0.005) and lower overall survival (hazard ratio 4.2, P<0.001). Multivariate analysis showed that minimal residual disease positive status determined by sequencing was an independent factor associated with risk of death (hazard ratio 4.54, P=0.005) and the only independent factor conferring risk of relapse (hazard ratio 3.76, P=0.012). This sequencing-based method simplifies and standardizes minimal residual disease evaluation, with high applicability in acute myeloid leukemia. It is also an improvement upon flow cytometry- and quantitative polymerase chain reaction-based prediction of outcomes of patients with acute myeloid leukemia and could be incorporated in clinical settings and clinical trials.

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Figures

Figure 1.
Figure 1.
Workflow of the next-geneartion sequencing – minimal residual disease method. DNA amplification, library preparation and sequencing experimental workflow. Genomic DNA (gDNA) is amplified by quantitative (q) polymerase chain reaction (PCR) using specific primers. Libraries are prepared in four steps: end repair, adaptor ligation, size selection, and PCR amplification. The libraries are then sequenced. A customized bioinformatic pipeline analyzes the sequences obtained. The results are expressed as a ratio of mutated sequences (mut) among wild-type (wt) sequences.
Figure 2.
Figure 2.
Calibration curve of minimal residual disease in serial dilutions. (A,B) Ten-fold dilution curves for the assessment of the sensitivity of next-generation sequencing (NGS) in (A) insertions-deletions (InDel), using OCI-AML3 gDNA with 50% NPM1 type A mutation (R2 = 0.98); and (B) single nucleotide variabts (SNV), using OCI-AML3 gDNA with 50% mutated DNMT3A (R2 = 0.98), and gDNA with 50% mutated IDH1 or IDH2 from a commercial standard (R2 = 0.91 and R2 = 0.98, respectively). (C,D) The same 10-fold dilution curves for the assessment of sensitivity of digital polymerase chain reaction (dPCR) in (C) InDel (R2 = 0.98); and (D) SNV (R2 = 0.91 for IDH1 and R2 = 0.98 for IDH2). The vertical red bars indicate the limit of quantification (LOQ) according to the sample. Clone frequency is expressed as target concentration as mutated copies/μL in wild-type copies/μL. Negative controls are included in the calibration curves and had levels below the corresponding LOQ values.
Figure 3.
Figure 3.
Analysis of overall survival and disease-free survival in patients with acute myeloid leukemia stratified according to minimal residual disease levels determined by sequencing. Analysis of overall survival for (A) the induction data set, (C) the consolidation data set, and (C) both together. Analysis of disease-free survival for (B) the induction data set, (D) the consolidation data set, and (F) both together. The cutoff used for overall and disease-free survival was 0.001 at the post–induction check-point (n=35), 0.00026 at the post-consolidation check–point (n=28) and 0.00035 for both check-points (all data set) (n=63). The numbers of censored patients with respect to the stratified groups and the numbers at risk are indicated. Statistically significant values: *P<0.05, **P<0.01.
Figure 4.
Figure 4.
Analysis of overall survival and disease-free survival in patients with acute myeloid leukemia stratified according to minimal residual disease levels determined by conventional methods. Kaplan-Meier plots of (A) overall survival and (B) disease-free survival according to minimal residual disease (MRD) assessment by multiparametric flow cytometry (MRC) and (C) overall survival and (D) disease-free survival according to MRD assessment by quantitative polymerase chain reaction (qPCR) analysis. The numbers of censored patients with respect to each stratified group and numbers at risk are indicated. Statistically significant values: *P<0.05, **P<0.01.

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