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Quantitative Analysis of MLL Fusion Transcripts By Droplet Digital PCR to Monitor Minimal Residual Disease in MLL-Rearranged Acute Myeloid Leukemia

微小残留病 髓系白血病 急性早幼粒细胞白血病 白血病 融合基因 融合转录本 净现值1 数字聚合酶链反应 癌症研究 医学 生物 肿瘤科 免疫学 聚合酶链反应 基因 遗传学 维甲酸 核型 染色体
作者
Sadia Afrin,Christine Zhang,Claus Meyer,Mellissa Maybury,Thy Pham,Nicola C. Venn,Toby N. Trahair,Rosemary Sutton,Rolf Marschalek,J. Lynn Fink,Andrew S. Moore
出处
期刊:Blood [American Society of Hematology]
卷期号:132 (Supplement 1): 2746-2746
标识
DOI:10.1182/blood-2018-99-117761
摘要

Abstract Rearrangements of the mixed lineage leukemia gene (MLL, re-named KMT2A) result in aggressive leukemia. Current risk stratification of MLL-rearranged (MLL-r) leukemia is directed by the fusion partner gene and, increasingly, by minimal residual disease (MRD) assessment after induction therapy. The clinical significance of quantifying fusion transcript levels in leukemia patients is firmly established in chronic myeloid leukemia and acute promyelocytic leukemia but is less well studied in MLL-r patients. Real-time quantitative PCR (RQ-PCR) is the standardized assay for molecular MRD monitoring in patients with MLL-rearranged leukemia. However, this method is less precise when few leukemic cells are present, thus limiting its application for highly sensitive MRD monitoring. Droplet digital PCR (ddPCR) allows for absolute quantification of fusion transcripts when multiple copies of fusion transcripts are present per cell. Therefore, we aimed to evaluate whether determining MLL fusion transcript levels by ddPCR could improve the sensitivity of MRD monitoring in MLL-r leukemia. A total of 44 diagnostic and follow-up samples obtained from paediatric MLL-r leukemia patients (26 ALL, 18 AML) were subjected to targeted next-generation sequencing to obtain patient-specific fusion sequences. MLL fusion transcripts were quantified by ddPCR in a total of 17 samples obtained from 4 paediatric AML patients with MLL fusions involving MLLT3 (n = 3) and MLLT10 (n = 1). Fusion-specific probe assays were designed from each of the patient specific fusion sequences for MRD assessment by ddPCR. To determine the detection limit of this method in quantifying MLL fusion transcripts, two MLL-r AML cell lines (MV4-11 and THP-1), and one MLL-wt cell line (Kasumi-1) were used. MLL fusion transcript level of detection of ddPCR was determined by serially diluting MLL-r cDNA into MLL-wt cDNA (Kasumi-1). Using 20ng of MLL-r cDNA in 200ng diluent as the highest concentration, a 10-fold dilution series was performed to make concentrations ranging from 10−2 to 10−7. Each ddPCR reaction mixture contained 11ul of cDNA mix as template with 1X Supermix no dUTP (Bio-Rad), 500 nM of both F/R primers and 250 nM of 5'-FAM labelled probe (IDT). Droplets were generated using a QX200 Droplet Generator (Bio-Rad). A general thermal cycler protocol with annealing at 61°C for 1 minute was performed and positive fluorescence droplets were read using QX200 Droplet Reader (Bio-Rad). MRD of patient samples, derived from ddPCR, was then compared to MRD derived from DNA-based RQ-PCR, following the guidelines established by the EuroMRD group. Our ddPCR method showed high reliability and sensitivity, with the detection limit determined to be 10-5 for a cell line with low MLL fusion transcript expression (THP-1), and 10-6 for a cell line with high MLL fusion transcript expression (MV4-11). Comparison of results obtained by RQ- PCR and ddPCR in a total of 17 diagnostic and follow-up samples from 4 AML patients showed excellent/good concordance between methods for 13 samples with moderate MRD levels. The 4 samples with low levels of MRD (10-4 to 10-5) below the quantitative range as defined by EuroMRD for RQ-PCR were all detectable by ddPCR, highlighting that ddPCR could provide robust and highly sensitive MRD assays compared to the standardized RQ-PCR assays. In conclusion, ddPCR is a promising technique that can reproducibly and reliably quantify MLL-r transcripts for MRD monitoring of MLL-r leukemia. Highly sensitive and robust molecular MRD monitoring by ddPCR holds promise for improving response-based therapeutic stratification and prediction of molecular relapse before overt hematological relapse. Disclosures No relevant conflicts of interest to declare.

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