Impact of BCR::ABL1 transcript type on RT-qPCR amplification performance and molecular response to therapy.

Several studies have reported that chronic myeloid leukaemia (CML) patients expressing e14a2 BCR::ABL1 have a faster molecular response to therapy compared to patients expressing e13a2. To explore the reason for this difference we undertook a detailed technical comparison of the commonly used Europe Against Cancer (EAC) BCR::ABL1 reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) assay in European Treatment and Outcome Study (EUTOS) reference laboratories (n = 10). We found the amplification ratio of the e13a2 amplicon was 38% greater than e14a2 (p = 0.015), and the amplification efficiency was 2% greater (P = 0.17). This subtle difference led to measurable transcript-type dependent variation in estimates of residual disease which could be corrected by (i) taking the qPCR amplification efficiency into account, (ii) using alternative RT-qPCR approaches or (iii) droplet digital PCR (ddPCR), a technique which is relatively insensitive to differences in amplification kinetics. In CML patients, higher levels of BCR::ABL1/GUSB were identified at diagnosis for patients expressing e13a2 (n = 67) compared to e14a2 (n = 78) when analysed by RT-qPCR (P = 0.0005) but not ddPCR (P = 0.5). These data indicate that widely used RT-qPCR assays result in subtly different estimates of disease depending on BCR::ABL1 transcript type; these differences are small but may need to be considered for optimal patient management.

Analysis of chronic myeloid leukaemia during deep molecular response by genomic PCR: a traffic light stratification model with impact on treatment-free remission.

This work investigated patient-specific genomic BCR-ABL1 fusions as markers of measurable residual disease (MRD) in chronic myeloid leukaemia, with a focus on relevance to treatment-free remission (TFR) after achievement of deep molecular response (DMR) on tyrosine kinase inhibitor (TKI) therapy. DNA and mRNA BCR-ABL1 measurements by qPCR were compared in 2189 samples (129 patients) and by digital PCR in 1279 sample (62 patients). A high correlation was found at levels of disease above MR4, but there was a poor correlation for samples during DMR. A combination of DNA and RNA MRD measurements resulted in a better prediction of molecular relapse-free survival (MRFS) after TKI stop (n = 17) or scheduled interruption (n = 25). At 18 months after treatment cessation, patients with stopped or interrupted TKI therapy who were DNA negative/RNA negative during DMR maintenance (green group) had an MRFS of 80% and 100%, respectively, compared with those who were DNA positive/RNA negative (MRFS = 57% and 67%, respectively; yellow group) or DNA positive/RNA positive (MRFS = 20% for both cohorts; red group). Thus, we propose a "traffic light" stratification as a TFR predictor based on DNA and mRNA BCR-ABL1 measurements during DMR maintenance before TKI cessation.

Characterization of 46 patient-specific BCR-ABL1 fusions and detection of SNPs upstream and downstream the breakpoints in chronic myeloid leukemia using next generation sequencing.

In chronic myeloid leukemia, the identification of individual BCR-ABL1 fusions is required for the development of personalized medicine approach for minimal residual disease monitoring at the DNA level. Next generation sequencing (NGS) of amplicons larger than 1000 bp simplified and accelerated a process of characterization of patient-specific BCR-ABL1 genomic fusions. NGS of large regions upstream and downstream the individual breakpoints in BCR and ABL1 genes, respectively, also provided information about the sequence variants such are single nucleotide polymorphisms.

Next-generation deep sequencing improves detection of BCR-ABL1 kinase domain mutations emerging under tyrosine kinase inhibitor treatment of chronic myeloid leukemia patients in chronic phase.

PURPOSE: Here, we studied whether amplicon next-generation deep sequencing (NGS) could improve the detection of emerging BCR-ABL1 kinase domain mutations in chronic phase chronic myeloid leukemia (CML) patients under tyrosine kinase inhibitor (TKI) treatment and discussed the clinical relevance of such sensitive mutational detection. METHODS: For NGS data evaluation including extraction of biologically relevant low-level variants from background error noise, we established and applied a robust and versatile bioinformatics approach. RESULTS: Results from a retrospective longitudinal analysis of 135 samples of 15 CML patients showed that NGS could have revealed emerging resistant mutants 2-11 months earlier than conventional sequencing. Interestingly, in cases who later failed first-line imatinib treatment, NGS revealed that TKI-resistant mutations were already detectable at the time of major or deeper molecular response. Identification of emerging mutations by NGS was mirrored by BCR-ABL1 transcript level expressed either fluctuations around 0.1 %(IS) or by slight transcript level increase. NGS also allowed tracing mutations that emerged during second-line TKI therapy back to the time of switchover. Compound mutants could be detected in three cases, but were not found to outcompete single mutants. CONCLUSIONS: This work points out, that next-generation deep sequencing, coupled with a robust bioinformatics approach for mutation calling, may be just in place to ensure reliable detection of emerging BCR-ABL1 mutations, allowing early therapy switch and selection of the most appropriate therapy. Further, prospective assessment of how to best integrate NGS in the molecular monitoring and clinical decision algorithms is warranted.