CONTEXT: Testing for BCR-ABL1 kinase domain (KD) mutations should always be performed before tyrosine kinase inhibitor (TKI) changes. Next-generation sequencing (NGS) is the best approach to highlight emerging mutations in patients not responding adequately to TKI therapy. However, NGS requires sample centralization and batch analysis and has a non-negligible time to results. In this study, we set up and validated a novel droplet digital PCR (ddPCR)-based multiplex strategy for the detection and quantitation of transcripts harboring mutations impacting TKI selection. METHODS: In collaboration with Bio-Rad, a 3-tube ddPCR strategy was designed that enables identification and quantitation of 16 nucleotide substitutions encoding the 13 mutations associated with resistance to one or more second-generation TKI (2GTKI). Primers and FAM-or FAM/HEX-labelled probes were grouped on a TKI-specific basis and generated clusters of droplets mapping to spatially distinct areas of the 2D plot based on resistance profiles. Each tube also incorporated primers and HEX-labelled probes for e13a2, e14a2, and e1a2 BCR::ABL1 fusion transcripts to express results as the percentage of mutation-positive over total BCR::ABL1 transcripts. For validation, a total of 101 RNA samples from healthy donors, TKI-sensitive and -resistant patients, and BCR::ABL1-positive and -negative cell lines were used. cDNA (125 ng) obtained with ABL1-specific primers was analyzed in duplicate on a QX200 ddPCR system (Bio-Rad). RESULTS: The limit of blank was determined using 60 blank samples. Accuracy and specificity were confirmed using 48 samples positive for one or more 2GTKI-resistant mutations or mutations at nearby codons (to exclude cross-reactivity). Analysis of serial dilutions of cell line mixtures made using BCR::ABL1-positive mutation-positive cells, BCR::ABL1-positive unmutated cells, and BCR::ABL1-negative cells to mimic different mutation frequencies (70%, 5%, and 0.5%) and different transcript levels (MR0 to MR3) showed that a 0.5% lower detection limit could be consistently achieved irrespective of BCR::ABL1 levels. CONCLUSIONS: ddPCR proved highly sensitive and accurate. Total hands-on time was approximately 2 hrs, and time from sample to results was 2 days. Therefore, ddPCR may be integrated into diagnostic algorithms of CML (and Ph+ ALL) patients as a convenient first-level screening tool for mutations impacting TKI selection.

Abteilung Hämatologie Onkologie Klinik für Innere Medizin 2 Universitätsklinikum Jena Jena Germany

Bio Rad Laboratories Digital Biology Group Peterborough United Kingdom

Bio Rad Laboratories Digital Biology Group Pleasanton USA

Department of Experimental Diagnostic and Specialty Medicine Institute of Hematology L e A Seràgnoli University of Bologna Bologna Italy

Institute of Hematology and Blood Transfusion Prague Czech Republic

IRCCS Azienda Ospedaliero Universitaria di Bologna Istituto di Ematologia Seràgnoli Bologna Italy

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