BCR-ABL1 kinase domain mutation analysis by next generation sequencing detected additional mutations in chronic myeloid leukemia patients with suboptimal response to imatinib

Mutations in the BCR-ABL1 kinase domain (BCR-ABL1 KD) is one of the most common determinants of tyrosine kinase inhibitor (TKI) resistance in patients with chronic myelogenous leukemia (CML) [1]. The emergence of BCRABL1 kinase domain (KD) mutations contributes to 40–50% of all TKI resistant cases [2]. The current gold standard method for BCR-ABL1 KD mutation detection is Sanger sequencing (SS), which has an analytical sensitivity limit of 10–20% [3]. SS cannot reliably discriminate between polyclonal (more than one mutant clone) and compound mutations [4]. Next generation sequencing (NGS) is increasingly being suggested as the method of choice for detecting BCR-ABL1 KD mutations due to the increased sensitivity of this method to identify mutations at variant allele frequencies (VAFs) as low as 1–3% [3]. The presence of even low-level BCR-ABL1 KD mutations have been shown to be significantly associated with poorer outcomes in patients receiving TKI for CML [3]. NGS based BCR-ABL1 KD mutation testing at the time of suspected TKI failure could aid in subsequent therapy selection [3]. Although BCR-ABL1 KD mutations explained TKI SubOptimal Response (SOR) to a certain extent in our patients (33% overall; 14% in Chronic phase (CP) CML [5]), the reasons for SOR in a majority of these patients remain unclear. Here we assessed whether NGS could identify BCR-ABL1 KD mutations in CML patients with SOR to imatinib, but mutation negative by SS. We also attempted to demonstrate the kinetics of low-level mutations detected by NGS in a subset of these patients. This study is unique since we specifically analyzed whether NGS could detect any additional mutations in patients who had no detectable mutations by SS. All previous studies using NGS to detect BCR-ABL1 KD mutations have tested all the imatinib failure patient samples by both SS and NGS [3,6,7]. Three cohorts of patients were included in this study (Figure 1). Cohort 1 included CML patients with BCR-ABL1 KD mutation detected by SS for validation of the inhouse bioinformatics pipeline (n1⁄4 5). Cohort 2 included samples from CML patients with imatinib failure (BCRABL1 transcript ratio of >1% at a median duration of 20months post imatinib therapy (3 164months) as per ELN guidelines [8] (n1⁄4 51) collected between 2015 and 2017. Cohort 3 included CP-CML patients who did not achieve MMR (BCR-ABL1 transcript ratio >0.1%, defined as SOR) after 12-months of imatinib therapy (n1⁄4 41), enrolled in a prospective study. Both cohorts 2 and 3 were negative for BCR-ABL1 KD mutation by SS. Patients with clinically relevant BCR-ABL1 KD mutation detected by NGS in cohorts 1 and 3 were also longitudinally followed-up by SS during subsequent time points at least once in 6months. This study was approved by Institutional review board. The demographics of patients in all 3 cohorts is listed in Supplementary Table 1. Total RNA was extracted from peripheral blood samples using Trizol reagent followed by cDNA synthesis using random hexamer and reverse transcriptase enzyme (High-Capacity c-DNA Reverse Transcription Kit, Thermo Scientific, Applied Biosystems). BCR-ABL1 KD mutation screening by SS was performed as previously described [9,10]. BCR-ABL1 KD mutation by NGS was carried out as previously described [4]. Library preparation was carried out based on SureSelect QXT Library Preparation protocol (Agilent, Cat #G9683B). The Illumina-compatible sequencing library was quantified by Qubit fluorometer (Thermo Fisher Scientific, MA, USA). Sequencing was performed in Illumina Hiseq and Miseq platforms. Analysis was carried out by creating a bioinformatic pipeline created and run on an open source, web-based platform (https://usegalaxy.org/). After checking the FASTQ files for quality