Detection and Monitoring of BCR-ABL1 Kinase Domain Mutations By Next Generation Sequencing

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 4042-4042
Author(s):  
Pascal Vannuffel ◽  
Barbara Cauwelier ◽  
Céline De Rop ◽  
Friedel Nollet

Abstract Background. Among myeloproliferative diseases, development of chronic myeloid leukaemia (CML) is associated with the emergence of the fusion oncogene BCR-ABL1 resulting from a t(9,22) chromosomal translocation (Philadelphia chromosome). Mutations of the BCR-ABL1 kinase domain constitute a major cause of treatment failure in CML patients receiving tyrosine kinase inhibitor (TKI) treatment. Moreover, the occurrence of cells with multiple mutations is frequently associated with a higher resistance rate to the different TKI (Imatinib, Dasatinib or Nilotinib). So far, the gold standard procedure to detect BCR-ABL1 mutations remains the conventional Sanger Sequencing (SS), endowed with an analytical sensitivity of 10 to 20 %. The recent implementation of Next Generation Sequencing (NGS) allows lowering the sensitivity level and quantitative follow-up of the mutated subclone(s), which probably improves CML patient's treatments management. Aims. In this retrospective study, we evaluate the advantage of NGS approach to i) identify patients harbouring (low level) mutations that have not been not assessed by conventional methods, ii) detect the emergence of mutated clones earlier than SS and iii) monitor evolution of mutations. Methods. Total BCR-ABL1 RNA was transcribed into a long range cDNA covering the kinase, the regulatory, and the SH2/SH3 domains of either p190 or p210 BCR-ABL1 transcripts (exons 4 to 10). From primers designed with the AmpliseqTM Designer Software, a set of 10 amplicons was generated according to the AmpliSeqTM protocol. Bar-coded libraries were sequenced on the Ion Torrent PGM platform and data were analysed with Torrent Suite and NextGene softwares. Serial dilutions of samples harbouring mutations at different levels were used to determine a variant frequency cut-off. Our methodology was applied to a group of 36 patients presenting with poor response to TKI and with no mutation detected by SS and to a set of 100 samples, corresponding to 20 mutated patients, at different time points before the time of mutation identification by SS. Results. From the serial dilutions experiment, the detection limit of the assay was set up to 2 % (R² > 0.997). An overall coverage ranging from 20 000 to 50 000 reads can be achieved for the hotspot mutations when up to 12 samples were tested together on a 316 Ion chip. On the 36 patients tested by NGS versus SS, no one was found to harbour TKI-resistance mutation. NGS successfully detected all mutations identified by SS; mutations were typically detected within 4 months (18/20 patients) and were also detected up to 9 months prior to detection by SS, even in patients with a low abundance of BCR-ABL1 transcripts and in sequencing failure by SS. In 2 patients presenting with up to 3 mutations, evolution of mutations (emergence, expansion or depletion) correlates with clinical data of treatment decisions, i.e. E255K (patient-1) and L248V (patient-2) depletions when switching from Imatinib to Dasatinib, F317L (patient-1), G250E (patient-1) and T315I (patient-2) expansions under Dasatinib and a complete but transient depletion of T315I (patient-2) with the protein synthesis inhibitor homoharringtonine (Omacetaxine). Finally, assessment of the mutation status of one patient with compound mutations following an Illumina protocol on a MiSeq platform had allowed comparison of technologies performances. Conclusions. NGS did not detect mutations in 36 patients poorly responding to TKI with no detectable BCR-ABL1 TK mutation by SS. For 20 patients showing BCR-ABL1 TK mutation by SS, NGS was able to detect the mutation in samples taken up to 9 months prior to the moment when the mutation was observed by SS. Advances in sequencing technologies and further lowering sensitivity levels can contribute even more to earlier detection of mutations and guide an earlier switch of TKI. Quantitative and sensitive monitoring of mutation evolution can also inform the most appropriate and optimized treatment algorithms. A prospective evaluation of the clinical impact of NGS-based BCR-ABL1 mutation detection is ongoing. Disclosures Vannuffel: ARIAD Pharmaceuticals: Research Funding.

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 384-384 ◽  
Author(s):  
Yucel Erbilgin ◽  
Ahmet Emre Eskazan ◽  
Ozden Hatirnaz Ng ◽  
Ayse Salihoglu ◽  
Tugrul Elverdi ◽  
...  

Abstract Background and Aim BCR-ABL1 mutation testing is recommended for chronic myeloid leukemia (CML) patients who have suboptimal response and/or treatment failure with tyrosine kinase inhibitor (TKI) therapy. BCR-ABL1 mutations in the kinase domain (KD) of ABL1 account for at least 40-50% of all TKI resistant cases. Thus, detection of low-level mutations after development of resistance may offer critical information to guide subsequent therapy selection. The current gold standard for BCR-ABL1 mutation detection is Sanger sequencing (SS), which has an analytical sensitivity of approximately 10-20%. In this study, our aim was to detect low level BCR-ABL1 variants in follow up samples of CML patients with TKI resistance using next-generation sequencing (NGS) approach. Methods Eight patients with CML who were resistant to imatinib had been routinely sequenced with SS for BCR-ABL1 KD mutations between December 2009 and December 2012. We then retrospectively analyzed these samples with NGS. RT and long range PCR was performed to amplify BCR-ABL1 fusion transcripts and the PCR products sequenced bidirectional after library preparation. We performed a fusion transcript based BCR-ABL1 mutation assay using Roche 454 amplicon deep-sequencing technology that is suited for detecting low level variants in pooled amplicon samples. Sequencing data was analyzed with GS Amplicon Variant Analyzer (AVA) software, and the variant frequency cut-off was adjusted to 1%. Results Clinical features, sequencing results, and the outcomes of the patients were summarized in Table 1. Four patients were male, and the median age was 37 years (range, 20-60 years). The patients were all in chronic phase at the time of the diagnosis. After imatinib resistance, 4 patients had received dasatinib (DAS), and 2 were given nilotinib (NIL) as second line TKI treatment. The remaining two patients had both received DAS and NIL (Table 1). In a set of 20 clinical samples, at different time points, NGS not only identified all the mutations detected by SS, but additionally identified low level variants present between 1 – 28.12 %. T315I and E255K/V were the most common mutations, which were detected in four patients, both by SS and NGS at the same time points (Table 1). Two patients (patient #1 and #4) had T315I, and they both progressed to blastic phase and died. E255K was detected in patients #2 and #3, and patient #2 had achieved and maintained complete cytogenetic and major molecular responses with 100 mg daily DAS, whereas patient #3 had received both NIL and DAS, but she was deceased due to myeloid blastic crisis. Among 4 patients (patients #5, #6, #7, and #8), mutation analysis was performed at eleven different time points, and these patients were wild-type with SS. We also did not detect any clinically significant mutations in these patients by NGS. Most probably mechanisms other than KD mutations were responsible for the TKI resistance among these four patients. Conclusions Polyclonal mutations in BCR-ABL1 KD are commonly identified in TKI resistant patients. Thus, detection of low-level mutations after development of resistance offers critical information to guide subsequent therapy selection. An inappropriate kinase inhibitor selection could highly increase the risk of treatment failure with clonal expansion of the resistant mutant. In our imatinib resistant cohort, we detected low level variants accompany to known mutations which may constitute background genetic variations. Although we had expected to detect mutations earlier by NGS (i.e. before these mutations can be detected by SS), we did not observe such finding in our patients. The patients' samples may not show a stable mutation spectrum between time points. Hence, it is not always possible to spot a mutation before patients show resistance to therapy. Regular NGS analysis might detect these mutations in earlier phases, which might help clinicians to choose the most suitable individual treatment modality for the patients. Acknowledgment The authors would like to thank the Interlaboratory Robustness of Next-generation sequencing (IRON) Phase II study group members, especially to Simona Soverini and Alexander Kohlmann who designed BCR-ABL primers and plates. We also would like to thank the Research Fund of the Istanbul University (Project no. 24244) and Turkish Society of Hematology for supporting the study. Disclosures: Sayitoglu: Roche Diagnostics: Research Support Other.


2017 ◽  
Vol 34 (7) ◽  
Author(s):  
Matthew K. Stein ◽  
Lindsay Morris ◽  
Jennifer L. Sullivan ◽  
Moon Fenton ◽  
Ari VanderWalde ◽  
...  

2020 ◽  
Vol 58 (2) ◽  
pp. 306-313 ◽  
Author(s):  
Mariano Provencio ◽  
Clara Pérez-Barrios ◽  
Miguel Barquin ◽  
Virginia Calvo ◽  
Fabio Franco ◽  
...  

AbstractBackgroundNon-small cell lung cancer (NSCLC) patients benefit from targeted therapies both in first- and second-line treatment. Nevertheless, molecular profiling of lung cancer tumors after first disease progression is seldom performed. The analysis of circulating tumor DNA (ctDNA) enables not only non-invasive biomarker testing but also monitoring tumor response to treatment. Digital PCR (dPCR), although a robust approach, only enables the analysis of a limited number of mutations. Next-generation sequencing (NGS), on the other hand, enables the analysis of significantly greater numbers of mutations.MethodsA total of 54 circulating free DNA (cfDNA) samples from 52 NSCLC patients and two healthy donors were analyzed by NGS using the Oncomine™ Lung cfDNA Assay kit and dPCR.ResultsLin’s concordance correlation coefficient and Pearson’s correlation coefficient between mutant allele frequencies (MAFs) assessed by NGS and dPCR revealed a positive and linear relationship between the two data sets (ρc = 0.986; 95% confidence interval [CI] = 0.975–0.991; r = 0.987; p < 0.0001, respectively), indicating an excellent concordance between both measurements. Similarly, the agreement between NGS and dPCR for the detection of the resistance mutation p.T790M was almost perfect (K = 0.81; 95% CI = 0.62–0.99), with an excellent correlation in terms of MAFs (ρc = 0.991; 95% CI = 0.981–0.992 and Pearson’s r = 0.998; p < 0.0001). Importantly, cfDNA sequencing was successful using as low as 10 ng cfDNA input.ConclusionsMAFs assessed by NGS were highly correlated with MAFs assessed by dPCR, demonstrating that NGS is a robust technique for ctDNA quantification using clinical samples, thereby allowing for dynamic genomic surveillance in the era of precision medicine.


2018 ◽  
Vol 56 (7) ◽  
pp. 1046-1053 ◽  
Author(s):  
Anne Bergougnoux ◽  
Valeria D’Argenio ◽  
Stefanie Sollfrank ◽  
Fanny Verneau ◽  
Antonella Telese ◽  
...  

Abstract Background: Many European laboratories offer molecular genetic analysis of the CFTR gene using a wide range of methods to identify mutations causative of cystic fibrosis (CF) and CFTR-related disorders (CFTR-RDs). Next-generation sequencing (NGS) strategies are widely used in diagnostic practice, and CE marking is now required for most in vitro diagnostic (IVD) tests in Europe. The aim of this multicenter study, which involved three European laboratories specialized in CF molecular analysis, was to evaluate the performance of Multiplicom’s CFTR MASTR Dx kit to obtain CE-IVD certification. Methods: A total of 164 samples, previously analyzed with well-established “reference” methods for the molecular diagnosis of the CFTR gene, were selected and re-sequenced using the Illumina MiSeq benchtop NGS platform. Sequencing data were analyzed using two different bioinformatic pipelines. Annotated variants were then compared to the previously obtained reference data. Results and conclusions: The analytical sensitivity, specificity and accuracy rates of the Multiplicom CFTR MASTR assay exceeded 99%. Because different types of CFTR mutations can be detected in a single workflow, the CFTR MASTR assay simplifies the overall process and is consequently well suited for routine diagnostics.


2020 ◽  
Vol 5 (3) ◽  
pp. 467-479 ◽  
Author(s):  
Malinda Butz ◽  
Amber McDonald ◽  
Patrick A Lundquist ◽  
Melanie Meyer ◽  
Sean Harrington ◽  
...  

Abstract Background Deafness and hearing loss are common conditions that can be seen independently or as part of a syndrome and are often mediated by genetic causes. We sought to develop and validate a hereditary hearing loss panel (HHLP) to detect single nucleotide variants (SNVs), insertions and deletions (indels), and copy number variants (CNVs) in 166 genes related to nonsyndromic and syndromic hearing loss. Methods We developed a custom-capture next-generation sequencing (NGS) reagent to detect all coding regions, ±10 flanking bp, for the 166 genes related to nonsyndromic and syndromic hearing loss. Our validation consisted of testing 52 samples to establish accuracy, reproducibility, and analytical sensitivity. In addition to NGS, supplementary methods, including multiplex ligation-dependent probe amplification, long-range PCR, and Sanger sequencing, were used to ensure coverage of regions that had high complexity or homology. Results We observed 100% positive and negative percentage agreement for detection of SNVs (n = 362), small indels (1–22 bp, n = 25), and CNVs (gains, n = 8; losses, n = 17). Finally, we showed that this assay was able to detect variants with a variant allele frequency ≥20% for SNVs and indels and ≥30% to 35% for CNVs. Conclusions We validated an HHLP that detects SNVs, indels, and CNVs in 166 genes related to syndromic and nonsyndromic hearing loss. The results of this assay can be utilized to confirm a diagnosis of hearing loss and related syndromic disorders associated with known causal genes.


Sign in / Sign up

Export Citation Format

Share Document