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Somatic variants in CML-CP as predictive biomarker
(2G-TKI) dasatinib, nilotinib and bosutinib. In random- ized studies, 2G-TKI induce faster, deeper molecular responses than imatinib with a lower risk of progression to blast phase but no convincing evidence of better sur- vival.2-4 Consequently, there is controversy as to which TKI to use as initial therapy, although imatinib remains the first choice for many people because of the low inci- dence of serious life-threatening side-effects and recent availability of less expensive generic formulations.5,6
Clinical risk scores can be used to direct initial therapy but are often inaccurate at the subject level.7-10 Early molec- ular responses analyzed by reverse transcription-quantita- tive PCR (RT-qPCR) at 3, 6 and 12 months are widely used to direct therapy.11-13 Individuals failing to achieve these landmarks can be switched to a different TKI but there are no convincing data that the change of therapy changes their outcome. Because most progressions occur within two years of starting TKI-therapy14 early identification of those at high risk of progression would facilitate more rapid decision-making regarding more aggressive therapy.
In other hematologic neoplasms, the presence of somat- ically mutated genes involving signaling, RNA splicing, transcriptional control, DNA damage response and epige- netic regulation is correlated with survival and sometimes drives treatment.15,16 However, no ‘mutator’ phenotype associated with clinical outcome has been described in CML, particularly in chronic phase, as earlier studies focused on blastic phase.17-20 Four recent whole-exome sequencing (WES) and/or whole-transcriptome (RNA-Seq) studies identified somatic variants in 24, 19, 13 and 65 exomes (or transcriptomes in one study) from newly-diag- nosed CML-CP21,22 and in chronic phase and blast transfor- mation.23,24 Studies using deeper, targeted sequencing described genetic variants in CML-CP,25-28 especially in genes associated with epigenetic regulation. These vari- ants were also present in Philadelphia (Ph)-chromosome- negative cells, suggesting that they antedated the BCRABL1 translocation event as an early step in develop- ing CML.29 Finally, variants in hematologically normal eld- erly individuals are described, although the risk of conver- sion from age-related clonal hematopoiesis (ARCH) to leukemia was modest.30,31
We recently identified differences in genome-wide DNA methylation patterns in CD34+ cells of CML-CP compared with normal subjects. These differences were not observed at the time of complete cytogenetic remis- sion,32 suggesting a role for epigenetic regulation in CML- CP. In this study, we interrogated genetic variants in pre- therapy CML-CP using a targeted panel of genes enriched in epigenetic modifiers and Ion Torrent Personal-Genome- Machine (PGM) next-generation sequencing (NGS). We then assessed the predictive value of these variants for diverse therapy outcomes in the context of different TKI therapies.
Methods
Study participants
We studied 124 untreated subjects with CML-CP and 14 normal individuals as negative controls, selecting CD34+ cells. Subjects were non-consecutive and selected for optimal response (n=69) or non-response (n=55) to TKI-therapy.11 Evolution of the somatic variants after treatment, was investigated using CD34+ (n=11) and whole-blood cells (n=4) from subjects in major molecular remis-
sion (MR3; 3-log reduction in BCRABL1-transcripts from baseline) and after progression to blast phase, respectively. We also used CD34+ cells from three subjects with somatic variants at diagnosis, to establish liquid cultures with in vitro TKI-treatment, as a biolog- ical validation of our findings (Online Supplementary Methods and Results, and Online Supplementary Figure S1). All subjects gave writ- ten informed consent and the local research Ethics Committee approved the study.
Definitions
Response was defined as BCRABL1/ABL1 transcript levels according to the International Scale (IS) ≤10%, ≤1% and ≤0.1% at 3, 6 and 12 months after initiating TKI-therapy, respectively.11 Because some subjects did not have real-time qualitative poly- merase chain reaction (RT-qPCR) sampling at pre-specified times during the first year, responders were required to have at least ≥2 of these results available. Non-responders satisfied the European LeukemiaNet criteria for failure.11
DNA preparation
In 103 subjects, paired leukemia/control DNA was analyzed; in 44 and 59 subjects control DNA was obtained from diagnostic T cells expanded in vitro and from samples in MR4-molecular remis- sion (4-log reduction from baseline),33 respectively. We measured BCRABL1/ABL1 in 13 T-cell samples and confirmed very low expression. In seven subjects with somatic variants at diagnosis we compared detection of somatic variants in whole-blood and CD34+ cell populations (Online Supplementary Methods and Results).
Targeted gene panel design
Based on preliminary analyses investigating gene expression for epigenetic modifiers in CML-CP (Online Supplementary Methods and Results, and Online Supplementary Figure S2), and a literature review for frequently mutated genes in leukemia, we generated a custom panel of 71 genes enriched for modifiers of DNA methy- lation and histone methylation/acetylation (2002 amplicons) (Table1).
Semi-conductor-based targeted sequencing
Amplicon library preparation, templating and sequencing using the Ion Torrent PGM (Thermo Fisher Scientific, Waltham, MA, USA) were performed in line with the manufacturer’s instructions (Online Supplementary Methods). To validate somatic variants, we re-ran newly-prepared libraries with validation rate of 70% (49 of 70).
Ion PGM sequencing informatics
Base-calling, mapping, alignment and further quality filtering were performed using Torrent-Suite_v4.0.2 and the Cloud-based Ion-Reporter_v5-software (Thermo Fisher Scientific; analysis pipeline available in Online Supplementary Methods and Online Supplementary Figure S3). The data have been deposited at the European Variation Archive under accession n. PRJEB32264.
Statistical analysis
Results were analyzed in R_v3.2.2. Event-free-survival (EFS),34 progression-free-survival (PFS) and CML-related-survival probabil- ities were estimated by the Kaplan-Meier method and compared by the log-rank test at six or eight years (2G-TKI and imatinib, respectively) from starting therapy. A Cox proportional hazard regression model was used to estimate hazard ratios (HR) and 95% confidence intervals (95%CI) in univariate/multivariate analyses. The rate of MR3 at five years was estimated by the cumulative incidence function with groups compared by the Gray test (univariate), and the Fine-Gray model (multivariate analysis;
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