Background: Chronic myeloid leukemia (CML) is most commonly driven by the major BCR::ABL1 transcript (p210), while the minor BCR::ABL1 variant (p190) defines a rare subgroup associated with more aggressive disease and poorer outcomes (Jabbour et al., Blood Cancer J. 2017). Despite these clinical differences, the clonal architecture and molecular evolution of p190 CML during the chronic phase under tyrosine kinase inhibitor (TKI) therapy remain poorly characterized. Here, we performed comprehensive genomic profiling of a series of patients with p190 CML, at diagnosis and during follow-up, and compared the results to an age-matched cohort of patients with p210 CML.

Aim: The aim of this study was to characterize the genomic profile of p190 CML chronic phase at diagnosis, compare it to p210 CML, and investigate clonal evolution over time in relation to treatment response.

Methods: Forty-two patients with p190 CML in chronic phrase from the Fi-LMC cohort were identified. Data collection followed the current French legal rules for observational studies. Patients with p190 CML were compared to 42 age-matched patients enrolled in the SPIRIT trial (NCT00219739) with p210 CML in chronic phase on Imatinib alone as a control for age-related clonal hematopoiesis. BCR::ABL1/ABL1 transcript levels were quantified using standardized European Against Cancer (EAC) protocols. Targeted high-throughput sequencing (HTS, 80-gene panel including both myeloid and lymphoid-related genes) was performed on diagnostic samples in all cases. Genomic breakpoints were identified in all patients using a custom HTS-based assay. For p190 CML patients, matched hematologic/cytogenetic remissions samples were available, enabling longitudinal assessment of clonal evolution under TKI therapy.

Results: We analyzed 42 p190 CML patients in chronic phase, matched for age with 42 p210 CML patients (68.9 vs 67.6 years, p=0.4733). Complete blood count of the p190 patients (n=42) revealed differences compared to p210 patients with lower white blood cell counts (38.2 vs 58.0 x109/L, p=0.002), lower platelet counts (278 vs 366 x109/L, p=0.0015) and higher monocyte counts (12.3% vs 2.0%, p <0.0001). ELTS risk was high, intermediate and low in 45%; 38% and 11% of patients, respectively. First-line treatments were imatinib (38/42), dasatinib (2/42) or nilotinib (2/42). Additional cytogenetic abnormalities (ACA), assessed by conventional cytogenetics, were observed in 28% of p190 and 20% of p210 patients (p=0.4354). At diagnosis, at least one mutation was detected in 37 out 42 p190 patients, compared to 10 out of 42 p210 patients (88% vs 22%; p<0.001). In p190 patients, mutations frequently involved ASXL1 (65%), TET2 (multi-hit) (21%), DNMT3A (8%), KDM6A (8%)and STAT5B (8%), whereas in p210 patients, the most common mutations involved ASXL1 (11%), TET2 (7%) and RUNX1 (4%). No correlation was found between the genomic coordinates of the BCR intron 1 and ABL1 intron 1 breakpoints and the mutational landscape at diagnosis.

Furthermore, in 34 of the 42 p190 patients with at least one mutation and a high variant allele frequency (VAF > 40%), follow-up samples were available at the time of a ≥ 2-log reduction in BCR::ABL1 levels. This allowed the comparison of VAFs over time and infer whether the BCR::ABL1 rearrangement represented a primary or secondary event. Among these 34 patients, BCR::ABL1 was expected to be a primary event in 24 (71%) patients, and a secondary event in 10 (29%) patients. Clonal hierarchy was confirmed in selected cases using single-cell proteogenomics with Tapestri platform (MissionBio, USA). Patients with a secondary profile typically harbored co-mutations in ASXL1, TET2 and RUNX1 suggesting a chronic myelomonocytic leukemia (CMML)-like mutational pattern. During follow-up, these patients commonly presented with cytopenias (8/10), with 5/10 requiring long-term transfusion support.

Conclusion: Our data from the largest p190 cohort already described revealed that p190 CML displays a distinct clinical and molecular profile with more frequently secondary features and high mutation rates and CMML-like features (ASXL1, TET2 multi-hit and RUNX1) in a subset of patients. Routine high-throughput sequencing at diagnosis could improve risk stratification and guide treatment strategies. Single-cell proteogenomic profiling may refine disease understanding and management in this high-risk subset.

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