Introduction:

The BCR::ABL1 transcript is a defining characteristic of Chronic Myeloid Leukemia (CML) and European LeukemiaNet (ELN) guidelines emphasize monitoring its levels to evaluate treatment efficacy. While tyrosine kinase inhibitor (TKI) therapy has significantly improved outcomes for patients with chronic phase CML (CP-CML), a subset of patients still exhibits suboptimal responses. Qualitative differences in BCR::ABL1 transcript subtypes appear to affect response rates. Previous studies, primarily focusing on imatinib (IM) as frontline therapy, indicated that CML patients carrying the e14a2 transcript achieve more frequently optimal molecular responses by RT-QPCR if compared with e13a2. However, similar data in patients receiving second-generation TKIs (2G-TKIs) as frontline treatment is limited.

Patients and Methods

Hence, we evaluated in the real-life scenario of the GIMEMA LabNet CML network the impact of the most frequent BCR::ABL1 transcript types (e14a2, e13a2, double isoform e14a2/e13a2) molecular response rate of patients with newly diagnosed CP-CML at 6, 12, 24 months after frontline treatment. Findings were stratified as IM-treated versus 2G-TKIs.

Results:

Out of 9,699 patients, 1471 met study criteria with evaluable samples at the above timepoints. BCR::ABL1 transcript subtype carriers were: 675 (46%) with e14a2, 375 (25%) with e13a2, 290 (20%) with e14a2/e13a2, others 131 (9%). Current analysis focused on 1340 patients carrying the most frequent transcripts. Median age at diagnosis was 59 years (range 18-91), males were 766 (57%) and females 574 (43%). Frontline CML therapy was IM in 721, 2G-TKIs in 619 (230 with DAS, 386 with NIL, 3 with BOS). Within the IM cohort, at 6, 12 and 24 months, e14a2 carriers achieved > MR2 responses (38%, 60%, 80%;) if compared with e13a2 patients (21%, 39%, 68%, p=0.001, p<0.001, p=0.037 respectively). At the same time-points double isoform carriers performed better than e13a2 (35%, 62%, 85%; p=0.012, p<0.001, p=0.009). Among the 2G-TKIs cohort, e14a2 patients obtained better > MR2 responses at 6 and 12 months (67%, 75%) than e13a2 (50%, 62%; p=0.003, p=0.02 respectively) but there was no statistical difference at 24 months (85% vs 76%). No differences were documented when e14a2 was compared to the double isoform. Double isoforms showed better > MR2 rates than e13a2 at 6 and 12 months (67% vs 50%, 77% vs 62%; p=0.024, p=0.042) while at 24 months the rates of > MR2 were comparable (79% vs 76%). Notably, when e13a2 carriers were treated with 2G-TKIs achieved better and faster responses at 6 and 12 months (p<0.001) than with IM.

Conclusions:

Our data confirms that the kinetic behavior of BCR::ABL1 molecular reduction on frontline TKIs treatment shows different trajectories when evaluated by transcript types. Even if a limitation of our analysis might be the lack of risk distribution by Sokal or ELTS, these results, obtained in a high number of analyzed patients, preserve a notable meaning. These kinetic differences are also evident in 2G-TKIs treated patients. However, to what extent these differences are related to RTQ-PCR technical limitations (not relevant with digital PCR) or to real differences intrinsically related to the transcript type is yet to be clarified.

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2025
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