We're bringing you highlights from the 67th ASH Annual Meeting with a summary of selected scientific sessions on CML

🌟 Oral Abstract Session: CML clinical & epidemiological -
Decoding the molecular drivers of response and resistance

Chairs: Sin Tiong Ong (Singapore) - 
Naranie Shanmunagathan (Adelaide)
This session highlighted advances in understanding why patients with CML either respond well to TKIs, relapse after stopping therapy, or develop treatment failure. Across six presentations, scientists used genomic profiling, single-cell sequencing, transcriptomics, machine learning, clonal evolution studies, and integrated DNA/RNA MRD monitoring to decode mechanisms of resistance, relapse, and biological heterogeneity.
Key themes included ASXL1-driven risk, LSC signatures predicting relapse, genomic variants at diagnosis, AI-based TFR prediction, the distinct biology of minor BCR::ABL1, and DNA-based minimal residual disease (MRD) monitoring for safer TKI de-escalation.

Our key takeaways from the presentations:

Presentation 1:
Distinct patterns of mutant ASXL1 over time and their implications for treatment failure and BCR::ABL1 mutation development in newly diagnosed patients with CML in chronic phase treated with asciminib vs investigator-selected (IS) tyrosine kinase inhibitors in the ASC4FIRST study
Speaker: Susan Branford (Adelaide)
“Most ASXL1 clones presented at diagnosis were eradicated during therapy, but those that persisted or emerged were closely linked with poor outcomes.” – Susan Branford

Key points:

• ASXL1 prevalence: ASXL1 was the most frequent additional genomic alteration (11% baseline; 15% anytime), with most clones eradicated on therapy. 
• Risk patterns: Persistent or emergent ASXL1 variants were strongly associated with treatment failure and acquisition of BCR::ABL1 mutations. 
• Clonal interpretation: Emergent variants must be interpreted alongside BCR::ABL1 dynamics to distinguish CHIP clones, which lack leukemic relevance.
• Treatment comparison: ASXL1 patients without ASXL1 mutations had lower failure rates on asciminib, whereas ASXL1 positive patients had similar outcomes across both arms.
• Clinical implication: mutated ASXL1 is a risk factor, but not a treatment-selection biomarker between asciminib and IS-TKIs. 

Presentation 2:
A single-cell atlas of diagnostic bone marrow to uncover the origins of CML relapse following therapy cessation
Speaker: Vaidehi Krishnan (Singapore)
“LSC signatures at diagnosis can predict relapse after stopping TKIs.” – Vaidehi Krishnan

Key points:

• Predictive LSC states:Diagnostic leukemic stem cells (LSCs) already carry relapse-specific transcriptional signatures, independent of cell composition. 
• Two relapse subtypes: Relapse divides into MYC/mTOR-driven (proliferative) and TNFα/NF-κB-driven (immune) subtypes.
• Immune microenvironment: Relapse-I patients showed heightened cell - cell interactions, particularly TNFα signalling to LSCs. 
• Novel biomarkers: PRSS21 and SPAG6 emerged as candidate diagnostic TFR biomarkers requiring validation. 
• Clinical insight: Remission LSCs occupy a hybrid intermediate state, potentially explaining TKI sensitivity and durable TFR.

Presentation 3:
Somatic mutations at diagnosis in patients with chronic phase CML receiving frontline imatinib are associated with a higher rate of treatment failure: First analysis from the international CML Foundation (iCMLf) Genomics Alliance on the HARMONY platform

Presenter: Susan Branford (Adelaide)
“This is the largest genomic analysis of frontline imatinib-treated patients, and it highlights the clear clinical relevance of pathogenic variants at diagnosis.” – Susan Branford

Key points:

• Global data integration:The iCMLf Genomics Alliance, in partnership with the HARMONY big-data platform, aggregates international genomic and clinical datasets to enable the largest, standardised analysis of pathogenic variants in frontline CML, strengthening the evidence base for genomics-guided risk stratification. 
• Pathogenic variants: 20% of patients carried pathogenic mutations at diagnosis - most commonly ASXL1 (11%) - and these variants were associated with higher treatment failure, more BCR::ABL1 mutations, and lower MMR rates.
• Progression risk: Variant-positive patients showed a trend toward higher progression to AP/BP, though not always statistically significant due to mixed cohort selection.
• Validation:Variant frequencies and clinical associations were consistent with previously published single-centre studies, reinforcing the robustness of the pooled dataset.
• Future work: Ongoing expansion of the dataset and separation of retrospectively sequenced cases will support refined risk models and multivariable analyses.
  
  

Presentation 4:
A machine learning approach identifies a transcriptomic signature predicting treatment-free remission in chronic myeloid leukemia
Presenter: Vincent Alcazar (Lyon)
“To date, there is no tool capable of predicting treatment-free remission at the individual level — our model aims to change that.” – Vincent Alcazar
Key points:

• Predictive signature: A 50-gene blood-based signature predicted TFR with AUC 0.72–0.76 in external validation. 
• Biological pathways: High-signature patients showed glycolysis/ROS and antigen-processing activation, while low-signature patients displayed MYC targets, genomic instability, and T-cell exhaustion.
• Model independence: Prediction was independent of TKI duration and DMR duration, meeting current TFR prerequisites.
• Clinical application: On going prospective study to develop a tool for prediction at the individual level. 
• Future steps: Moving to targeted RNA sequencing for a practical clinical TFR test applicable across TKIs.

Presentation 5:
Molecular landscape and clonal evolution in minor versus major BCR::ABL1 chronic myeloid leukemia under tyrosine kinase inhibition: A Study from the French group fi-LMC
Presenter: Benjamin Podvin (Lille)
“Minor BCR::ABL1 CML is a rare subtype with a distinct clinico-biological and molecular profile.“ – Benjamin Podvin

Key points:

• Minor subtype: Minor BCR::ABL1 CML represents a biologically specific subtype with a myelomonocytic phenotype and deeper cytopenias. 
• High mutational burden: Minor cases showed frequent ASXL1, TET2, DNMT3A, and multi-hit epigenetic lesions, indicating a pre-mutated myeloid background.
• Clonal architecture: In ~1/3 of cases, the BCR::ABL1 fusion was a secondary event, arising on top of pre-existing myeloid clones. 
• Single-cell profilingMulti-omic single-cell profiling demonstrated broad myeloid involvement with sparing of T-cells and clarified primary vs secondary acquisition patterns. 
• Clinical relevance: Minor BCR::ABL1 behaves more like a CMML-like myeloid neoplasm, supporting tailored monitoring and therapeutic strategies. 

Presentation 6:
DNA-based MRD monitoring enhances risk stratification during TKI dose reduction in CML: Evidence from the clinical trial
Presenter: Katerina Machova Polakova (Prague)
“DNA-based MRD helps distinguish truly deep responders from those with silent residual disease —
a critical step for safe TKI tapering.” – Katerina Machova Polakova

Key points:

• MRD stratification model: Combined DNA and RNA MRD stratification accurately predicted relapse risk during both dose reduction and post-cessation. 
• Risk groups: Double-positive patients had the highest relapse rates; DNA+/RNA- showed intermediate risk; double-negative had ~90% relapse-free survival. 
• MRD dynamics: MRD status evolved over time, with RNA re-emergence during de-escalation serving as an early warning signal. 
• Clinical guidance: Double-negative patients may qualify for less intensive monitoring, while DNA-positive, RNA-negative, and red double-positive groups require adjusted dosing or delayed cessation.
• Clinical impact: DNA-guided de-escalation may reduce relapse, improving safety and precision in TKI stopping strategies.