Grandisin induces apoptosis in leukemic K562 cells

Abstract In this study, the potential antileukemic activity of grandisin, a lignan extracted from Piper solmsianum, was evaluated against the leukemic line K562. The cytotoxicity of grandisin (0.018 to 2.365 µM) was evaluated in K562 and normal peripheral blood lymphocytes by Trypan Blue Exclusion and MTT methods after 48h exposure to the drug. In both methods, cellular viability was concentration-dependent and the IC50 values were lower than 0.85µM. Analysis of K562 cells after treatment with grandisin showed that the cell cycle was arrested in the G1 phase with a 12.31% increase, while both S and G2 phases decreased. Morphological studies conducted after the exposure of K562 to grandisin revealed changes consistent with the apoptosis process, which was confirmed by anexin V stain and caspase activation. Thus, lignan grandisin showed antileukemic activities against the K562 cell line and the cell death process occurred via apoptosis

BCR-ABL1 Compound Mutations Combining Key Kinase Domain Positions Confer Clinical Resistance to Ponatinib in Ph Chromosome-Positive Leukemia

SummaryPonatinib is the only currently approved tyrosine kinase inhibitor (TKI) that suppresses all BCR-ABL1 single mutants in Philadelphia chromosome-positive (Ph+) leukemia, including the recalcitrant BCR-ABL1T315I mutant. However, emergence of compound mutations in a BCR-ABL1 allele may confer ponatinib resistance. We found that clinically reported BCR-ABL1 compound mutants center on 12 key positions and confer varying resistance to imatinib, nilotinib, dasatinib, ponatinib, rebastinib, and bosutinib. T315I-inclusive compound mutants confer high-level resistance to TKIs, including ponatinib. In vitro resistance profiling was predictive of treatment outcomes in Ph+ leukemia patients. Structural explanations for compound mutation-based resistance were obtained through molecular dynamics simulations. Our findings demonstrate that BCR-ABL1 compound mutants confer different levels of TKI resistance, necessitating rational treatment selection to optimize clinical outcome