Chronic myeloid leukemia (CML) is caused by the constitutively activated tyrosine kinase breakpoint cluster (BCR)-ABL. Current frontline therapy for CML is imatinib, an inhibitor of BCR-ABL. Although imatinib has a high rate of clinical success in early phase CML, treatment resistance is problematic, particularly in later stages of the disease, and is frequently mediated by mutations in BCR-ABL. Dasatinib (BMS-354825) is a multitargeted tyrosine kinase inhibitor that targets oncogenic pathways and is a more potent inhibitor than imatinib against wild-type BCR-ABL. It has also shown preclinical activity against all but one of the imatinib-resistant BCR-ABL mutants tested to date. Analysis of the crystal structure of dasatinib-bound ABL kinase suggests that the increased binding affinity of dasatinib over imatinib is at least partially due to its ability to recognize multiple states of BCR-ABL. The structure also provides an explanation for the activity of dasatinib against imatinib-resistant BCR-ABL mutants. (Cancer Res 2006; 66(11): 5790-7)

Computational tools can markedly accelerate the rate at which murine genetic models can be analyzed. We developed a computational method for mapping phenotypic traits that vary among inbred strains onto haplotypic blocks. This method correctly predicted the genetic basis for strain-specific differences in several biologically important traits. It was also used to identify an allele-specific functional genomic element regulating H2-Ealpha gene expression. This functional element, which contained the binding sites for YY1 and a second transcription factor that is probably serum response factor, is located within the first intron of the H2-Ealpha gene. This computational method will greatly improve our ability to identify the genetic basis for a variety of phenotypic traits, ranging from qualitative trait information to quantitative gene expression data, which vary among inbred mouse strains.