Cancer presents a difficult challenge for oncologists, as there are few therapies that specifically target disease cells. Existing treatment strategies rely heavily on physical and chemical agents that nonspecifically affect DNA metabolism. To improve the effectiveness of these treatments, we have identified a new class of protein kinase inhibitor that targets a major DNA repair pathway. A representative of this class, 1-(2-hydroxy-4-morpholin-4-yl-phenyl)-ethanone, inhibits the DNA-dependent protein kinase (DNA-PK) and differs significantly from previously studied DNA-PK inhibitors both structurally and functionally. DNA-PK participates in the cellular response to and repair of chromosomal DNA double-strand breaks (DSBs). These new selective inhibitors recapitulate the phenotype of DNA-PK defective cell lines including those from SCID mice. These compounds directly inhibit the repair of DNA DSBs and consequently enhance the cytotoxicity of physical and chemical agents that induce DSBs but not other DNA lesions. In contrast to previously studied DNA-PK inhibitors, these compounds appear benign, exhibiting no toxic effects in the absence of DSB-inducing treatments. Most importantly, 1-(2-hydroxy-4-morpholin-4-yl-phenyl)-ethanone synergistically enhances radiation-induced tumor control in a mouse-human xenograft assay. These studies validate DNA-PK as a cancer drug target and suggest a new approach for enhancing the effects of existing cancer therapies.
Non-human primates may be the only relevant species for pharmacology or toxicology studies of certain biologics, due to lack of activity in other species. Flow cytometry immunophenotyping is often included as a minimally invasive adjunct to standard toxicity testing. A retrospective inter-laboratory analysis was conducted to assess counts and variability of the main cell types monitored in toxicity studies, and to provide guidance for conduct and interpretation of immunophenotyping assessments in cynomolgus monkeys. Univariate and multivariate models were developed. Study design factors influencing cell counts and variability were identified and a power analysis was performed. Pre-study and on-study counts were generally similar; longitudinal analysis showed little drift in mean counts or within-animal variability over time. Within-animal variability was lower than inter-animal variability. Gender was associated with small but significant differences in mean counts and variability. Age was associated with significant differences in variability. Immunophenotype definitions were associated with significant differences in mean counts and within-animal variability for most cell types. Power analysis for groups of 6–8 animals showed that differences of ≈50% in counts of T-cells, T-cell subsets, and B-cells compared to pre-treatment values may be detected; for NK cells and monocytes, differences of ≈60–90% may be detected. This review yields some general points to consider for immunophenotyping studies, i.e. (a) analysis of log-transformed cell count data and comparisons using each animal as its own reference will improve ability to detect changes, (b) the magnitude of change detectable given study group size should be considered, (c) multiplication of sampling timepoints during a study seems unnecessary, (d) consideration should be given to using only one gender, when applicable, to increase power while minimizing animal usage, and (e) the choice of immunophenotype has impacts on cell counts and variability.
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