Dasatinib inhibits the growth of molecularly heterogeneous myeloid leukemias.

PURPOSE: Dasatinib is a dual Src/Abl inhibitor recently approved for Bcr-Abl+ leukemias with resistance or intolerance to prior therapy. Because Src kinases contribute to multiple blood cell functions by triggering a variety of signaling pathways, we hypothesized that their molecular targeting might lead to growth inhibition in acute myeloid leukemia (AML). EXPERIMENTAL DESIGN: We studied growth factor-dependent and growth factor-independent leukemic cell lines, including three cell lines expressing mutants of receptor tyrosine kinases (Flt3 or c-Kit) as well as primary AML blasts for responsiveness to dasatinib. RESULTS: Dasatinib resulted in the inhibition of Src family kinases in all cell lines and blast cells at approximately 1 x 10(-9) mol/L. It also inhibited mutant Flt3 or Kit tyrosine phosphorylation at approximately 1 x 10(-6) mol/L. Mo7e cells expressing the activating mutation (codon 816) of c-Kit were most sensitive to growth inhibition with a GI(50) of 5 x 10(-9) mol/L. Primary AML blast cells exhibited a growth inhibition of \u3c1 x\u3e10(-6) mol/L. Cell lines that showed growth inhibition at approximately 1 x 10(-6) mol/L showed a G(1) cell cycle arrest and correlated with accumulation of p21 and p27 protein. The addition of rapamycin or cytotoxic agents enhanced growth inhibition. Dasatinib also caused the apoptosis of Mo7e cells expressing oncogenic Kit. CONCLUSIONS: Although all of the precise targets for dasatinib are not known, this multikinase inhibitor causes either growth arrest or apoptosis in molecularly heterogeneous AML. The addition of cytotoxic or targeted agents can enhance its effects

Charting the hidden City: Collecting prison social network data

Penologists have long emphasized the importance of studying social relationships among prisoners to understand how people adapt to confinement. While several penological traditions clearly implicate social networks as an explanatory mechanism, network methods have rarely been applied in prison research. We suspect that prison scholars have been slow to incorporate social networks into their research because of the challenges—both real and perceived—of collecting social network data in the prison setting. In this article, we argue that successfully collecting network data from prisoners can be achieved by carefully adapting methods to the peculiarities and constraints of the prison setting. We draw upon experiences from the Prison Inmate Networks Study (PINS) and its associated projects in five Pennsylvania prisons to construct a framework for understanding and overcoming the obstacles to network data collection in prisons

DS_10.1177_0022146518790935 – Supplemental material for Social Networks and Health in a Prison Unit

<p>Supplemental material, DS_10.1177_0022146518790935 for Social Networks and Health in a Prison Unit by Dana L. Haynie, Corey Whichard, Derek Kreager, David Schaefer and Sara Wakefield in Journal of Health and Social Behavior</p

Slowly Produced MicroRNAs Control Protein Levels*

Proteins are the primary agents of function in biological systems, and their levels are critical control elements, reflecting the interplay between transcription, translation, and protein degradation. Here, we consider the role of microRNAs (miRNAs) in the post-transcriptional regulation of protein synthesis. To determine their impact on protein concentration, we constructed a mechanistic model consisting of four state variables and nine kinetic parameters that account for transcript sequestration and degradation via miRNA-mRNA complex formation. Our dynamical model predicts that, even when present in low copy number, miRNAs can exert potent effects on protein concentration. Sensitivity analysis of the steady-state solution indicates that miRNA synthesis commonly acts to fine-tune protein concentrations. However, the same analysis shows that for a small subset of miRNA-mRNA pairs characterized by slowly produced miRNAs, the miRNA synthesis rate is the dominant control element. Our model equations provide a tool to evaluate the importance of particular miRNAs on their target proteins and promote the development of miRNA-based therapies that target proteins associated with cancer, inflammation, and metabolic disorders