ABT-869, a multitargeted receptor tyrosine kinase inhibitor: inhibition of FLT3 phosphorylation and signaling in acute myeloid leukemia

In 15% to 30% of patients with acute myeloid leukemia (AML), aberrant proliferation is a consequence of a juxtamembrane mutation in the FLT3 gene (FMS-like tyrosine kinase 3–internal tandem duplication [FLT3-ITD]), causing constitutive kinase activity. ABT-869 (a multitargeted receptor tyrosine kinase inhibitor) inhibited the phosphorylation of FLT3, STAT5, and ERK, as well as Pim-1 expression in MV-4-11 and MOLM-13 cells (IC_(50) approximately 1-10 nM) harboring the FLT3-ITD. ABT-869 inhibited the proliferation of these cells (IC_(50) = 4 and 6 nM, respectively) through the induction of apoptosis (increased sub-G_(0)/G_1 phase, caspase activation, and PARP cleavage), whereas cells harboring wild-type (wt)–FLT3 were less sensitive. In normal human blood spiked with AML cells, ABT-869 inhibited phosphorylation of FLT3 (IC_(50) approximately 100 nM), STAT5, and ERK, and decreased Pim-1 expression. In methylcellulose-based colony-forming assays, ABT-869 had no significant effect up to 1000 nM on normal hematopoietic progenitor cells, whereas in AML patient samples harboring both FLT3-ITD and wt-FLT3, ABT-869 inhibited colony formation (IC_(50) = 100 and 1000 nM, respectively). ABT-869 dose-dependently inhibited MV-4-11 and MOLM-13 flank tumor growth, prevented tumor formation, regressed established MV-4-11 xenografts, and increased survival by 20 weeks in an MV-4-11 engraftment model. In tumors, ABT-869 inhibited FLT3 phosphorylation, induced apoptosis (transferase-mediated dUTP nick-end labeling [TUNEL]) and decreased proliferation (Ki67). ABT-869 is under clinical development for AML

Reimagining large river management using the Resist–Accept–Direct (RAD) framework in the Upper Mississippi River

Background: Large-river decision-makers are charged with maintaining diverse ecosystem services through unprecedented social-ecological transformations as climate change and other global stressors intensify. The interconnected, dendritic habitats of rivers, which often demarcate jurisdictional boundaries, generate complex management challenges. Here, we explore how the Resist–Accept–Direct (RAD) framework may enhance large-river management by promoting coordinated and deliberate responses to social-ecological trajectories of change. The RAD framework identifies the full decision space of potential management approaches, wherein managers may resist change to maintain historical conditions, accept change toward different conditions, or direct change to a specified future with novel conditions. In the Upper Mississippi River System, managers are facing social-ecological transformations from more frequent and extreme high-water events. We illustrate how RAD-informed basin-, reach-, and site-scale decisions could: (1) provide cross-spatial scale framing; (2) open the entire decision space of potential management approaches; and (3) enhance coordinated inter-jurisdictional management in response to the trajectory of the Upper Mississippi River hydrograph. Results: The RAD framework helps identify plausible long-term trajectories in different reaches (or subbasins) of the river and how the associated social-ecological transformations could be managed by altering site-scale conditions. Strategic reach-scale objectives may reprioritize how, where, and when site conditions could be altered to contribute to the basin goal, given the basin’s plausible trajectories of change (e.g., by coordinating action across sites to alter habitat connectivity, diversity, and redundancy in the river mosaic). Conclusions: When faced with long-term systemic transformations (e.g., \u3e 50 years), the RAD framework helps explicitly consider whether or when the basin vision or goals may no longer be achievable, and direct options may open yet unconsidered potential for the basin. Embedding the RAD framework in hierarchical decision-making clarifies that the selection of actions in space and time should be derived from basin-wide goals and reach-scale objectives to ensure that site-scale actions contribute effectively to the larger river habitat mosaic. Embedding the RAD framework in large-river decisions can provide the necessary conduit to link flexibility and innovation at the site scale with stability at larger scales for adaptive governance of changing social-ecological systems

Identifying monitoring information needs that support the management of fish in large rivers.

Management actions intended to benefit fish in large rivers can directly or indirectly affect multiple ecosystem components. Without consideration of the effects of management on non-target ecosystem components, unintended consequences may limit management efficacy. Monitoring can help clarify the effects of management actions, including on non-target ecosystem components, but only if data are collected to characterize key ecosystem processes that could affect the outcome. Scientists from across the U.S. convened to develop a conceptual model that would help identify monitoring information needed to better understand how natural and anthropogenic factors affect large river fishes. We applied the conceptual model to case studies in four large U.S. rivers. The application of the conceptual model indicates the model is flexible and relevant to large rivers in different geographic settings and with different management challenges. By visualizing how natural and anthropogenic drivers directly or indirectly affect cascading ecosystem tiers, our model identified critical information gaps and uncertainties that, if resolved, could inform how to best meet management objectives. Despite large differences in the physical and ecological contexts of the river systems, the case studies also demonstrated substantial commonalities in the data needed to better understand how stressors affect fish in these systems. For example, in most systems information on river discharge and water temperature were needed and available. Conversely, information regarding trophic relationships and the habitat requirements of larval fishes were generally lacking. This result suggests that there is a need to better understand a set of common factors across large-river systems. We provide a stepwise procedure to facilitate the application of our conceptual model to other river systems and management goals

Gene Expression Signatures for the Accurate Diagnosis of Peripheral T-Cell Lymphoma Entities in the Routine Clinical Practice

Peripheral T-cell lymphoma (PTCL) includes heterogeneous clinicopathologic entities with numerous diagnostic and treatment challenges. We previously defined robust transcriptomic signatures that distinguish common PTCL entities and identified two novel biologic and prognostic PTCL-not otherwise specified subtypes (PTCL-TBX21 and PTCL-GATA3). We aimed to consolidate a gene expression-based subclassification using formalin-fixed, paraffin-embedded (FFPE) tissues to improve the accuracy and precision in PTCL diagnosis. We assembled a well-characterized PTCL training cohort (n = 105) with gene expression profiling data to derive a diagnostic signature using fresh-frozen tissue on the HG-U133plus2.0 platform (Affymetrix, Inc, Santa Clara, CA) subsequently validated using matched FFPE tissues in a digital gene expression profiling platform (nCounter, NanoString Technologies, Inc, Seattle, WA). Statistical filtering approaches were applied to refine the transcriptomic signatures and then validated in another PTCL cohort (n = 140) with rigorous pathology review and ancillary assays. In the training cohort, the refined transcriptomic classifier in FFPE tissues showed high sensitivity (> 80%), specificity (> 95%), and accuracy (> 94%) for PTCL subclassification compared with the fresh-frozen-derived diagnostic model and showed high reproducibility between three independent laboratories. In the validation cohort, the transcriptional classifier matched the pathology diagnosis rendered by three expert hematopathologists in 85% (n = 119) of the cases, showed borderline association with the molecular signatures in 6% (n = 8), and disagreed in 8% (n = 11). The classifier improved the pathology diagnosis in two cases, validated by clinical findings. Of the 11 cases with disagreements, four had a molecular classification that may provide an improvement over pathology diagnosis on the basis of overall transcriptomic and morphological features. The molecular subclassification provided a comprehensive molecular characterization of PTCL subtypes, including viral etiologic factors and translocation partners. We developed a novel transcriptomic approach for PTCL subclassification that facilitates translation into clinical practice with higher precision and uniformity than conventional pathology diagnosis