Constitutive overexpression and activation of NPM-ALK fusion protein [t(2:5)(p23;q35)] is a key oncogenic event that drives the survival and proliferation of anaplastic large-cell lymphomas (ALCLs). We have identified a highly potent and selective small-molecule ALK inhibitor, NVP-TAE684, which blocked the growth of ALCL-derived and ALK-dependent cell lines with IC 50 values between 2 and 10 nM. NVP-TAE684 treatment resulted in a rapid and sustained inhibition of phosphorylation of NPM-ALK and its downstream effectors and subsequent induction of apoptosis and cell cycle arrest. In vivo , NVP-TAE684 suppressed lymphomagenesis in two independent models of ALK-positive ALCL and induced regression of established Karpas-299 lymphomas. NVP-TAE684 also induced down-regulation of CD30 expression, suggesting that CD30 may be used as a biomarker of therapeutic NPM-ALK kinase activity inhibition.

Rapid quantitative methods for characterizing small molecules, peptides, proteins, or RNAs in a broad array of cellular assays would allow one to discover new biological activities associated with these molecules and also provide a more comprehensive profile of drug candidates early in the drug development process. Here we describe a robotic system, termed the automated compound profiler, capable of both propagating a large number of cell lines in parallel and assaying large collections of molecules simultaneously against a matrix of cellular assays in a highly reproducible manner. To illustrate its utility, we have characterized a set of 1,400 kinase inhibitors in a panel of 35 activated tyrosine-kinasedependent cellular assays in dose-response format in a single experiment. Analysis of the resulting multidimensional dataset revealed subclusters of both inhibitors and kinases with closely correlated activities. The approach also identified activities for the p38 inhibitor BIRB796 and the dual src͞abl inhibitor BMS-354825 and exposed the expected side activities for Glivec͞STI571, including cellular inhibition of c-kit and platelet-derived growth factor receptor. This methodology provides a powerful tool for unraveling the cellular biology and molecular pharmacology of both naturally occurring and synthetic chemical diversity.drug discovery ͉ high-throughput screening ͉ tyrosine kinase T he ability to simultaneously interrogate the activities of a library of molecules against a large panel of cellular assays would provide a rapid efficient means to begin to characterize and correlate the biological properties of both natural and synthetic chemical diversity. For example, libraries of noncoding RNAs, mutant growth factors, small molecule kinase inhibitors, or even existing drugs could be assayed for their potency and selectivity in pathway-based or receptor screens or toxicity and metabolic stability in diverse cell types to discover a new biological activity or optimize the pharmacological properties of a molecule (1-3). Although whole-cell systems represent an attractive milieu to characterize gene and small-molecule function, no robust and systematic method exists to correlate chemical structure and biological activity across a large number of molecules and cellular assays. To address this problem, we have developed an approach that affords rapid cost-effective broad-based cellular profiling in parallel against molecular libraries. An industrial-scale automated compound profiling (ACP) system has been designed, which consists of an automated tissue culture system for propagating cell lines, integrated with a system for automatically performing miniaturized cell-based assays in 384-or 1,536-well microplates. The ACP can rapidly test thousands of arrayed molecules, in replicates, in doseresponse format against hundreds of unique cellular assays in a single experiment.To demonstrate this capability, we focused on the problem of identifying selective small-molecule inhibitors of protein tyrosine kinases. Tyrosine ...

Summary Environmental exposures to chemically heterogeneous endocrine disrupting chemicals (EDCs) mimic or interfere with hormone actions, and negatively impact human health. Despite public interest and the prevalence of EDCs in the environment, methods to mechanistically classify these diverse chemicals in a high throughput (HT) manner have not been actively explored. Here, we describe the use of multi-parametric, HT microscopy-based platforms to examine how a prototypical EDC, Bisphenol A (BPA), and eighteen poorly studied analogs (BPXs), affect estrogen receptor (ER). We show that short exposure to BPA and most BPXs induce ERα and/or ERβ and change levels of target gene transcription. Many BPXs exhibit higher affinity for ERβ and act as ERβ antagonists, while they act largely as agonists or mixed agonists/antagonists on ERα. Finally, despite binding to ERs, some BPXs exhibit lower levels of activity. Our comprehensive view of BPXs activities allows their classification and evaluation of potential harmful effects. The strategy described here used on a large scale basis likely offers a faster, more cost-effective way to identify safer BPA alternatives.

The transforming growth factor β (TGF-β) family of growth factors are key regulators of mammalian development and their dysregulation is implicated in human disease, notably, heritable vasculopathies including Marfan (MFS, OMIM #154700) and Loeys–Dietz syndromes (LDS, OMIM #609192). We described a syndrome presenting at birth with distal arthrogryposis, hypotonia, bifid uvula, a failure of normal post-natal muscle development but no evidence of vascular disease; some of these features overlap with MFS and LDS. A de novo mutation in TGFB3 was identified by exome sequencing. Several lines of evidence indicate the mutation is hypomorphic suggesting that decreased TGF-β signaling from a loss of TGFB3 activity is likely responsible for the clinical phenotype. This is the first example of a mutation in the coding portion of TGFB3 implicated in a clinical syndrome suggesting TGFB3 is essential for both human palatogenesis and normal muscle growth.