Both the timing and molecular determinants of metastasis are unknown, hindering treatment and prevention efforts. Here we characterize the evolutionary dynamics of this lethal process by analyzing exome sequencing data from 118 biopsies from 23 colorectal cancer (CRC) patients Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:

One of the major challenges facing researchers studying complex biological systems is integration of data from -omics platforms. Omic-scale data include DNA variations, transcriptom profiles, and RAomics. Selection of an appropriate approach for a data-integration task is problem dependent, primarily dictated by the information contained in the data. In situations where modeling of multiple raw datasets jointly might be extremely challenging due to their vast differences, rankings from each dataset would provide a commonality based on which results could be integrated. Aggregation of microRNA targets predicted from different computational algorithms is such a problem. Integration of results from multiple mRNA studies based on different platforms is another example that will be discussed. Formulating the problem of integrating ranked lists as minimizing an objective criterion, we explore the usage of a cross entropy Monte Carlo method for solving such a combinatorial problem. Instead of placing a discrete uniform distribution on all the potential solutions, an iterative importance sampling technique is utilized "to slowly tighten the net" to place most distributional mass on the optimal solution and its neighbors. Extensive simulation studies were performed to assess the performance of the method. With satisfactory simulation results, the method was applied to the microRNA and mRNA problems to illustrate its utility.

Vascular hypercontractile responses to norepinephrine in DS hypertensive rats can, in part, be explained by an impairment in endothelial nitric oxide production.

Nephropathic cystinosis is an autosomal recessive metabolic, lifelong disease characterized by lysosomal cystine accumulation throughout the body that commonly presents in infancy with a renal Fanconi syndrome and, if untreated, leads to end-stage kidney disease (ESKD) in the later childhood years. The molecular basis is due to mutations in CTNS, the gene encoding for the lysosomal cystine-proton cotransporter, cystinosin. During adolescence and adulthood, extrarenal manifestations of cystinosis develop and require multidisciplinary care. Despite substantial improvement in prognosis due to cystine-depleting therapy with cysteamine, no cure of the disease is currently available. Kidney Disease: Improving Global Outcomes (KDIGO) convened a Controversies Conference on cystinosis to review the state-of-the-art knowledge and to address areas of controversies in pathophysiology, diagnostics, monitoring, and treatment in different age groups. More importantly, promising areas of investigation that may lead to optimal outcomes for patients afflicted with this lifelong, systemic disease were discussed with a research agenda proposed for the future.

Genomic changes observed across treatment may result from either clonal evolution or geographically disparate sampling of heterogeneous tumors. Here we use computational modeling based on analysis of fifteen primary breast tumors and find that apparent clonal change between two tumor samples can frequently be explained by pre-treatment heterogeneity, such that at least two regions are necessary to detect treatment-induced clonal shifts. To assess for clonal replacement, we devise a summary statistic based on whole-exome sequencing of a pre-treatment biopsy and multi-region sampling of the post-treatment surgical specimen and apply this measure to five breast tumors treated with neoadjuvant HER2-targeted therapy. Two tumors underwent clonal replacement with treatment, and mathematical modeling indicates these two tumors had resistant subclones prior to treatment and rates of resistance-related genomic changes that were substantially larger than previous estimates. Our results provide a needed framework to incorporate primary tumor heterogeneity in investigating the evolution of resistance.

High-throughput sequencing techniques are increasingly affordable and produce massive amounts of data. Together with other high-throughput technologies, such as microarrays, there are an enormous amount of resources in databases. The collection of these valuable data has been routine for more than a decade. Despite different technologies, many experiments share the same goal. For instance, the aims of RNA-seq studies often coincide with those of differential gene expression experiments based on microarrays. As such, it would be logical to utilize all available data. However, there is a lack of biostatistical tools for the integration of results obtained from different technologies. Although diverse technological platforms produce different raw data, one commonality for experiments with the same goal is that all the outcomes can be transformed into a platform-independent data format -rankings -for the same set of items. Here we present the R package TopKLists, which allows for statistical inference on the lengths of informative (top-k) partial lists, for stochastic aggregation of full or partial lists, and for graphical exploration of the input and consolidated output. A graphical user interface has also been implemented for providing access to the underlying algorithms. To illustrate the applicability and usefulness of the package, we integrated microRNA data of non-small cell lung cancer across different measurement techniques and draw conclusions. The package can be obtained from CRAN under a LGPL-3 license.

A series of 6-hetaryloxy benzoxaborole compounds was designed and synthesized for a structure–activity relationship (SAR) investigation to assess the changes in antimalarial activity which result from 6-aryloxy structural variation, substituent modification on the pyrazine ring, and optimization of the side chain ester group. This SAR study discovered highly potent 6-(2-(alkoxycarbonyl)pyrazinyl-5-oxy)-1,3-dihydro-1-hydroxy-2,1-benzoxaboroles (9, 27–34) with IC50s = 0.2–22 nM against cultured Plasmodium falciparum W2 and 3D7 strains. Compound 9 also demonstrated excellent in vivo efficacy against P. berghei in infected mice (ED90 = 7.0 mg/kg).

We previously reported that inhibition of Rho-kinase (ROCK) by hydroxyl fasudil improves cognitive deficit and neuronal damage in rats with chronic cerebral ischemia (Huang et al., Cell Mol Neurobiol 28:757-768, 2008). In this study, fasudil mesylate (FM) was investigated for its neuroprotective potential in rats with ischemia following middle cerebral artery occlusion (MCAO) and reperfusion. The effect of fasudil mesylate was also studied in rat brain cortical and hippocampal slices treated with oxygen-glucose deprivation (OGD) injury. Gross anatomy showed that cerebral infarct size, measured with 2,3,5-triphenyltetrazolium chloride (TTC) staining, was significantly smaller in the FM-treated than in the non-FM-treated ischemic rats. In the brain regions vulnerable to ischemia of ischemic rats, fasudil mesylate was also found to significantly restore the enzyme protein expression level of endothelial nitric oxide synthase (eNOS), which was decreased in ischemia. However, it remarkably reduced the protein synthesis of inducible nitric oxide synthase (iNOS) that was induced by ischemia and reperfusion. In rat brain slices treated with OGD injury, fasudil mesylate increased the neuronal cell viability by 40% for cortex and by 61% for hippocampus, respectively. Finally, in the presence of OGD and fasudil mesylate, superoxide dismutase (SOD) activity was increased by 50% for cortex and by 58% for hippocampus, compared to OGD only group. In conclusion, our in vivo study showed that fasudil mesylate not only decreased neurological deficit but also reduced cerebral infarct size, possibly and at least partially by augmenting eNOS protein expression and inhibiting iNOS protein expression after ischemia-reperfusion.