98 research outputs found

    Identification and characterization of small-molecule inhibitors of hepsin.

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    Hepsin is a type II transmembrane serine protease overexpressed in the majority of human prostate cancers. We recently demonstrated that hepsin promotes prostate cancer progression and metastasis and thus represents a potential therapeutic target. Here we report the identification of novel small-molecule inhibitors of hepsin catalytic activity. We utilized purified human hepsin for high-throughput screening of established drug and chemical diversity libraries and identified sixteen inhibitory compounds with IC(50) values against hepsin ranging from 0.23-2.31 microM and relative selectivity of up to 86-fold or greater. Two compounds are orally administered drugs established for human use. Four compounds attenuated hepsin-dependent pericellular serine protease activity in a dose dependent manner with limited or no cytotoxicity to a range of cell types. These compounds may be used as leads to develop even more potent and specific inhibitors of hepsin to prevent prostate cancer progression and metastasis

    Neural Reconstruction Integrity: A Metric for Assessing the Connectivity Accuracy of Reconstructed Neural Networks

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    Neuroscientists are actively pursuing high-precision maps, or graphs consisting of networks of neurons and connecting synapses in mammalian and non-mammalian brains. Such graphs, when coupled with physiological and behavioral data, are likely to facilitate greater understanding of how circuits in these networks give rise to complex information processing capabilities. Given that the automated or semi-automated methods required to achieve the acquisition of these graphs are still evolving, we developed a metric for measuring the performance of such methods by comparing their output with those generated by human annotators (“ground truth” data). Whereas classic metrics for comparing annotated neural tissue reconstructions generally do so at the voxel level, the metric proposed here measures the “integrity” of neurons based on the degree to which a collection of synaptic terminals belonging to a single neuron of the reconstruction can be matched to those of a single neuron in the ground truth data. The metric is largely insensitive to small errors in segmentation and more directly measures accuracy of the generated brain graph. It is our hope that use of the metric will facilitate the broader community's efforts to improve upon existing methods for acquiring brain graphs. Herein we describe the metric in detail, provide demonstrative examples of the intuitive scores it generates, and apply it to a synthesized neural network with simulated reconstruction errors. Demonstration code is available

    Neural Reconstruction Integrity: A Metric for Assessing the Connectivity Accuracy of Reconstructed Neural Networks

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    Neuroscientists are actively pursuing high-precision maps, or graphs consisting of networks of neurons and connecting synapses in mammalian and non-mammalian brains. Such graphs, when coupled with physiological and behavioral data, are likely to facilitate greater understanding of how circuits in these networks give rise to complex information processing capabilities. Given that the automated or semi-automated methods required to achieve the acquisition of these graphs are still evolving, we developed a metric for measuring the performance of such methods by comparing their output with those generated by human annotators (“ground truth” data). Whereas classic metrics for comparing annotated neural tissue reconstructions generally do so at the voxel level, the metric proposed here measures the “integrity” of neurons based on the degree to which a collection of synaptic terminals belonging to a single neuron of the reconstruction can be matched to those of a single neuron in the ground truth data. The metric is largely insensitive to small errors in segmentation and more directly measures accuracy of the generated brain graph. It is our hope that use of the metric will facilitate the broader community's efforts to improve upon existing methods for acquiring brain graphs. Herein we describe the metric in detail, provide demonstrative examples of the intuitive scores it generates, and apply it to a synthesized neural network with simulated reconstruction errors. Demonstration code is available

    Microguards and micromessengers of the genome

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    The regulation of gene expression is of fundamental importance to maintain organismal function and integrity and requires a multifaceted and highly ordered sequence of events. The cyclic nature of gene expression is known as ‘transcription dynamics’. Disruption or perturbation of these dynamics can result in significant fitness costs arising from genome instability, accelerated ageing and disease. We review recent research that supports the idea that an important new role for small RNAs, particularly microRNAs (miRNAs), is in protecting the genome against short-term transcriptional fluctuations, in a process we term ‘microguarding’. An additional emerging role for miRNAs is as ‘micromessengers’—through alteration of gene expression in target cells to which they are trafficked within microvesicles. We describe the scant but emerging evidence that miRNAs can be moved between different cells, individuals and even species, to exert biologically significant responses. With these two new roles, miRNAs have the potential to protect against deleterious gene expression variation from perturbation and to themselves perturb the expression of genes in target cells. These interactions between cells will frequently be subject to conflicts of interest when they occur between unrelated cells that lack a coincidence of fitness interests. Hence, there is the potential for miRNAs to represent both a means to resolve conflicts of interest, as well as instigate them. We conclude by exploring this conflict hypothesis, by describing some of the initial evidence consistent with it and proposing new ideas for future research into this exciting topic

    Comprehensive microRNA profiling in acetaminophen toxicity identifies novel circulating biomarkers for human liver and kidney injury

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    Our objective was to identify microRNA (miRNA) biomarkers of drug-induced liver and kidney injury by profiling the circulating miRNome in patients with acetaminophen overdose. Plasma miRNAs were quantified in age- and sex-matched overdose patients with (N=27) and without (N=27) organ injury (APAP-TOX and APAP-no TOX, respectively). Classifier miRNAs were tested in a separate cohort (N=81). miRNA specificity was determined in non-acetaminophen liver injury and murine models. Sensitivity was tested by stratification of patients at hospital presentation (N=67). From 1809 miRNAs, 75 were 3-fold or more increased and 46 were 3-fold or more decreased with APAP-TOX. A 16 miRNA classifier model accurately diagnosed APAP-TOX in the test cohort. In humans, the miRNAs with the largest increase (miR-122-5p, miR-885-5p, miR-151a-3p) and the highest rank in the classifier model (miR-382-5p) accurately reported non-acetaminophen liver injury and were unaffected by kidney injury. miR-122-5p was more sensitive than ALT for reporting liver injury at hospital presentation, especially combined with miR-483-3p. A miRNA panel was associated with human kidney dysfunction. In mice, miR-122-5p, miR-151a-3p and miR-382-5p specifically reported APAP toxicity - being unaffected by drug-induced kidney injury. Profiling of acetaminophen toxicity identified multiple miRNAs that report acute liver injury and potential biomarkers of drug-induced kidney injury

    Relationship between circulating microRNA-30c with total- and LDL-cholesterol, their circulatory transportation and effect of statins

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    Background: Small non-coding microRNAs (miR) have important regulatory roles and are used as biomarkers of disease. We investigated the relationship between lipoproteins and circulating miR-30c, evaluated how they are transported in circulation and determined whether statins altered the circulating concentration of miR-30c. Methods: To determine the relationship between lipoproteins and circulating miR-30c, serum samples from 79 subjects recruited from a lipid clinic were evaluated. Ultracentrifugation and nanoparticle tracking analysis was used to evaluate the transportation of miR-30c in the circulation by lipoproteins and extracellular vesicles in three healthy volunteers. Using archived samples from previous studies, the effects of 40 mg rosuvastatin (n = 22) and 40 mg pravastatin (n = 24) on miR-30c expression was also examined. RNA extraction, reverse transcription-quantitative real-time polymerase chain reaction was carried out using standard procedures. Results: When stratified according to total cholesterol concentration, there was increased miR-30c expression in the highest compared to the lowest tertile (p = 0.035). There was significant positive correlation between miR- 30c and total- (r = 0.367; p = 0.002) and LDL-cholesterol (r = 0.391; p = 0.001). We found that miR-30c was transported in both exosomes and on HDL3. There was a 3.8-fold increased expression of circulating miR-30c after pravastatin treatment for 1 year (p = 0.005) but no significant change with atorvastatin after 8 weeks (p = 0.145). Conclusions: This study shows for the first-time in humans that circulating miR-30c is significantly, positively correlated with total- and LDL-cholesterol implicating regulatory functions in lipid homeostasis. We show miR-30c is transported in both exosomes and on HDL3 and pravastatin therapy significantly increased circulating miR-30c expression adding to the pleiotropic dimensions of statins

    Detection of circulating miRNAs : comparative analysis of extracellular vesicle-incorporated miRNAs and cell-free miRNAs in whole plasma of prostate cancer patients

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    Funding Information: This study was supported by the Norwegian Financial Mechanism 2009–2014 under Project Contract No NFI/R/2014/045. The funding body had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript. Publisher Copyright: © 2017 The Author(s).Background: Circulating cell-free miRNAs have emerged as promising minimally-invasive biomarkers for early detection, prognosis and monitoring of cancer. They can exist in the bloodstream incorporated into extracellular vesicles (EVs) and ribonucleoprotein complexes. However, it is still debated if EVs contain biologically meaningful amounts of miRNAs and may provide a better source of miRNA biomarkers than whole plasma. The aim of this study was to systematically compare the diagnostic potential of prostate cancer-associated miRNAs in whole plasma and in plasma EVs. Methods: RNA was isolated from whole plasma and plasma EV samples from a well characterised cohort of 50 patient with prostate cancer (PC) and 22 patients with benign prostatic hyperplasia (BPH). Nine miRNAs known to have a diagnostic potential for PC in cell-free blood were quantified by RT-qPCR and the relative quantities were compared between patients with PC and BPH and between PC patients with Gleason score ≥ 8 and ≤6. Results: Only a small fraction of the total cell-free miRNA was recovered from the plasma EVs, however the EV-incorporated and whole plasma cell-free miRNA profiles were clearly different. Four of the miRNAs analysed showed a diagnostic potential in our patient cohort. MiR-375 could differentiate between PC and BPH patients when analysed in the whole plasma, while miR-200c-3p and miR-21-5p performed better when analysed in plasma EVs. EV-incorporated but not whole plasma Let-7a-5p level could distinguish PC patients with Gleason score ≥ 8 vs ≤6. Conclusions: This study demonstrates that for some miRNA biomarkers EVs provide a more consistent source of RNA than whole plasma, while other miRNAs show better diagnostic performance when tested in the whole plasma.publishersversionPeer reviewe

    Diagnostic, prognostic and predictive value of cell-free miRNAs in prostate cancer : A systematic review

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    Publisher Copyright: © 2016 Endzeliņš et al.Prostate cancer, the second most frequently diagnosed cancer in males worldwide, is estimated to be diagnosed in 1.1 million men per year. Introduction of PSA testing substantially improved early detection of prostate cancer, however it also led to overdiagnosis and subsequent overtreatment of patients with an indolent disease. Treatment outcome and management of prostate cancer could be improved by the development of non-invasive biomarker assays that aid in increasing the sensitivity and specificity of prostate cancer screening, help to distinguish aggressive from indolent disease and guide therapeutic decisions. Prostate cancer cells release miRNAs into the bloodstream, where they exist incorporated into ribonucleoprotein complexes or extracellular vesicles. Later, cell-free miRNAs have been found in various other biofluids. The initial RNA sequencing studies suggested that most of the circulating cell-free miRNAs in healthy individuals are derived from blood cells, while specific disease-associated miRNA signatures may appear in the circulation of patients affected with various diseases, including cancer. This raised a hope that cell-free miRNAs may serve as non-invasive biomarkers for prostate cancer. Indeed, a number of cell-free miRNAs that potentially may serve as diagnostic, prognostic or predictive biomarkers have been discovered in blood or other biofluids of prostate cancer patients and need to be validated in appropriately designed longitudinal studies and clinical trials. In this review, we systematically summarise studies investigating cell-free miRNAs in biofluids of prostate cancer patients and discuss the utility of the identified biomarkers in various clinical scenarios. Furthermore, we discuss the possible mechanisms of miRNA release into biofluids and outline the biological questions and technical challenges that have arisen from these studies.publishersversionPeer reviewe
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