Pro-neural transcription factors as cancer markers.

BACKGROUND: The aberrant transcription in cancer of genes normally associated with embryonic tissue differentiation at various organ sites may be a hallmark of tumour progression. For example, neuroendocrine differentiation is found more commonly in cancers destined to progress, including prostate and lung. We sought to identify proteins which are involved in neuroendocrine differentiation and differentially expressed in aggressive/metastatic tumours. RESULTS: Expression arrays were used to identify up-regulated transcripts in a neuroendocrine (NE) transgenic mouse model of prostate cancer. Amongst these were several genes normally expressed in neural tissues, including the pro-neural transcription factors Ascl1 and Hes6. Using quantitative RT-PCR and immuno-histochemistry we showed that these same genes were highly expressed in castrate resistant, metastatic LNCaP cell-lines. Finally we performed a meta-analysis on expression array datasets from human clinical material. The expression of these pro-neural transcripts effectively segregates metastatic from localised prostate cancer and benign tissue as well as sub-clustering a variety of other human cancers. CONCLUSION: By focussing on transcription factors known to drive normal tissue development and comparing expression signatures for normal and malignant mouse tissues we have identified two transcription factors, Ascl1 and Hes6, which appear effective markers for an aggressive phenotype in all prostate models and tissues examined. We suggest that the aberrant initiation of differentiation programs may confer a selective advantage on cells in all contexts and this approach to identify biomarkers therefore has the potential to uncover proteins equally applicable to pre-clinical and clinical cancer biology.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Identification of synthetic lethality of PRKDC in MYC-dependent human cancers by pooled shRNA screening

BACKGROUND: MYC family members are among the most frequently deregulated oncogenes in human cancers, yet direct therapeutic targeting of MYC in cancer has been challenging thus far. Synthetic lethality provides an opportunity for therapeutic intervention of MYC-driven cancers. METHODS: A pooled kinase shRNA library screen was performed and next-generation deep sequencing efforts identified that PRKDC was synthetically lethal in cells overexpressing MYC. Genes and proteins of interest were knocked down or inhibited using RNAi technology and small molecule inhibitors, respectively. Quantitative RT-PCR using TaqMan probes examined mRNA expression levels and cell viability was assessed using CellTiter-Glo (Promega). Western blotting was performed to monitor different protein levels in the presence or absence of RNAi or compound treatment. Statistical significance of differences among data sets were determined using unpaired t test (Mann-Whitney test) or ANOVA. RESULTS: Inhibition of PRKDC using RNAi (RNA interference) or small molecular inhibitors preferentially killed MYC-overexpressing human lung fibroblasts. Moreover, inducible PRKDC knockdown decreased cell viability selectively in high MYC-expressing human small cell lung cancer cell lines. At the molecular level, we found that inhibition of PRKDC downregulated MYC mRNA and protein expression in multiple cancer cell lines. In addition, we confirmed that overexpression of MYC family proteins induced DNA double-strand breaks; our results also revealed that PRKDC inhibition in these cells led to an increase in DNA damage levels. CONCLUSIONS: Our data suggest that the synthetic lethality between PRKDC and MYC may in part be due to PRKDC dependent modulation of MYC expression, as well as MYC-induced DNA damage where PRKDC plays a key role in DNA damage repair

Sensory Neuron-Specific GPCR Mrgprs Are Itch Receptors Mediating Chloroquine-Induced Pruritus

The cellular and molecular mechanisms mediating histamine-independent itch in primary sensory neurons are largely unknown. Itch induced by chloroquine (CQ) is a common side effect of this widely used antimalarial drug. Here, we show that Mrgprs, a family of G protein-coupled receptors expressed exclusively in peripheral sensory neurons, function as itch receptors. Mice lacking a cluster of Mrgpr genes display significant deficits in itch induced by CQ but not histamine. CQ directly excites sensory neurons in an Mrgpr-dependent manner. CQ specifically activates mouse MrgprA3 and human MrgprX1. Loss- and gain-of-function studies demonstrate that MrgprA3 is required for CQ responsiveness in mice. Furthermore, MrgprA3-expressing neurons respond to histamine and coexpress gastrin-releasing peptide, a peptide involved in itch sensation, and MrgprC11. Activation of these neurons with the MrgprC11-specific agonist BAM8-22 induces itch in wild-type but not mutant mice. Therefore, Mrgprs may provide molecular access to itch-selective neurons and constitute novel targets for itch therapeutics

Using a Machine Learning Method to Predict the Penetration Depth of a Gravity Corer

The study of penetration depth of gravity piston samplers has an essential impact on sampling efficiency and instrument safety. This study focuses on predicting penetration depth based on the characteristic parameters of the sampled seafloor sediments and the sampler parameters. Although numerous studies of gravity corer penetration depth have been carried out, most have been based on the energy conservation equation, which considers a varying number of influencing factors. Furthermore, most research has focused on the same research idea of finding analytical solutions. The present study proposes a new approach to predicting gravity corer penetration depth based on a machine learning method that uses real sampling data from the sea and experimental data from a gravity sampling physical model for training and testing. Experimental results indicate that the machine learning model can accurately predict gravity corer penetration depth. Moreover, predictions were made for the same penetration conditions using the machine learning model and three other analytical solution models. Results show that the prediction accuracy of machine learning outperforms that of the analytical prediction model under various statistical rubrics. This study demonstrates the capacity of the proposed machine learning model and provides civil engineers with an effective tool to predict the penetration depth of gravity corers

Using a Machine Learning Method to Predict the Penetration Depth of a Gravity Corer

The study of penetration depth of gravity piston samplers has an essential impact on sampling efficiency and instrument safety. This study focuses on predicting penetration depth based on the characteristic parameters of the sampled seafloor sediments and the sampler parameters. Although numerous studies of gravity corer penetration depth have been carried out, most have been based on the energy conservation equation, which considers a varying number of influencing factors. Furthermore, most research has focused on the same research idea of finding analytical solutions. The present study proposes a new approach to predicting gravity corer penetration depth based on a machine learning method that uses real sampling data from the sea and experimental data from a gravity sampling physical model for training and testing. Experimental results indicate that the machine learning model can accurately predict gravity corer penetration depth. Moreover, predictions were made for the same penetration conditions using the machine learning model and three other analytical solution models. Results show that the prediction accuracy of machine learning outperforms that of the analytical prediction model under various statistical rubrics. This study demonstrates the capacity of the proposed machine learning model and provides civil engineers with an effective tool to predict the penetration depth of gravity corers

Pro-neural transcription factors as cancer markers.

BACKGROUND: The aberrant transcription in cancer of genes normally associated with embryonic tissue differentiation at various organ sites may be a hallmark of tumour progression. For example, neuroendocrine differentiation is found more commonly in cancers destined to progress, including prostate and lung. We sought to identify proteins which are involved in neuroendocrine differentiation and differentially expressed in aggressive/metastatic tumours. RESULTS: Expression arrays were used to identify up-regulated transcripts in a neuroendocrine (NE) transgenic mouse model of prostate cancer. Amongst these were several genes normally expressed in neural tissues, including the pro-neural transcription factors Ascl1 and Hes6. Using quantitative RT-PCR and immuno-histochemistry we showed that these same genes were highly expressed in castrate resistant, metastatic LNCaP cell-lines. Finally we performed a meta-analysis on expression array datasets from human clinical material. The expression of these pro-neural transcripts effectively segregates metastatic from localised prostate cancer and benign tissue as well as sub-clustering a variety of other human cancers. CONCLUSION: By focussing on transcription factors known to drive normal tissue development and comparing expression signatures for normal and malignant mouse tissues we have identified two transcription factors, Ascl1 and Hes6, which appear effective markers for an aggressive phenotype in all prostate models and tissues examined. We suggest that the aberrant initiation of differentiation programs may confer a selective advantage on cells in all contexts and this approach to identify biomarkers therefore has the potential to uncover proteins equally applicable to pre-clinical and clinical cancer biology.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Detection and Organ-Specific Ablation of Neuroendocrine Cells by <i>Synaptophysin</i> Locus-Based BAC Cassette in Transgenic Mice

<div><p>The role of cells of the diffuse neuroendocrine system in development and maintenance of individual organs and tissues remains poorly understood. Here we identify a regulatory region sufficient for accurate <i>in vivo</i> expression of synaptophysin (SYP), a common marker of neuroendocrine differentiation, and report generation of Tg(<i>Syp-EGFP^loxP-DTA)147^Ayn</i> (<i>SypELDTA</i>) mice suitable for flexible organ-specific ablation of neuroendocrine cells. These mice express EGFP and diphtheria toxin fragment A (DTA) in SYP positive cells before and after Cre-<i>loxP</i> mediated recombination, respectively. As a proof of principle, we have crossed <i>SypELDTA</i> mice with <i>EIIA-Cre</i> and <i>PB-Cre4</i> mice. <i>EIIA-Cre</i> mice express Cre recombinase in a broad range of tissues, while <i>PB-Cre4</i> mice specifically express Cre recombinase in the prostate epithelium. Double transgenic <i>EIIA-Cre; SypELDTA</i> embryos exhibited massive cell death in SYP positive cells. At the same time, <i>PB-Cre4; SypELDTA</i> mice showed a substantial decrease in the number of neuroendocrine cells and associated prostate hypotrophy. As no increase in cell death and/or Cre-<i>loxP</i> mediated recombination was observed in non-neuroendocrine epithelium cells, these results suggest that neuroendocrine cells play an important role in prostate development. High cell type specificity of <i>Syp</i> locus-based cassette and versatility of generated mouse model should assure applicability of these resources to studies of neuroendocrine cell functions in various tissues and organs.</p></div

Powder metallurgy processed metal-matrix friction materials for space applications

Abstract Owing to the increasing demand for tribological brakes for space applications, the development of novel materials and advanced technologies is necessary. This paper presents the design, characterization, and realization of powder metallurgy processed metal-matrix friction materials intended for the above-mentioned tribological brakes. Selecting appropriate ingredients, which provides an effective way to tailor the properties of the friction material, is evolving as a strategy to meet the design requirements. The tribological behaviors of the friction material are experimentally investigated under different conditions, and special attention is focused on the vacuum tribology. Examinations and analyses of the friction surface and subsurface corroborate the wear mechanism. In addition, the erosion resistances of the friction material are evaluated by exposure tests of ultraviolet irradiation and atomic oxygen. Finally, present and potential space applications of the friction material are also introduced based on experimental studies

Genomic structure of the <i>Syp</i> gene.

<p>(A) Location of the <i>Syp</i> locus on mouse, rat, and human chromosome X. Mouse <i>Syp</i> contains 7 exons (black boxes). The translation initiation codon, ATG, is located in the first exon. The <i>NRSE</i> is located within the first intron of <i>Syp</i>. (B) Sequence comparison of the <i>NRSE</i> derived from <i>Syp</i> across species.</p

<i>EIIA-Cre; SypELDTA</i> embyros exhibit massive cell death in SYP positive cells.

<p>(A) Design of crosses between male <i>SypELDTA</i> and female <i>EIIA-Cre</i> transgenic mice. (B-M) SYP (B, D, F, H, J, L) and cleaved Caspase-3 (C, E, G, I, K, M) expression (arrows) in serial sections of <i>EIIA-Cre; SypELDTA</i> (B-G) and <i>EIIA-Cre</i> (H-M) embryos collected on gestational day 10.5. High (D-G, J-M) magnification images of brain (D, E, J, K) and dorsal root ganglion (F, G,L, M) regions shown as rectangles in low magnification images (B, C, H, I). b, brain, g, dorsal root ganglia. ABC Elite method. Hematoxylin counterstaining. Calibration bar: 950 µm (B, C, H, I), 50 µm (D-G, J-M).</p