Chronophin regulates active vitamin B6 levels and transcriptomic features of glioblastoma cell lines cultured under non-adherent, serum-free conditions

Background: The phosphatase chronophin (CIN/PDXP) has been shown to be an important regulator of glioma cell migration and invasion. It has two known substrates: p-Ser3-cofilin, the phosphorylated form of the actin binding protein cofilin, and pyridoxal 5′-phosphate, the active form of vitamin B6. Phosphoregulation of cofilin, among other functions, plays an important role in cell migration, whereas active vitamin B6 is a cofactor for more than one hundred enzymatic reactions. The role of CIN has yet only been examined in glioblastoma cell line models derived under serum culture conditions. Results: We found that CIN is highly expressed in cells cultured under non-adherent, serum-free conditions that are thought to better mimic the in vivo situation. Furthermore, the substrates of CIN, p-Ser3-cofilin and active vitamin B6, were significantly reduced as compared to cell lines cultured in serum-containing medium. To further examine its molecular role we stably knocked down the CIN protein with two different shRNA hairpins in the glioblastoma cell lines NCH421k and NCH644. Both cell lines did not show any significant alterations in proliferation but expression of differentiation markers (such as GFAP or TUBB3) was increased in the knockdown cell lines. In addition, colony formation was significantly impaired in NCH644. Of note, in both cell lines CIN knockdown increased active vitamin B6 levels with vitamin B6 being known to be important for S-adenosylmethionine biosynthesis. Nevertheless, global histone and DNA methylation remained unaltered as was chemoresistance towards temozolomide. To further elucidate the role of phosphocofilin in glioblastoma cells we applied inhibitors for ROCK1/2 and LIMK1/2 to our model. LIMK- and ROCK-inhibitor treatment alone was not toxic for glioblastoma cells. However, it had profound, but antagonistic effects in NCH421k and NCH644 under chemotherapy. Conclusion: In non-adherent glioblastoma cell lines cultured in serum-free medium, chronophin knockdown induces phenotypic changes, e.g. in colony formation and transcription, but these are highly dependent on the cellular background. The same is true for phenotypes observed after treatment with inhibitors for kinases regulating cofilin phosphorylation (ROCKs and LIMKs). Targeting the cofilin phosphorylation pathway might therefore not be a straightforward therapeutic option in glioblastoma

Resonances in an external field: the 1+1 dimensional case

Using non-relativistic effective field theory in 1+1 dimensions, we generalize Luescher's approach for resonances in the presence of an external field. This generalized approach provides a framework to study the infinite-volume limit of the form factor of a resonance determined in lattice simulations.Comment: 13 pages, 2 postscript figure

Computational polymorph screening reveals late-appearing and poorly-soluble form of rotigotine

The active pharmaceutical ingredient rotigotine—a dopamine agonist for the treatment of Parkinson’s and restless leg diseases—was known to exist in only one polymorphic form since 1985. In 2008, the appearance of a thermodynamically more stable and significantly less soluble polymorph led to a massive batch recall followed by economic and public health implications. Here, we carry out state-of-the-art computational crystal structure prediction, revealing the late-appearing polymorph without using any prior information. In addition, we predict a third crystalline form of rotigotine having thermodynamic stability between forms I and II. We provide quantitative description of the relative stability and solubility of the rotigotine polymorphs. Our study offers new insights into a challenging polymorphic system and highlights the robustness of contemporary computational crystal structure prediction during pharmaceutical development

Frequent Epigenetic Inactivation of DIRAS-1 and DIRAS-2 Contributes to Chemo-Resistance in Gliomas

We previously reported that DIRAS-3 is frequently inactivated in oligodendrogliomas due to promoter hypermethylation and loss of the chromosomal arm 1p. DIRAS-3 inactivation was associated with better overall survival. Consequently, we now investigated regulation and function of its family members DIRAS-1 and DIRAS-2. We found that DIRAS-1 was strongly downregulated in 65% and DIRAS-2 in 100% of analyzed glioma samples compared to non-neoplastic brain tissue (NNB). Moreover, a significant down-regulation of DIRAS-1 and -2 was detected in glioma data obtained from the TCGA database. Mutational analyses did not reveal any inactivating mutations in the DIRAS-1 and -2 coding regions. Analysis of the DIRAS-1 and -2 promoter methylation status showed significantly higher methylation in IDH-mutant astrocytic and IDH-mutant and 1p/19q-codeleted oligodendroglial tumors compared to NNB. Treatment of U251MG and Hs683 glioblastoma cells lines with 5-azacytidine led to significant re-expression of DIRAS-1 and -2. For IDH-wild-type primary gliomas, however, we did not observe significantly elevated DIRAS-1 and -2 promoter methylation levels, but still detected strong downregulation of both DIRAS family members. Additional analyses revealed that DIRAS-1 and -2 expression was also regulated by histone modifications. We observed a shift towards promoter heterochromatinization for DIRAS-1 and less promoter euchromatinization for DIRAS-2 in IDH-wild-type glioblastomas compared to controls. Treatment of the two glioblastoma cell lines with a histone deacetylase inhibitor led to significant re-expression of DIRAS-1 and -2. Functionally, overexpression of DIRAS-1 and -2 in glioblastoma cells translated into significantly higher sensitivity to lomustine treatment. Analyses of DNA damage markers revealed that DIRAS-1 and -2 may play a role in p53-dependent response to alkylating chemotherapy

Molecular dissection of the valproic acid effects on glioma cells

Many glioblastoma patients suffer from seizures why they are treated with antiepileptic agents. Valproic acid (VPA) is a histone deacetylase inhibitor that apart from its anticonvulsive effects in some retrospective studies has been suggested to lead to a superior outcome of glioblastoma patients. However, the exact molecular effects of VPA treatment on glioblastoma cells have not yet been deciphered. We treated glioblastoma cells with VPA, recorded the functional effects of this treatment and performed a global and unbiased next generation sequencing study on the chromatin (ChIP) and RNA level. 1) VPA treatment clearly sensitized glioma cells to temozolomide: A protruding VPA-induced molecular feature in this context was the transcriptional upregulation/reexpression of numerous solute carrier (SLC) transporters that was also reflected by euchromatinization on the histone level and a reexpression of SLC transporters in human biopsy samples after VPA treatment. DNA repair genes were adversely reduced. 2) VPA treatment, however, also reduced cell proliferation in temozolomide-naive cells: On the molecular level in this context we observed a transcriptional upregulation/reexpression and euchromatinization of several glioblastoma relevant tumor suppressor genes and a reduction of stemness markers, while transcriptional subtype classification (mesenchymal/proneural) remained unaltered. Taken together, these findings argue for both temozolomide-dependent and -independent effects of VPA. VPA might increase the uptake of temozolomide and simultaneously lead to a less malignant glioblastoma phenotype. From a mere molecular perspective these findings might indicate a surplus value of VPA in glioblastoma therapy and could therefore contribute an additional ratio for clinical decision making

Matrix elements of unstable states

Using the language of non-relativistic effective Lagrangians, we formulate a systematic framework for the calculation of resonance matrix elements in lattice QCD. The generalization of the L\"uscher-Lellouch formula for these matrix elements is derived. We further discuss in detail the procedure of the analytic continuation of the resonance matrix elements into the complex energy plane and investigate the infinite-volume limit

Report on the sixth blind test of organic crystal structure prediction methods.

The sixth blind test of organic crystal structure prediction (CSP) methods has been held, with five target systems: a small nearly rigid molecule, a polymorphic former drug candidate, a chloride salt hydrate, a co-crystal and a bulky flexible molecule. This blind test has seen substantial growth in the number of participants, with the broad range of prediction methods giving a unique insight into the state of the art in the field. Significant progress has been seen in treating flexible molecules, usage of hierarchical approaches to ranking structures, the application of density-functional approximations, and the establishment of new workflows and `best practices' for performing CSP calculations. All of the targets, apart from a single potentially disordered Z' = 2 polymorph of the drug candidate, were predicted by at least one submission. Despite many remaining challenges, it is clear that CSP methods are becoming more applicable to a wider range of real systems, including salts, hydrates and larger flexible molecules. The results also highlight the potential for CSP calculations to complement and augment experimental studies of organic solid forms.The organisers and participants are very grateful to the crystallographers who supplied the candidate structures: Dr. Peter Horton (XXII), Dr. Brian Samas (XXIII), Prof. Bruce Foxman (XXIV), and Prof. Kraig Wheeler (XXV and XXVI). We are also grateful to Dr. Emma Sharp and colleagues at Johnson Matthey (Pharmorphix) for the polymorph screening of XXVI, as well as numerous colleagues at the CCDC for assistance in organising the blind test. Submission 2: We acknowledge Dr. Oliver Korb for numerous useful discussions. Submission 3: The Day group acknowledge the use of the IRIDIS High Performance Computing Facility, and associated support services at the University of Southampton, in the completion of this work. We acknowledge funding from the EPSRC (grants EP/J01110X/1 and EP/K018132/1) and the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC through grant agreements n. 307358 (ERC-stG- 2012-ANGLE) and n. 321156 (ERC-AG-PE5-ROBOT). Submission 4: I am grateful to Mikhail Kuzminskii for calculations of molecular structures on Gaussian 98 program in the Institute of Organic Chemistry RAS. The Russian Foundation for Basic Research is acknowledged for financial support (14-03-01091). Submission 5: Toine Schreurs provided computer facilities and assistance. I am grateful to Matthew Habgood at AWE company for providing a travel grant. Submission 6: We would like to acknowledge support of this work by GlaxoSmithKline, Merck, and Vertex. Submission 7: The research was financially supported by the VIDI Research Program 700.10.427, which is financed by The Netherlands Organisation for Scientific Research (NWO), and the European Research Council (ERC-2010-StG, grant agreement n. 259510-KISMOL). We acknowledge the support of the Foundation for Fundamental Research on Matter (FOM). Supercomputer facilities were provided by the National Computing Facilities Foundation (NCF). Submission 8: Computer resources were provided by the Center for High Performance Computing at the University of Utah and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1053575. MBF and GIP acknowledge the support from the University of Buenos Aires and the Argentinian Research Council. Submission 9: We thank Dr. Bouke van Eijck for his valuable advice on our predicted structure of XXV. We thank the promotion office for TUT programs on advanced simulation engineering (ADSIM), the leading program for training brain information architects (BRAIN), and the information and media center (IMC) at Toyohashi University of Technology for the use of the TUT supercomputer systems and application software. We also thank the ACCMS at Kyoto University for the use of their supercomputer. In addition, we wish to thank financial supports from Conflex Corp. and Ministry of Education, Culture, Sports, Science and Technology. Submission 12: We thank Leslie Leiserowitz from the Weizmann Institute of Science and Geoffrey Hutchinson from the University of Pittsburgh for helpful discussions. We thank Adam Scovel at the Argonne Leadership Computing Facility (ALCF) for technical support. Work at Tulane University was funded by the Louisiana Board of Regents Award # LEQSF(2014-17)-RD-A-10 “Toward Crystal Engineering from First Principles”, by the NSF award # EPS-1003897 “The Louisiana Alliance for Simulation-Guided Materials Applications (LA-SiGMA)”, and by the Tulane Committee on Research Summer Fellowship. Work at the Technical University of Munich was supported by the Solar Technologies Go Hybrid initiative of the State of Bavaria, Germany. Computer time was provided by the Argonne Leadership Computing Facility (ALCF), which is supported by the Office of Science of the U.S. Department of Energy under contract DE-AC02-06CH11357. Submission 13: This work would not have been possible without funding from Khalifa University’s College of Engineering. I would like to acknowledge Prof. Robert Bennell and Prof. Bayan Sharif for supporting me in acquiring the resources needed to carry out this research. Dr. Louise Price is thanked for her guidance on the use of DMACRYS and NEIGHCRYS during the course of this research. She is also thanked for useful discussions and numerous e-mail exchanges concerning the blind test. Prof. Sarah Price is acknowledged for her support and guidance over many years and for providing access to DMACRYS and NEIGHCRYS. Submission 15: The work was supported by the United Kingdom’s Engineering and Physical Sciences Research Council (EPSRC) (EP/J003840/1, EP/J014958/1) and was made possible through access to computational resources and support from the High Performance Computing Cluster at Imperial College London. We are grateful to Professor Sarah L. Price for supplying the DMACRYS code for use within CrystalOptimizer, and to her and her research group for support with DMACRYS and feedback on CrystalPredictor and CrystalOptimizer. Submission 16: R. J. N. acknowledges financial support from the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. [EP/J017639/1]. R. J. N. and C. J. P. acknowledge use of the Archer facilities of the U.K.’s national high-performance computing service (for which access was obtained via the UKCP consortium [EP/K014560/1]). C. J. P. also acknowledges a Leadership Fellowship Grant [EP/K013688/1]. B. M. acknowledges Robinson College, Cambridge, and the Cambridge Philosophical Society for a Henslow Research Fellowship. Submission 17: The work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1- 0387 and by the National Science Foundation Grant CHE-1152899. The work at the University of Silesia was supported by the Polish National Science Centre Grant No. DEC-2012/05/B/ST4/00086. Submission 18: We would like to thank Constantinos Pantelides, Claire Adjiman and Isaac Sugden of Imperial College for their support of our use of CrystalPredictor and CrystalOptimizer in this and Submission 19. The CSP work of the group is supported by EPSRC, though grant ESPRC EP/K039229/1, and Eli Lilly. The PhD students support: RKH by a joint UCL Max-Planck Society Magdeburg Impact studentship, REW by a UCL Impact studentship; LI by the Cambridge Crystallographic Data Centre and the M3S Centre for Doctoral Training (EPSRC EP/G036675/1). Submission 19: The potential generation work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1-0387 and by the National Science Foundation Grant CHE-1152899. Submission 20: The work at New York University was supported, in part, by the U.S. Army Research Laboratory and the U.S. Army Research Office under contract/grant number W911NF-13-1-0387 (MET and LV) and, in part, by the Materials Research Science and Engineering Center (MRSEC) program of the National Science Foundation under Award Number DMR-1420073 (MET and ES). The work at the University of Delaware was supported by the U.S. Army Research Laboratory and the U.S. Army Research Office under contract/grant number W911NF-13-1- 0387 and by the National Science Foundation Grant CHE-1152899. Submission 21: We thank the National Science Foundation (DMR-1231586), the Government of Russian Federation (Grant No. 14.A12.31.0003), the Foreign Talents Introduction and Academic Exchange Program (No. B08040) and the Russian Science Foundation, project no. 14-43-00052, base organization Photochemistry Center of the Russian Academy of Sciences. Calculations were performed on the Rurik supercomputer at Moscow Institute of Physics and Technology. Submission 22: The computational results presented have been achieved in part using the Vienna Scientific Cluster (VSC). Submission 24: The potential generation work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1-0387 and by the National Science Foundation Grant CHE-1152899. Submission 25: J.H. and A.T. acknowledge the support from the Deutsche Forschungsgemeinschaft under the program DFG-SPP 1807. H-Y.K., R.A.D., and R.C. acknowledge support from the Department of Energy (DOE) under Grant Nos. DE-SC0008626. This research used resources of the Argonne Leadership Computing Facility at Argonne National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-06CH11357. This research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DEAC02-05CH11231. Additional computational resources were provided by the Terascale Infrastructure for Groundbreaking Research in Science and Engineering (TIGRESS) High Performance Computing Center and Visualization Laboratory at Princeton University.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1107/S2052520616007447