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6. Biology-inspired microphysiological systems to advance patient benefit and animal welfare in drug development

Author

Marx U., Akabane T., Andersson T.B., Baker E, Beilmann M., Beken S., Brendler-Schwaab S., Cirit M., David R., Dehne E.M., Durieux I., Ewart L., Fitzpatrick S.C., Frey O., Fuchs F., Griffith L.G., Hamilton G.A., Hartung T., Hoeng J., Hogberg H., Hughes D.J., Ingber D.E., Iskandar A., Kanamori T., Kojima H., Kuehnl J., Leist M., Li B., Loskill P., Mendrick D.L., Neumann T., Pallocca G., Rusyn I., Smirnova L., Steger-Hartmann T., Tagle D.A., Tonevitsky A., Tsyb S., Trapecar M., Water B. van de, Eijnden-van Raaij J. van den, Vulto P., Watanabe K., Wolf A., Zhou X., Roth A.

Subjects
microphysiological systems, regulatory acceptance, assay qualification, iPSC-derived organoids, organ-on-chip, multi-organ-chip, drug testing, organoids, industrial adoption
Abstract

The first microfluidic microphysiological systems (MPS) entered the academic scene more than 15 years ago and were considered an enabling technology to human (patho)biology in vitro and, therefore, provide alternative approaches to laboratory animals in pharmaceutical drug development and academic research. Nowadays, the field generates more than a thousand scientific publications per year. Despite the MPS hype in academia and by platform providers, which says this technology is about to reshape the entire in vitro culture landscape in basic and applied research, MPS approaches have neither been widely adopted by the pharmaceutical industry yet nor reached regulated drug authorization processes at all. Here, 46 leading experts from all stakeholders - academia, MPS supplier industry, pharmaceutical and consumer products industries, and leading regulatory agencies - worldwide have analyzed existing challenges and hurdles along the MPS-based assay life cycle in a second workshop of this kind in June 2019. They identified that the level of qualification of MPS-based assays for a given context of use and a communication gap between stakeholders are the major challenges for industrial adoption by end-users. Finally, a regulatory acceptance dilemma exists against that background. This t4 report elaborates on these findings in detail and summarizes solutions how to overcome the roadblocks. It provides recommendations and a roadmap towards regulatory accepted MPS-based models and assays for patients' benefit and further laboratory animal reduction in drug development. Finally, experts highlighted the potential of MPS-based human disease models to feedback into laboratory animal replacement in basic life science research.

Published
2020

17. THEORETICAL INVESTIGATION OF CHARGE DELOCALIZATION IN QUATERNARY AMMONIUM CATIONS IN THE CASE OF CETYLPYRIDINIUM

Author

Telychka, V. S., Fizer, O. I., Fizer, M. M., Rusyn, I. F., and Lendel, V. G.

Subjects
cetylpyridinium, AM1, charge, delocalization, semiempirical
Abstract

Cetylpyridinium chloride or bromide are detergents which are widely used in industrial and household cleaners and in pharmaceuticals as cationic surfactants and disinfectants. Moreover, cetylpyridinim salts are popular catalysts in organic synthesis.In this work, we have considered the delocalization of charge in the cation of cetylpyridinium. The starting geometry of cetylpyridinim cation was modeled in the Avogadro program. Further geometry optimization was carried out by using AM1 Hamiltonian in the MOPAC216 package. Preparation of incoming mopac files was carried out through the Gabedit program interface. The values of the dielectric permittivity of different mediums were varied from 1 to 120.It was established that the positive charge is not localized on the nitrogen atom, as it is commonly shown, but delocalized over the pyridine ring and the cetyl chain. The pyridine ring is partially positively charged, however, the group charge does not correspond to the unit while lies within the range from +0.65e to +0.71e. The rest residual positive charge is delocalized along the cetyl chain. Moreover, in polar solvents, the first four methylene groups of cetyl substituent carry the main part in delocalization of the positive charge. As for modeling in the gas phase, the charge is even more delocalized, and the seventh methylene group has a partial group charge is about +0.005e. Such an effect of the polar medium can be explained by the localization of charge due to electrostatic interaction with the polar solvents. The methyl-group and the neighboring methylene group adjacent to it, have rather high values of partial charges, which explains some of the features in the spectral (NMR) properties of the terminal CH3 group.To simulate large systems based on the CP cation, it is advisable to reduce the length of the chain to six carbon atoms (of course, if not the effects caused by the chain's length itself is planned to be investigated). The choice of a chain containing six carbon atoms is due to the need for at least four carbon atoms to adequately simulate delocalization of a charge in a similar way as in the CP and two more carbons to reproduce the effects of the terminal methyl group., Цетилпіридинію хлорид або бромід є детергентами, які широко використовуються в промислових і побутових миючих композиціях і фармацевтичних засобах, в якості катіонних поверхнево-активних речовин (кПАР) і дезінфікуючих засобів. Більш того, цетилпіридинієві солі є популярними каталізаторами в органічному синтезі. У даній роботі ми розглянули делокалізацію заряду в катіоні цетилпіридинію. Початкова геометрія цетилпіридинієвого катіона була змодельована в програмі Авогадро. Подальша оптимізація геометрії була проведена з використанням AM1 Гамільтоніана в програмному пакеті MOPAC2016. Підготовка вхідних mopac-файлів здійснювалася за допомогою інтерфейсу програми Gabedit. Значення діелектричної проникності різних середовищ варіювали від 1 до 120.Встановлено, що позитивний заряд не локалізований на атомі Нітрогену, як це зазвичай позначають, а делокалізований по всьому піридиновому кільцю і частково по цетильному ланцюгу. Піридинове кільце частково позитивно заряджене, однак загальний заряд не відповідає одиниці, а знаходиться в межах від +0.65e до +0.71e. Решта залишкового позитивного заряду делокалізована вздовж цетильного ланцюга. Крім того, в полярних розчинниках перші чотири метиленові групи цетильного замісника вносять основний вклад у делокалізацію позитивного заряду. Що ж стосується моделювання в газовій фазі, то заряд ще більш делокалізований, а сьома метиленовая група має частковий груповий заряд близько +0.005e. Такий ефект полярної середовища можна пояснити локалізацією заряду внаслідок електростатичної взаємодії з полярними розчинниками. Термінальна метильна-група і сусідня метиленова група, яка з’єднана з нею, мають досить високі значення часткових зарядів, що пояснює деякі особливості спектральних (ЯМР) властивостей термінальної групи СН3.Для моделювання великих систем, які містять катіони цетилпіридинію, доцільно зменшити довжину алкільного ланцюга до шести атомів вуглецю (звичайно ж, якщо не планується дослідження властивостей, які викликані саме довжиною ланцюга). Вибір ланцюга, що містить шість атомів вуглецю, обумовлений необхідністю, щонайменше, чотирьох атомів Карбону для адекватного моделювання делокалізації заряду аналогічно тому, як у цетилпіридинію, і ще двох атомів Карбону для відтворення ефектів термінальної метильної групи.

Published
2019

24. Alcohol consumption and ethyl carbamate

Author

Allen, N, Anderson, L, Beland, F, Bénichou, J, Beral, V, Bloomfield, K, Brooks, P, Cai, L, Cho, S, Crabb, D, Eriksson, P, Gapstur, S, Gmel, G, Griciute, L, Kono, S, Lachenmeier, D, La Vecchia, C, Marques, M, Miller, AB, Rehm, J, Rehn-Mendoza, N, Rusyn, I, Seitz, H, Weiderpass, E, and Willett, W

Published
2016

25. Prediction of human population responses to toxic compounds by a collaborative competition

Author

Eduati, F, Mangravite, L, Wang, T, Tang, Hongxiang, Bare, J, Huang, R, Norman, T, Kellen, M, Menden, M, Yang, J, Zhan, X, Zhong, R, Xiao, G, Xia, M, Abdo, N, Kosyk, O, Friend, S, Stolovitzky, G, Dearry, A, Tice, R, Simeonov, S, Rusyn, I, Wright, F, Xie, Y, Alaimo, S, Amadoz, A, Ammad-ud-din, M, Chloé-Azencott, A, Bacardit, J, Barron, P, Bernard, E, Beyer, A, Bin, S, van Bömmel, A, Borgwardt, K, Brys, A, Caffrey, B, Chang, J, Christodoulou, E, Clément-Ziza, M, Cohen, T, Cowherd, M, Demeyer, S, Dopazo, J, Elhard, J, Falcao, A, Ferro, A, Friedenberg, D, Giugno, R, Gong, Y, Gorospe, J, Granville, C, Grimm, D, Heinig, M, Hernansaiz, R, Hochreiter, S, Liang-Huang, C, Huska, M, Jiao, Y, Klambauer, G, Kuhn, M, Kursa, M, Kutum, R, Lazzarini, N, Lee, I, Leung, M, K W, Lim, Liu, C, F L, López, Mammana, A, Mayr, A, Michoel, T, Mongiovì, M, Moore, J, Narasimhan, R, Opiyo, S, Pandey, G, Peabody, A, Perner, J, Pulvirenti, A, Rawlik, K, Reinhardt, S, Riffle, C, Ruderfer, D, Sander, A, Savage, R, Scornet, E, Sebastian-Leon, P, Sharan, R, Simon-Gabriel, C, Stoven, V, Sun, J, Tang, H, Teixeira, A, Tenesa, A, Jean-Vert, P, Vingron, M, Walter, T, Whalen, S, Wiśniewska, Z, Wu, Y, Xu, H, Zhang, S, Zhao, J, W Zheng J, Ziwei, D, Simeonov, A, Raymond, R Tice, Saez-Rodriguez, J., NIEHS-NCATS-UNC DREAM Toxicogenetics Collaboration, Institut de Recherche pour le Développement (IRD), National Center for Advancing Translational Sciences (NCATS), National Institutes of Health [Bethesda] (NIH), Data Storage Institute - A*STAR, Capital Normal University [Beijing], Southwest University of China, sans affiliation, Shanghai Ocean University, Centre de Bioinformatique (CBIO), MINES ParisTech - École nationale supérieure des mines de Paris-PSL Research University (PSL), Cancer et génôme: Bioinformatique, biostatistiques et épidémiologie d'un système complexe, MINES ParisTech - École nationale supérieure des mines de Paris-Institut Curie-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de l'Information Géographique et Forestière [IGN] (IGN), Systèmes Productifs, Logistique, Organisation des Transports et Travail (IFSTTAR/AME/SPLOTT), Communauté Université Paris-Est-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR), Biotechnology Center [Dresden] (BIOTEC), Technische Universität Dresden (TUD), Laboratoire National de Métrologie et d'Essais [Trappes] (LNE ), Centre for Biomedical Network Research on Rare Diseases (CIBERER), Department of Computational Genomics, Centro de Investigación Príncipe Felipe (CIPF), Functional Genomics Node (INB), CIPF, Computational Intelligence Research Group (CA3), Centre of Technology and Systems (CTS), Faculty of Sciences and Technology (FCT NOVA), Universidade Nova de Lisboa (NOVA)-Universidade Nova de Lisboa (NOVA)-Faculty of Sciences and Technology (FCT NOVA), Universidade Nova de Lisboa (NOVA)-Universidade Nova de Lisboa (NOVA)-Faculdade de Ciências e Tecnologia (FCT NOVA), Universidade Nova de Lisboa (NOVA), ACEEE, The Institute of Doctors Engineers and Scientists - IDES, Laboratoire Traitement et Communication de l'Information (LTCI), Télécom ParisTech-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS), Laboratory of Information, Network and Communication Sciences (LINCS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Mines-Télécom [Paris] (IMT), Institute of Computational Biology, Helmholtz-Zentrum München (HZM), Stony Brook University [SUNY] (SBU), State University of New York (SUNY), University of Pensylvania, Institute for Infocomm Research - I²R [Singapore], Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées, Department of Mechanical and Aerospace Engineering [Davis], University of California [Davis] (UC Davis), University of California-University of California, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Ludwig-Maximilians-Universität München (LMU), Laboratoire Architecture, Ville, Urbanisme, Environnement (LAVUE), École nationale supérieure d'architecture de Paris-La Villette (ENSAPLV)-École nationale supérieure d'architecture de Paris Val-de-Seine (ENSA PVDS)-Université Paris 8 Vincennes-Saint-Denis (UP8)-Ministère de la Culture (MC)-Université Paris Nanterre (UPN)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Statistique Théorique et Appliquée (LSTA), Université Pierre et Marie Curie - Paris 6 (UPMC), Agricultural Technological Extensive Station of Luntai County in Xinjiang, Medstar Research Institute, Huawei Technologies [Shanghaï], School of Economics and Business Administration (School of Economics and Business Administration), Beijing Normal University, National Center for Mathematics and Interdisciplinary Sciences [Beijing] (NCMIS), Academy of Mathematics and Systems Science (AMSS), Chinese Academy of Sciences [Beijing] (CAS)-Chinese Academy of Sciences [Beijing] (CAS), Division of Biostatistics, Helmholtz-Institute for Biomedical Engineering [RWTH Aachen University], European Bioinformatics Institute [Hinxton] (EMBL-EBI), EMBL Heidelberg, Agricultural Information Institute (AII), Chinese Academy of Agricultural Sciences (CAAS), Department of Computer Science - Lafayette College, Lafayette College [Easton], MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Cancer et génome: Bioinformatique, biostatistiques et épidémiologie d'un système complexe, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut Curie [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Communauté Université Paris-Est, Technische Universität Dresden = Dresden University of Technology (TU Dresden), Faculdade de Ciências e Tecnologia = School of Science & Technology (FCT NOVA), Universidade Nova de Lisboa = NOVA University Lisbon (NOVA)-Universidade Nova de Lisboa = NOVA University Lisbon (NOVA)-Faculdade de Ciências e Tecnologia = School of Science & Technology (FCT NOVA), Universidade Nova de Lisboa = NOVA University Lisbon (NOVA)-Universidade Nova de Lisboa = NOVA University Lisbon (NOVA), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Paris 8 Vincennes-Saint-Denis (UP8)-École nationale supérieure d'architecture de Paris-La Villette (ENSAPLV)-Université Paris Nanterre (UPN)-École nationale supérieure d'architecture de Paris Val-de-Seine (ENSA PVDS)-Centre National de la Recherche Scientifique (CNRS)-Ministère de la Culture (MC), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Beijing Normal University (BNU), Sans affiliation, Mines Paris - PSL (École nationale supérieure des mines de Paris), Helmholtz Zentrum München = German Research Center for Environmental Health, Université Fédérale Toulouse Midi-Pyrénées-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse III - Paul Sabatier (UT3), Department of Mechanical and Aerospace Engineering [Univ California Davis] (MAE - UC Davis), University of California (UC)-University of California (UC), Université Paris 8 Vincennes-Saint-Denis (UP8)-École nationale supérieure d'architecture de Paris-La Villette (ENSAPLV), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Paris Nanterre (UPN)-École nationale supérieure d'architecture de Paris Val-de-Seine (ENSA PVDS)-Centre National de la Recherche Scientifique (CNRS)-Ministère de la Culture (MC), Centre National de la Recherche Scientifique (CNRS)-Université Paris Nanterre (UPN)-Ministère de la Culture (MC)-Université Paris 8 Vincennes-Saint-Denis (UP8)-École nationale supérieure d'architecture de Paris Val-de-Seine (ENSA PVDS)-École nationale supérieure d'architecture de Paris-La Villette (ENSAPLV), Institut Mines-Télécom [Paris] (IMT)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Pierre et Marie Curie - Paris 6 (UPMC), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT), and MINES ParisTech - École nationale supérieure des mines de Paris-Institut Curie [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Bioinformatics, MESH: Risk Assessment, Applied Microbiology and Biotechnology, MESH: Dose-Response Relationship, Drug, Genotype, MESH: Incidence, MESH: Models, Genetic, Cytotoxicity, ComputingMilieux_MISCELLANEOUS, media_common, education.field_of_study, High-throughput screening, MESH: Genetic Predisposition to Disease, drug, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], Trait, Molecular Medicine, Health occupations, Predictive medicine, Risk factors, Risk assessment, Biotechnology, data mining, expression, MESH: High-Throughput Screening Assays, media_common.quotation_subject, Population, Biomedical Engineering, MESH: Genetics, Population, Bioengineering, Computational biology, Biology, Competition (biology), Article, MESH: Computer Simulation, ddc:570, 1000 Genomes Project, education, MESH: Toxicity Tests, ta113, MESH: Humans, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], MESH: Hazardous Substances, MESH: Lymphocytes, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], RA
Abstract

The ability to computationally predict the effects of toxic compounds on humans could help address the deficiencies of current chemical safety testing. Here, we report the results from a community-based DREAM challenge to predict toxicities of environmental compounds with potential adverse health effects for human populations. We measured the cytotoxicity of 156 compounds in 884 lymphoblastoid cell lines for which genotype and transcriptional data are available as part of the Tox21 1000 Genomes Project. The challenge participants developed algorithms to predict interindividual variability of toxic response from genomic profiles and population-level cytotoxicity data from structural attributes of the compounds. 179 submitted predictions were evaluated against an experimental data set to which participants were blinded. Individual cytotoxicity predictions were better than random, with modest correlations (Pearson's r < 0.28), consistent with complex trait genomic prediction. In contrast, predictions of population-level response to different compounds were higher (r < 0.66). The results highlight the possibility of predicting health risks associated with unknown compounds, although risk estimation accuracy remains suboptimal., Nature Biotechnology, 33 (9), ISSN:1546-1696, ISSN:1087-0156

Published
2015

26. The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans

Author

Ardlie, K. G., Getz, G., Ferreira, P. G., Segre, A. V., Ward, L. D., Young, T. R., Lappalainen, T., Sullivan, T. J., Winckler, W., Li, G., Kheradpour, P., Lek, M., Shabalin, A. A., Hirschhorn, J. N., Deluca, D. S., MacArthur, D. G., Kellis, M., Rusyn, I., Wright, F. A., Nobel, A. B., Tukiainen, T., Esko, T., Iriarte, B., Gelfand, E. T., Maller, J. B., Zhou, Y.-H., Palmer, C. D., Meng, Y., Trowbridge, C. A., Ongen, H., Rivas, M. A., and Battle, A.

Abstract

Understanding the functional consequences of genetic variation, and how it affects complex human disease and quantitative traits, remains a critical challenge for biomedicine. We present an analysis of RNA sequencing data from 1641 samples across 43 tissues from 175 individuals, generated as part of the pilot phase of the Genotype-Tissue Expression (GTEx) project. We describe the landscape of gene expression across tissues, catalog thousands of tissue-specific and shared regulatory expression quantitative trait loci (eQTL) variants, describe complex network relationships, and identify signals from genome-wide association studies explained by eQTLs. These findings provide a systematic understanding of the cellular and biological consequences of human genetic variation and of the heterogeneity of such effects among a diverse set of human tissues.

Published
2015
Full Text
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27. Differences in the carcinogenic evaluation of glyphosate between the International Agency for Research on Cancer (IARC) and the European Food Safety Authority (EFSA)

Author

Portier, C.J., Armstrong, B.K., Baguley, B.C., Baur, X., Belyaev, I., Belle, R., Belpoggi, F., Biggeri, A., Bosland, M.C., Bruzzi, P., Budnik, L.T., Bugge, M.D., Burns, K., Calaf, G.M., Carpenter, D.O., Carpenter, H.M., Lopez-Carrillo, L., Clapp, R., Cocco, P., Consonni, D., Comba, P., Craft, E., Dalvie, M.A., Davis, D., Demers, P.A., Roos, A.J. De, DeWitt, J., Forastiere, F., Freedman, J.H., Fritschi, L., Gaus, C., Gohlke, J.M., Goldberg, M., Greiser, E., Hansen, J., Hardell, L., Hauptmann, M., Huang, W., Huff, J., James, M.O., Jameson, C.W., Kortenkamp, A., Kopp-Schneider, A., Kromhout, H., Larramendy, M.L., Landrigan, P.J., Lash, L.H., Leszczynski, D., Lynch, C.F., Magnani, C., Mandrioli, D., Martin, F.L., Merler, E., Michelozzi, P., Miligi, L., Miller, A.B., Mirabelli, D., Mirer, F.E., Naidoo, S., Perry, M.J., Petronio, M.G., Pirastu, R., Portier, R.J., Ramos, K.S., Robertson, L.W., Rodriguez, T., Roosli, M., Ross, M.K., Roy, D. Le, Rusyn, I., Saldiva, P., Sass, J., Savolainen, K., Scheepers, P.T.J., Sergi, C., Silbergeld, E.K., Smith, M.T., Stewart, B.W., Sutton, P., Tateo, F., Terracini, B., Thielmann, H.W., Thomas, D.B., Vainio, H., Vena, J.E., Vineis, P., Weiderpass, E., Weisenburger, D.D., Woodruff, T.J., Yorifuji, T., Yu, I.J., Zambon, P., Zeeb, H., Zhou, S.F., Portier, C.J., Armstrong, B.K., Baguley, B.C., Baur, X., Belyaev, I., Belle, R., Belpoggi, F., Biggeri, A., Bosland, M.C., Bruzzi, P., Budnik, L.T., Bugge, M.D., Burns, K., Calaf, G.M., Carpenter, D.O., Carpenter, H.M., Lopez-Carrillo, L., Clapp, R., Cocco, P., Consonni, D., Comba, P., Craft, E., Dalvie, M.A., Davis, D., Demers, P.A., Roos, A.J. De, DeWitt, J., Forastiere, F., Freedman, J.H., Fritschi, L., Gaus, C., Gohlke, J.M., Goldberg, M., Greiser, E., Hansen, J., Hardell, L., Hauptmann, M., Huang, W., Huff, J., James, M.O., Jameson, C.W., Kortenkamp, A., Kopp-Schneider, A., Kromhout, H., Larramendy, M.L., Landrigan, P.J., Lash, L.H., Leszczynski, D., Lynch, C.F., Magnani, C., Mandrioli, D., Martin, F.L., Merler, E., Michelozzi, P., Miligi, L., Miller, A.B., Mirabelli, D., Mirer, F.E., Naidoo, S., Perry, M.J., Petronio, M.G., Pirastu, R., Portier, R.J., Ramos, K.S., Robertson, L.W., Rodriguez, T., Roosli, M., Ross, M.K., Roy, D. Le, Rusyn, I., Saldiva, P., Sass, J., Savolainen, K., Scheepers, P.T.J., Sergi, C., Silbergeld, E.K., Smith, M.T., Stewart, B.W., Sutton, P., Tateo, F., Terracini, B., Thielmann, H.W., Thomas, D.B., Vainio, H., Vena, J.E., Vineis, P., Weiderpass, E., Weisenburger, D.D., Woodruff, T.J., Yorifuji, T., Yu, I.J., Zambon, P., Zeeb, H., and Zhou, S.F.

Abstract

Contains fulltext : 172314.pdf (Publisher’s version ) (Open Access)

Published
2016

30. Chemical safety assessment using read-across: assessing the use of novel testing methods to strengthen the evidence base for decision making

Author

Berggren, E., Amcoff, P., Benigni, R., Blackburn, K., Carney, E., Cronin, M., Deluyker, H., Gautier, F., Judson, R.S., Kass, G.E.N., Keller, D., Knight, D., Lilienblum, W., Mahony, C., Rusyn, I., Schultz, T., Schwarz, M., Schüürmann, Gerrit, White, A., Burton, J., Lostia, A.M., Munn, S., Worth, A., Berggren, E., Amcoff, P., Benigni, R., Blackburn, K., Carney, E., Cronin, M., Deluyker, H., Gautier, F., Judson, R.S., Kass, G.E.N., Keller, D., Knight, D., Lilienblum, W., Mahony, C., Rusyn, I., Schultz, T., Schwarz, M., Schüürmann, Gerrit, White, A., Burton, J., Lostia, A.M., Munn, S., and Worth, A.

Abstract

Background: Safety assessment for repeated dose toxicity is one of the largest challenges in the process to replace animal testing. This is also one of the proof of concept ambitions of SEURAT-1, the largest ever European Union research initiative on alternative testing, co-funded by the European Commission and Cosmetics Europe. This review is based on the discussion and outcome of a workshop organized on initiative of the SEURAT-1 consortium joined by a group of international experts with complementary knowledge to further develop traditional read-across and include new approach data.Objectives: The aim of the suggested strategy for chemical read-across is to show how a traditional read-across based on structural similarities between source and target substance can be strengthened with additional evidence from new approach data—for example, information from in vitro molecular screening, “-omics” assays and computational models—to reach regulatory acceptance. Methods: We identified four read-across scenarios that cover typical human health assessment situations. For each such decision context, we suggested several chemical groups as examples to prove when read-across between group members is possible, considering both chemical and biological similarities.Conclusions: We agreed to carry out the complete read-across exercise for at least one chemical category per read-across scenario in the context of SEURAT-1, and the results of this exercise will be completed and presented by the end of the research initiative in December 2015.

Published
2015

31. IARC monographs: 40 years of evaluating carcinogenic hazards to humans

Author

Pearce, N., Blair, A., Vineis, P., Ahrens, W., Andersen, A., Anto, J., Armstrong, B., Baccarelli, A., Beland, F., Berrington, A., Bertazzi, P., Birnbaum, L., Brownson, R., Bucher, J., Cantor, K., Cardis, E., Cherrie, J., Christiani, D., Cocco, P., Coggon, D., Comba, P., Demers, P., Dement, J., Douwes, J., Eisen, E., Engel, L., Fenske, R., Fleming, L., Fletcher, T., Fontham, E., Forastiere, F., Frentzel-Beyme, R., Fritschi, Lin, Gerin, M., Goldberg, M., Grandjean, P., Grimsrud, T., Gustavsson, P., Haines, A., Hartge, P., Hansen, J., Hauptmann, M., Heederik, D., Hemminki, K., Hemon, D., Hertz-Picciotto, I., Hoppin, J., Huff, J., Jarvholm, B., Kang, D., Karagas, M., Kjaerheim, K., Kjuus, H., Kogevinas, M., Kriebel, D., Kristensen, P., Kromhout, H., Laden, F., Lebailly, P., Lemasters, G., Lubin, J., Lynch, C., Lynge, E., Mannetje, A., McMichael, A., McLaughlin, J., Marrett, L., Martuzzi, M., Merchant, J., Merler, E., Merletti, F., Miller, A., Mirer, F., Monson, R., Nordby, K., Olshan, A., Parent, M., Perera, F., Perry, M., Pesatori, A., Pirastu, R., Porta, M., Pukkala, E., Rice, C., Richardson, D., Ritter, L., Ritz, B., Ronckers, C., Rushton, L., Rusiecki, J., Rusyn, I., Samet, J., Sandler, D., de Sanjose, S., Schernhammer, E., Costantini, A., Seixas, N., Shy, C., Siemiatycki, J., Silverman, D., Simonato, L., Smith, A., Smith, M., Spinelli, J., Spitz, M., Stallones, L., Stayner, L., Steenland, K., Stenzel, M., Stewart, B., Stewart, P., Symanski, E., Terracini, B., Tolbert, P., Vainio, H., Vena, J., Vermeulen, R., Victora, C., Ward, E., Weinberg, C., Weisenburger, D., Wesseling, C., Weiderpass, E., Zahm, S., Pearce, N., Blair, A., Vineis, P., Ahrens, W., Andersen, A., Anto, J., Armstrong, B., Baccarelli, A., Beland, F., Berrington, A., Bertazzi, P., Birnbaum, L., Brownson, R., Bucher, J., Cantor, K., Cardis, E., Cherrie, J., Christiani, D., Cocco, P., Coggon, D., Comba, P., Demers, P., Dement, J., Douwes, J., Eisen, E., Engel, L., Fenske, R., Fleming, L., Fletcher, T., Fontham, E., Forastiere, F., Frentzel-Beyme, R., Fritschi, Lin, Gerin, M., Goldberg, M., Grandjean, P., Grimsrud, T., Gustavsson, P., Haines, A., Hartge, P., Hansen, J., Hauptmann, M., Heederik, D., Hemminki, K., Hemon, D., Hertz-Picciotto, I., Hoppin, J., Huff, J., Jarvholm, B., Kang, D., Karagas, M., Kjaerheim, K., Kjuus, H., Kogevinas, M., Kriebel, D., Kristensen, P., Kromhout, H., Laden, F., Lebailly, P., Lemasters, G., Lubin, J., Lynch, C., Lynge, E., Mannetje, A., McMichael, A., McLaughlin, J., Marrett, L., Martuzzi, M., Merchant, J., Merler, E., Merletti, F., Miller, A., Mirer, F., Monson, R., Nordby, K., Olshan, A., Parent, M., Perera, F., Perry, M., Pesatori, A., Pirastu, R., Porta, M., Pukkala, E., Rice, C., Richardson, D., Ritter, L., Ritz, B., Ronckers, C., Rushton, L., Rusiecki, J., Rusyn, I., Samet, J., Sandler, D., de Sanjose, S., Schernhammer, E., Costantini, A., Seixas, N., Shy, C., Siemiatycki, J., Silverman, D., Simonato, L., Smith, A., Smith, M., Spinelli, J., Spitz, M., Stallones, L., Stayner, L., Steenland, K., Stenzel, M., Stewart, B., Stewart, P., Symanski, E., Terracini, B., Tolbert, P., Vainio, H., Vena, J., Vermeulen, R., Victora, C., Ward, E., Weinberg, C., Weisenburger, D., Wesseling, C., Weiderpass, E., and Zahm, S.

Abstract

Background: Recently, the International Agency for Research on Cancer (IARC) Programme for the Evaluation of Carcinogenic Risks to Humans has been criticized for several of its evaluations, and also for the approach used to perform these evaluations. Some critics have claimed that failures of IARC Working Groups to recognize study weaknesses and biases of Working Group members have led to inappropriate classification of a number of agents as carcinogenic to humans. oBjectives: The authors of this Commentary are scientists from various disciplines relevant to the identification and hazard evaluation of human carcinogens. We examined criticisms of the IARC classification process to determine the validity of these concerns. Here, we present the results of that examination, review the history of IARC evaluations, and describe how the IARC evaluations are performed. discussion: We concluded that these recent criticisms are unconvincing. The procedures employed by IARC to assemble Working Groups of scientists from the various disciplines and the techniques followed to review the literature and perform hazard assessment of various agents provide a balanced evaluation and an appropriate indication of the weight of the evidence. Some disagreement by individual scientists to some evaluations is not evidence of process failure. The review process has been modified over time and will undoubtedly be altered in the future to improve the process. Any process can in theory be improved, and we would support continued review and improvement of the IARC processes. This does not mean, however, that the current procedures are flawed. conclusions: The IARC Monographs have made, and continue to make, major contributions to the scientific underpinning for societal actions to improve the public’s health.

Published
2015

34. Carcinogenicity of Perfluorooctanoic Acid, Tetrafluoroethylene, Dichloromethane, 1,2-Dichloropropane, and 1,3-Propane Sultone

Author

Rusyn, I., Fritschi, Lin, Sergi, C., Hansen, J., Le Curieux, F., Bolt, H., Fukushima, S., Ichihara, G., Kamae, K., Kumagai, S., Tsuda, H., Kjaerheim, K., Bartell, S., Cesta, M., Chiu, W., Cooper, G., DeWitt, J., Friesen, M., Lash, L., Steenland, K., Rusyn, I., Fritschi, Lin, Sergi, C., Hansen, J., Le Curieux, F., Bolt, H., Fukushima, S., Ichihara, G., Kamae, K., Kumagai, S., Tsuda, H., Kjaerheim, K., Bartell, S., Cesta, M., Chiu, W., Cooper, G., DeWitt, J., Friesen, M., Lash, L., and Steenland, K.

Published
2014

35. Mouse population-guided resequencing reveals that variants in CD44 contribute to acetaminophen-induced liver injury in humans

Author

Paigen, K., Harris, S. C., Sackler, R. S., Ross, P. K., Tennant, R., Stylianou, I. M., Boorman, G. A., Su, S., Rusyn, I., Harris, C., Threadgill, D. W., Contractor, T., Wiltshire, T., Watkins, P. B., Bogue, M., Smith, P. C., Harbourt, D. E., Russo, M. W., and Harrill, A. H.

Abstract

Interindividual variability in response to chemicals and drugs is a common regulatory concern. It is assumed that xenobiotic-induced adverse reactions have a strong genetic basis, but many mechanism-based investigations have not been successful in identifying susceptible individuals. While recent advances in pharmacogenetics of adverse drug reactions show promise, the small size of the populations susceptible to important adverse events limits the utility of whole-genome association studies conducted entirely in humans. We present a strategy to identify genetic polymorphisms that may underlie susceptibility to adverse drug reactions. First, in a cohort of healthy adults who received the maximum recommended dose of acetaminophen (4 g/d × 7 d), we confirm that about one third of subjects develop elevations in serum alanine aminotransferase, indicative of liver injury. To identify the genetic basis for this susceptibility, a panel of 36 inbred mouse strains was used to model genetic diversity. Mice were treated with 300 mg/kg or a range of additional acetaminophen doses, and the extent of liver injury was quantified. We then employed whole-genome association analysis and targeted sequencing to determine that polymorphisms in Ly86, Cd44, Cd59a, and Capn8 correlate strongly with liver injury and demonstrated that dose-curves vary with background. Finally, we demonstrated that variation in the orthologous human gene, CD44, is associated with susceptibility to acetaminophen in two independent cohorts. Our results indicate a role for CD44 in modulation of susceptibility to acetaminophen hepatotoxicity. These studies demonstrate that a diverse mouse population can be used to understand and predict adverse toxicity in heterogeneous human populations through guided resequencing.

Published
2009
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37. P344 TRANSLATIONAL STUDY IDENTIFIES NEUTROPHIL GELATINASE-ASSOCIATED LIPOCALIN (NGAL) AS A POTENTIAL MEDIATOR OF LIVER INJURY AND FIBROGENESIS IN ALCOHOLIC HEPATITIS

Author

Odena, G., primary, Morales-Ibanez, O., additional, Affo, S., additional, Furuya, S., additional, Rusyn, I., additional, Altamirano, J., additional, Sancho-Bru, P., additional, Arroyo, V., additional, Gines, P., additional, Caballeria, J., additional, and Bataller, R., additional

Published
2014
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47. WY-14 643 rapidly activates nuclear factor κB in Kupffer cells before hepatocytes.

Author

Rusyn, I, Tsukamoto, H, and Thurman, RG

Abstract

Stimulation of cell proliferation caused by peroxisome proliferators was blocked by antibodies against TNFα and agents that inactivate Kupffer cells, a rich source of TNFα, which supports the hypothesis that Kupffer cells play a pivotal role in peroxisome proliferator-induced hyperplasia. Here, the ability of the very potent peroxisome proliferator WY-14 643 to activate the transcription factor NF-κB in rat liver was examined since it is involved in TNFα production. Female Sprague-Dawley rats were treated by gavage with WY-14 643 (100 mg/kg) while control animals were given equivalent doses of vehicle (olive oil). Activation of NF-κB in both whole liver, non-parenchymal cells, Kupffer cells and hepatocytes was assessed for up to 36 h using an electrophoretic mobility shift assay. In whole liver, WY-14 643 transiently increased NF-κB binding maximally 3.5-fold in 2-8 h followed by a steady decline to near control levels at 36 h. As early as 2 h after WY-14 643 treatment, the active form of NF-κB was localized predominantly in Kupffer cells with values 20- to 25-times greater than in hepatocytes. In hepatocytes, a small increase in NF-κB binding was observed but only 8 h after WY-14 643 administration. Pre-treatment with allopurinol, a xanthine oxidase inhibitor and free radical scavenger, suppressed NF-κB activation by WY-14 643 almost completely. It is concluded that NF-κB is activated by reactive oxygen species and plays a central role in the mechanism of action of peroxisome proliferators. Moreover, these findings support the hypothesis that Kupffer cells play a pivotal role in peroxisome proliferator-induced hepatocyte proliferation through rapid NF-κB activation and subsequent induction of TNFα production. TNFα from Kupffer cells stimulates growth in parenchymal cells later via mechanisms that also involve NF-κB. [ABSTRACT FROM PUBLISHER]

Published
1998
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50. Peroxisome proliferator-activated receptor alpha is restricted to hepatic parenchymal cells, not Kupffer cells: implications for the mechanism of action of peroxisome proliferators in hepatocarcinogenesis.

Author

Peters, J M, Rusyn, I, Rose, M L, Gonzalez, F J, and Thurman, R G

Abstract

Peroxisome proliferators increase hepatocyte proliferation and cause liver tumors in rodents, yet the mechanism of action is not understood. Based on studies with null mice it is known that peroxisome proliferator-activated receptor-alpha (PPARalpha) is involved. There is also evidence that Kupffer cells play a central role in peroxisome proliferator-induced carcinogenesis, most likely via mechanisms involving increases in superoxide, activation of nuclear factor kappaB and production of tumor necrosis factor-alpha (TNFalpha). However, it is not known whether PPARalpha is constitutively expressed in Kupffer cells. Therefore, the expression of PPAR isoforms in rat Kupffer and parenchymal cells was examined. Kupffer cells and hepatocytes of >99% purity were isolated from rats fed either a control diet or one containing 0.1% WY-14,643 for 1 week. Protein and RNA were obtained and PPAR expression was analyzed using northern and western blots. PPARalpha, PPARbeta and PPARgamma mRNA was detected in purified hepatocytes. In Kupffer cells, mRNA encoding PPARgamma was present while transcripts for PPARalpha and PPARbeta were not detected. Immunoblots were consistent with the results found by northern analysis. Moreover, when Kupffer cells from wild-type or PPARalpha-null mice were treated with WY-14,643 in vitro, superoxide production was similar. Combined, these results show that PPARalpha is expressed in rat parenchymal cells but not in Kupffer cells. These data are consistent with the hypothesis that parenchymal cells respond to Kupffer cell-derived TNFalpha via mechanisms dependent on PPARalpha within the parenchymal cells.

Published
2000
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