Download Final programme + abstracts (encl.)

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Symposium: Thursday 16 September 2010 in Oslo, Norway
Organised by ECETOC & EEMS, sponsored by CEFIC-LRI
Use of ‘omics to elucidate mechanism of action and integration of ‘omics in a systems
biology concept
Chairmen: Jos Kleinjans & Gunnar Brunborg
8.50
Welcome ─ Ben van Ravenzwaay / Henk Vrijhof ECETOC
8.55
Liver toxicogenomics within the pharmaceutical industry: From in vivo,
to slice, to permanent cell line
Willem Schoonen Available BvR
MSD
9.20
Sources of variation in baseline gene expression levels from
toxicogenomics study control animals
Chris Corton Available BvR
US EPA
9.45
The identification of modes of action on the thyroid by metabolic profiling
and its potential use for chemical grouping
Ben van Ravenzwaay
BASF / ECETOC
10.10
Coffee/tea
10.30
Toxicogenomics for genotoxicity and carcinogenicity prediction: The
role of microRNA
Joost van Delft Available JK
University of Maastricht
10.55
Prediction in the face of uncertainty: A Monte Carlo strategy for systems
biology of cancer treatment
Christoph Wierling Available JK.
Max Planck Institute for Molecular Genetics
11.20
Closing remarks ─ Neil Carmichael ECETOC Available HV
Check: BvR to add on Malaga learnings
10.30
End
Special lectures (Sobels)
APPENDIX A:ECETOC and LRI descriptions ........................................................... p. 2
APPENDIX B: Abstracts from Malaga WS .............................................................. p. 3-5
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The European Centre for Ecotoxicology and Toxicology of Chemicals (ECETOC)
ECETOC was established in 1978 as a scientific, non-profit making, non-commercial association and currently
counts as its members 47 of the leading companies with interests in the manufacture and use of chemicals. An
independent organisation, ECETOC provides a scientific forum through which the extensive specialist expertise
of manufacturers and users can be harnessed to research, review, assess and publish studies on the
ecotoxicology and toxicology of chemicals.
The Association’s main objective is to identify, evaluate and through such knowledge help the industry to
minimise any potentially adverse effects on human health and the environment that may arise from the
manufacture and use of chemicals. To achieve this, ECETOC facilitates the networking of suitably qualified
scientists from its member companies and co-operates in a scientific context with international agencies,
government authorities and professional societies.
ECETOC is governed by a Board of Administration comprising up to twelve senior executives from member
companies. The Board is responsible for the overall policy and finance of the organisation and appoints the
members of the Scientific Committee which defines, manages and peer reviews the ECETOC work programme.
The outputs of its work programme are manifested as published reports, papers and specialised workshops.
ECETOC also provides scientific representation of manufacturers and users of chemicals via presentations at
specialist fora and takes a scientific role in the activities of international organisations and regulatory groups.
Further information on ECETOC and its Science Programme can be found on the Internet, at
http://www.ecetoc.org/.
The Long-range Research Initiative (LRI)
Over the years, there has been growing awareness and concern about the potential impact of human activity and
man-made substances on the environment and human health. The chemical industry is conscious of the need to
address societal concerns and take responsibility in understanding the long-term impacts of its products and
processes.
The idea for LRI began in the USA in 1996, with the goal of responding to public and stakeholder concerns
through scientific investigation. The focus is on gaps in industry’s knowledge and understanding that are critical
for risk assessment. The broad aim is a validated infrastructure of scientific advice on which the entire industry
and regulatory bodies will draw to respond more quickly and accurately to the public’s questions. Today's LRI
is jointly managed by the American Chemical Council, Japanese Chemical Industry Association, and European
Chemical Council (CEFIC).
LRI sponsors research to help address some of the priorities of the European public health strategy: improving
risk assessment of chemicals; and more specifically monitoring effects of chemicals on health; understanding
the environmental factors in human health; establishing endocrine disruption references; and coordinating
research, data and activities at a European level. LRI also addresses many of the environmental objectives of the
European Union, including: linking environmental factors to health effects; understanding and reducing
chemical risks to environment; and improving animal testing in risk assessment.
ECETOC has been a key partner to CEFIC from the earliest stage of the LRI process. It provides scientific
support into the LRI, and input into the Research Programme.
Further information on the LRI may be found on the Internet, at http://www.cefic-lri.org/.
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LIVER TOXICOGENOMICS WITHIN THE PHARMACEUTICAL INDUSTRY
Willem G. Schoonen1, A.A. Staalduinen, W.M.A. Westerink, M.G.L.Elferink3, P.Olinga3, A.L.Draaisma3,
M.T.Merema3, S. Bauerschmidt2, J. Polman2, and G.M.M.Groothuis
1
Toxicology and Drug Disposition, and 2 Molecular Design and Informatics, MSD, Oss, The Netherlands, MSD,
Oss, The Netherlands, 3 Pharmacokinetics,Toxicology and Targeting, Dept of Pharmacy, University of
Groningen, The Netherlands
Liver, heart and kidney failure are the most prominent toxicity problems for drug development within the
pharmaceutical industry. The introduction of the microarray technology, in which a large number of genes can
be examined, created the possibility for early toxicity screening within the process of drug development. In this
study, the attention was focused on the liver, in which also phase I and II metabolism plays a pivotal role. The
effects of different necrotic, cholestatic and/or genotoxic compounds were analyzed at the gene expression level
in the rat liver both in vivo and in vitro. As in vitro model system the precision-cut liver slice model was used,
in which all liver cell types are present in their natural architecture. This is important since drug-induced
toxicity often is a multi-cellular process involving not only hepatocytes but also other cell types such as Kupffer
and stellate cells. The aim of this study was to validate the rat liver slice system as in vitro model system for
drug-induced toxicity studies. In addition, HepG2 cells, a widely used permanent human liver cell line derived
from human liver carcinoma, were studied for comparison. The results of the microarray studies show that the
in vitro profiles of gene expression in rat liver slices cluster per compound and incubation time, and when
analyzed in a commercial gene expression database (ToxShieldTM), can predict the in vivo toxicity and
pathology. In HepG2 cells, necrotic and cholestatic compounds can be distinguished from genotoxicants.
Moreover, by transfection of HepG2 cells with a proper selection of gene sets with their respective promoters,
high throughput assays have been developed for genotoxicity screening. These data show that the rat liver slice
system as well as HepG2 cells represent appropriate tools for the prediction of liver toxicity. The prediction of
human specific toxicity using human liver slices is currently under investigation.
Sources of variation in baseline gene expression levels from toxicogenomics study control animals
Chris Corton
Integrated Systems Toxicology Division, National Health and Environmental Effects Research Laboratory, USEPA, Research Triangle Park, NC
The use of gene expression profiling in to predict chemical mode of action would be enhanced by better
characterization of variance due to individual, environmental, and technical factors. Meta-analysis of
microarray data from untreated or vehicle-treated animals within the control arm of toxicogenomics studies has
yielded useful information on baseline fluctuations in gene expression. A dataset of control animal microarray
expression data was assembled by a working group of the Health and Environmental Sciences Institute's
Technical Committee on the Application of Genomics in Mechanism Based Risk Assessment in order to provide
a public resource for assessments of variability in baseline gene expression. Data from over 500 Affymetrix
microarrays from control rat liver and kidney were collected from 16 different institutions. Thirty-five
biological and technical factors were obtained for each animal, describing a wide range of study characteristics,
and a subset were evaluated in detail for their contribution to total variability using multivariate statistical and
graphical techniques. The study factors that emerged as key sources of variability included gender, organ
section, strain, and fasting state. These and other study factors were identified as key descriptors that should be
included in the minimal information about a toxicogenomics study needed for interpretation of results by an
independent source. Genes that are the most and least variable, gender-selective, or altered by fasting were also
identified and functionally categorized. In other studies, examples of gene expression variability through mouse
life stages will be discussed. Better characterization of gene expression variability in control animals will aid in
the design of toxicogenomics studies and in the interpretation of their results. (This abstract does not
necessarily reflect US EPA policy).
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The identification of direct and indirect modes of action on the thyroid by means of metabolic
profiling
Bennard van Ravenzwaay1, Eric Fabian1, Werner Mellert1, Volker Strauss1, Gerd Krennrich1, Tilmann
Walk2, Jan Wiemer2, Alexander Prokoudine2, Ralf Looser2, Michael Herold2 and Hennicke Kamp1
1) BASF SE Ludwigshafen, Germany
2) Metanomics GmbH, Berlin, Germany
We are using metabolic profiling to determine metabolite changes in the plasma of rats during
exposure to a great number of different chemicals and are gathering the patterns in a database
(MetaMaptmTox). Statistical analysis of individual and total parameters (ca. 280) over several years in
untreated control rats demonstrates the stability of control values. Consistently changed patterns of
metabolite levels in exposed animals can identify specific modes of action, whereas monitoring
individual biomarkers generally does not. The number of metabolites in the mode of action patterns
can vary considerably. An alteration of only 3 metabolites is characteristic of anemia‐inducing
chemicals, whereas large patterns (e.g. changes in up to approximately 20 metabolites) are required
to specifically identify liver cell toxicity.
Here we present metabolic patterns distinguishing two modes of action pertaining to thyroid effects.
Although several specific modes of action can lead to thyroid dysregulation, the two most common
are referred to as the direct mechanism (inhibition of thyroid hormone synthesis) and the indirect
mechanism (liver enzyme induction resulting in increased thyroid hormone metabolism). The latter is
one of the most common findings in toxicological studies. To establish a metabolic pattern for direct
effects we used three model substances, ETU, PTU and Methimazole. To confirm the specificity, we
compared these patterns with that induced by thyroxin administration to rats and noticed that nearly
all affected metabolite levels were changed, however, in an opposite direction. To induce an indirect
mechanism on the thyroid we administered Phenobarbital, Aroclor 1254, and Boscalid. The altered
pattern of metabolites was similar to, but not congruent with, the pattern established for general
liver enzyme induction. Applying the former pattern we identified other compounds with an indirect
effect on the thyroid and verified our assessment, using a perchlorate discharge assay, with a subset
of compounds (e.g. metazachlor).
New descriptors in toxicogenomics: Epigenetics and microRNA
Jos Kleinjans
Dept. of Health Risk Analysis & Toxicology
Maastricht University, The Netherlands
Transcriptomics has been successfully applied to in vitro models of human cells for the purpose of predicting
toxicity, e.g. with respect to genotoxicity/carcinogenicity, organ toxicity and endocrine disruption, in general
being able to predict toxicity with an accuracy of above 85%19. For innovative biomarker development, future
developments will focus on integrating multiple data streams derived from transcriptomics, miRNA analysis,
epigenetics, proteomics and metabonomics with traditional toxicological and histopathological endpoint
evaluation, in view of a systems biology or rather, systems toxicology approach.
In particular, completely new insights in long-term toxic effects on cells are to be expected from new readouts
such as epigenetics and miRNA.
Epigenetic alterations are potentially more damaging than nucleotide mutations because their effects on regional
chromatin structure can spread, thus affecting multiple genetic loci. They also tend to affect a high proportion of
those cells exposed, unlike conventional mutations, which are relatively rare. The most common changes are
alterations in the methylation pattern of DNA, but modifications of histone proteins are also implicated. It has
been shown that epigenetic inheritance of disease states for generations after the initial exposure, in cases
involving endocrine disruptors.
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MicroRNAs (miRNAs) have emerged as powerful negative regulators of mRNA levels in several systems.
These miRNAs can be held responsible for influencing mRNA levels of important genes involved in metabolic
and toxicological pathways. Increasing evidence has implicated miRNAs in biological processes such as normal
development and disease pathology, particularly in cancer.
Analysis of epigenetics and/or miRNA responses may therefore help in identifying novel sets of predictive
biomarkers at the level of regulation of gene expression of toxicologically relevant genes.
Prediction in the Face of Uncertainty: a Monte Carlo Strategy for Systems Biology of Cancer Treatment
Cancer is known to be a complex disease and its therapy has turned out to be difficult. Much information is
available on molecules and pathways involved in cancer onset and progression. By processing literature
information and pathway databases of twenty different signaling pathways known to be relevant for cancer (like
Wnt, Notch, BMP, Fas, Trail, EGF, IGF, Hedgehog, etc.), we have developed a large mathematical model of
these pathways. Although the development of large detailed mathematical models is difficult, the benefit one
could gain using their predictive power is tremendous. The development of such detailed mathematical models
is not only hampered by a limited knowledge about the topology of the cellular reaction network, but also by a
highly restricted availability of detailed mathematical descriptions of the individual reaction kinetics along with
their respective kinetic parameters. To overcome this bottleneck we introduce an approach, based on a Monte
Carlo strategy, in which the kinetic parameters are sampled from appropriate probability distributions and used
for multiple simulations in parallel. Results from different forms of the model (e.g., a model that resembles a
certain mutation or the treatment by a drug) can be compared with the unperturbed control and used for the
prediction of the effect of the perturbation. The established resources, tools, algorithms and models build a
foundation for the application of systems biology strategies in medical and pharmaceutical research and, based
on data from high-throughput genome, transcriptome, and proteome analysis, it enables the development of a
personalized medicine.
Resume
Christoph Wierling studied biology at the University of Münster, Germany, and obtained a PhD in
biochemistry at the Free University of Berlin. His research interests focus on modeling and simulation of
biological systems and the development of systems biology software. Currently he works as a group leader of
the systems biology group at the Max Planck Institute for Molecular Genetics in Berlin. Christoph Wierling is
co-author of one of the first text books on systems biology.