Adriano Henney

The virtual liver: a multidisciplinary, multilevel challenge for systems biology

The liver is the central metabolic organ in human physiology, with functions that are fundamentally important to the detoxification of xenobiotics (drugs), the maintenance of homeostasis of numerous blood metabolites, and the production of mediators of the acute phase response. Liver toxicity, whether actual or implied is the reason for the failure of a significant proportion of many promising novel medicines that consequently never reach the market, and diseases such as atherosclerosis, diabetes, and fatty liver diseases, that are a major burden on current health resources, are directly linked to functional and structural disorders of the liver. This article presents the concepts and approaches underpinning one of the most exciting and ambitious modeling projects in the field of systems biology and systems medicine. This major multidisciplinary research program is aimed at developing a whole‐organ model of the human liver, representing its central physiological functions under normal and pathological conditions The model will be composed of a larger battery of interconnected submodels representing liver anatomy and physiology, integrating processes across hierarchical levels in space, time, and structural organization. In this article, we outline the general architecture of the liver model and present first step taken to reach this ambitious goal. WIREs Syst Biol Med 2012 doi: 10.1002/wsbm.1158

Report on EU-USA workshop: how systems biology can advance cancer research (27 October 2008).

The main conclusion is that systems biology approaches can indeed advance cancer research, having already proved successful in a very wide variety of cancer‐related areas, and are likely to prove superior to many current research strategies. Major points include: Systems biology and computational approaches can make important contributions to research and development in key clinical aspects of cancer and of cancer treatment, and should be developed for understanding and application to diagnosis, biomarkers, cancer progression, drug development and treatment strategies. Development of new measurement technologies is central to successful systems approaches, and should be strongly encouraged. The systems view of disease combined with these new technologies and novel computational tools will over the next 5–20years lead to medicine that is predictive, personalized, preventive and participatory (P4 medicine). Major initiatives are in progress to gather extremely wide ranges of data for both somatic and germ‐line genetic variations, as well as gene, transcript, protein and metabolite expression profiles that are cancer‐relevant. Electronic databases and repositories play a central role to store and analyze these data. These resources need to be developed and sustained. Understanding cellular pathways is crucial in cancer research, and these pathways need to be considered in the context of the progression of cancer at various stages. At all stages of cancer progression, major areas require modelling via systems and developmental biology methods including immune system reactions, angiogenesis and tumour progression. A number of mathematical models of an analytical or computational nature have been developed that can give detailed insights into the dynamics of cancer‐relevant systems. These models should be further integrated across multiple levels of biological organization in conjunction with analysis of laboratory and clinical data. Biomarkers represent major tools in determining the presence of cancer, its progression and the responses to treatments. There is a need for sets of high‐quality annotated clinical samples, enabling comparisons across different diseases and the quantitative simulation of major pathways leading to biomarker development and analysis of drug effects. Education is recognized as a key component in the success of any systems biology programme, especially for applications to cancer research. It is recognized that a balance needs to be found between the need to be interdisciplinary and the necessity of having extensive specialist knowledge in particular areas. A proposal from this workshop is to explore one or more types of cancer over the full scale of their progression, for example glioblastoma or colon cancer. Such an exemplar project would require all the experimental and computational tools available for the generation and analysis of quantitative data over the entire hierarchy of biological information. These tools and approaches could be mobilized to understand, detect and treat cancerous processes and establish methods applicable across a wide range of cancers.

Report on EU-USA workshop: how systems biology can advance cancer research.

The main conclusion is that systems biology approaches can indeed advance cancer research, having already proved successful in a very wide variety of cancer‐related areas, and are likely to prove superior to many current research strategies. Major points include: Systems biology and computational approaches can make important contributions to research and development in key clinical aspects of cancer and of cancer treatment, and should be developed for understanding and application to diagnosis, biomarkers, cancer progression, drug development and treatment strategies. Development of new measurement technologies is central to successful systems approaches, and should be strongly encouraged. The systems view of disease combined with these new technologies and novel computational tools will over the next 5–20years lead to medicine that is predictive, personalized, preventive and participatory (P4 medicine). Major initiatives are in progress to gather extremely wide ranges of data for both somatic and germ‐line genetic variations, as well as gene, transcript, protein and metabolite expression profiles that are cancer‐relevant. Electronic databases and repositories play a central role to store and analyze these data. These resources need to be developed and sustained. Understanding cellular pathways is crucial in cancer research, and these pathways need to be considered in the context of the progression of cancer at various stages. At all stages of cancer progression, major areas require modelling via systems and developmental biology methods including immune system reactions, angiogenesis and tumour progression. A number of mathematical models of an analytical or computational nature have been developed that can give detailed insights into the dynamics of cancer‐relevant systems. These models should be further integrated across multiple levels of biological organization in conjunction with analysis of laboratory and clinical data. Biomarkers represent major tools in determining the presence of cancer, its progression and the responses to treatments. There is a need for sets of high‐quality annotated clinical samples, enabling comparisons across different diseases and the quantitative simulation of major pathways leading to biomarker development and analysis of drug effects. Education is recognized as a key component in the success of any systems biology programme, especially for applications to cancer research. It is recognized that a balance needs to be found between the need to be interdisciplinary and the necessity of having extensive specialist knowledge in particular areas. A proposal from this workshop is to explore one or more types of cancer over the full scale of their progression, for example glioblastoma or colon cancer. Such an exemplar project would require all the experimental and computational tools available for the generation and analysis of quantitative data over the entire hierarchy of biological information. These tools and approaches could be mobilized to understand, detect and treat cancerous processes and establish methods applicable across a wide range of cancers.

Unraveling liver complexity from molecular to organ level: Challenges and perspectives

Biological responses are determined by information processing at multiple and highly interconnected scales. Within a tissue the individual cells respond to extracellular stimuli by regulating intracellular signaling pathways that in turn determine cell fate decisions and influence the behavior of neighboring cells. As a consequence the cellular responses critically impact tissue composition and architecture. Understanding the regulation of these mechanisms at different scales is key to unravel the emergent properties of biological systems. In this perspective, a multidisciplinary approach combining experimental data with mathematical modeling is introduced. We report the approach applied within the Virtual Liver Network to analyze processes that regulate liver functions from single cell responses to the organ level using a number of examples. By facilitating interdisciplinary collaborations, the Virtual Liver Network studies liver regeneration and inflammatory processes as well as liver metabolic functions at multiple scales, and thus provides a suitable example to identify challenges and point out potential future application of multi-scale systems biology.

Multi-bio and multi-scale systems biology

Systems Biology has received many different definitions since the term became more current 15 years ago. Some of those definitions have focussed on interactions. A systems approach is necessarily one about interactions, emphasising processes rather than individual components. The launch of the Physiome Project by the International Union of Physiological Sciences (IUPS) at around the same time introduced the need to take account of multi-scale interactions. But that still left a major gap. Many of the big questions in biology arise in much the same form in different areas of the biological sciences, and importantly across disciplinary domains including the physical, mathematical, engineering, as well as human and social sciences. Moreover, the insights have often been most productive when transferred from one area to another. Thus, microbiology has transformed many of our ideas about genomes and evolution. Plant biology was where mobile genetic elements were first discovered and characterised. Immunology is where some of the important insights into evolutionary biology developed, through the ability of the system to evolve its own genomes rapidly in response to challenges. Physiology has continued to be the guardian of higher-level functional biology, while bioengineering has provided the conceptual and mathematical methods to approach those functional questions more rigorously. Biology is beginning to meet the challenge of Claude Bernard, 150 years ago, when in his influential book Introduction to the Study of Experimental Medicine (Bernard, 1865, 1984) he wrote “[The] application of mathematics to natural phenomena is the aim of all science, because the expression of the laws of phenomena should always be mathematical.”1 But that is easier said than done. Biological sciences create very major challenges for mathematics, and systems biology is illustrating those challenges, sometimes quite painfully as we encounter problems of combinatorial explosion in the numbers of possible interactions. That is true even, especially, at the level of single cells. Even quite small metabolic pathways can become intractable. One approach to that problem is to seek to develop new mathematics (e.g. Simeonov et al., 2013; Longo and Mont evil, 2014) and new insights from physics (e.g. Auffray and Nottale, 2008). The present focussed issue arises from the conviction that some important insights might come from interactions between the different areas of biology, and importantly across disciplinary domains including the physical, mathematical, engineering, as well as human and social sciences. That was what motivated IUPS to approach other bio-unions adhering to the International Council

Systems Biology: a new hope for drug discovery?

The rapid expansion of biomedical information following the mapping of the human genome has contributed to significant advances in acquiring a highly detailed picture of disease mechanisms at the molecular level. This revolution in biomedical science has also generated hope and expectation for the delivery of novel treatments for serious illnesses. However, the reality is that despite this detailed information the return in terms of delivery of new medicines has been relatively modest.

Report on EU-USA Workshop

The main conclusion is that systems biology approaches can indeed advance cancer research, having already proved successful in a very wide variety of cancer‐related areas, and are likely to prove superior to many current research strategies. Major points include: Systems biology and computational approaches can make important contributions to research and development in key clinical aspects of cancer and of cancer treatment, and should be developed for understanding and application to diagnosis, biomarkers, cancer progression, drug development and treatment strategies. Development of new measurement technologies is central to successful systems approaches, and should be strongly encouraged. The systems view of disease combined with these new technologies and novel computational tools will over the next 5–20years lead to medicine that is predictive, personalized, preventive and participatory (P4 medicine). Major initiatives are in progress to gather extremely wide ranges of data for both somatic and germ‐line genetic variations, as well as gene, transcript, protein and metabolite expression profiles that are cancer‐relevant. Electronic databases and repositories play a central role to store and analyze these data. These resources need to be developed and sustained. Understanding cellular pathways is crucial in cancer research, and these pathways need to be considered in the context of the progression of cancer at various stages. At all stages of cancer progression, major areas require modelling via systems and developmental biology methods including immune system reactions, angiogenesis and tumour progression. A number of mathematical models of an analytical or computational nature have been developed that can give detailed insights into the dynamics of cancer‐relevant systems. These models should be further integrated across multiple levels of biological organization in conjunction with analysis of laboratory and clinical data. Biomarkers represent major tools in determining the presence of cancer, its progression and the responses to treatments. There is a need for sets of high‐quality annotated clinical samples, enabling comparisons across different diseases and the quantitative simulation of major pathways leading to biomarker development and analysis of drug effects. Education is recognized as a key component in the success of any systems biology programme, especially for applications to cancer research. It is recognized that a balance needs to be found between the need to be interdisciplinary and the necessity of having extensive specialist knowledge in particular areas. A proposal from this workshop is to explore one or more types of cancer over the full scale of their progression, for example glioblastoma or colon cancer. Such an exemplar project would require all the experimental and computational tools available for the generation and analysis of quantitative data over the entire hierarchy of biological information. These tools and approaches could be mobilized to understand, detect and treat cancerous processes and establish methods applicable across a wide range of cancers.

Systems biology of mammalian cells: a report from the Freiburg conference.

The third international conference on ‘Systems Biology of Mammalian Cells’ (SBMC 2010) was held in Freiburg, Germany, on 3–5 June 2010. The conference, which took place under the auspices of Annette Schavan, the German Federal Minister for Education and Research, was attended by 330 scientists from 18 countries (Fig. 1); there were 36 speakers and 175 posters were presented and actively discussed. The conference was organised by HepatoSys, the German Competence Network for Systems Biology of hepatocytes and its successor the German Virtual Liver Network. In 2004, HepatoSys was launched by the German Federal Ministry of Education and Research (BMBF) to investigate intracellular processes in hepatocytes. Since April 2010, the German Virtual Liver Network has been striving to understand these processes at the next level. Building on the results of HepatoSys, the German Virtual Liver Network has started to examine processes in cell assemblies up to the whole organ. In his opening speech the parliamentary state secretary of the BMBF, Helge Braun, emphasised the importance of Systems Biology for the future of medical research. To support this innovative field the BMBF has up to now invested s300 million for past, present and future Systems Biology projects. The chair of the organising committee, Jens Timmer, University of Freiburg, welcomed the international participants with an overview of the history of the meeting venue. Afterwards, Adriano Henney, Program Director of the German Virtual Liver Network, introduced the ambitious goals of the network. The project started in April 2010 and is financed by the BMBF with s42 million for 5 years.