Project: Systems Analysis of TNF and TRAIL Signalling Pathways in Hepatocytes

Hepatocellular carcinoma is one of the most common forms of cancers worldwide. Therapeutic options are limited due to chemo-resistance to current therapies, mostly caused by failure to undergo cell death (apoptosis). To understand how the apoptosis signalling networks are regulated in normal hepatocytes and dysregulated in cancer is of key importance for the design of effective cancer therapies. Systems level understanding of complex biological pathways and networks requires knowledge of its units, structures and temporal processes. In this project we will investigate the dynamic regulation and threshold of apoptotic and non-apoptotic signalling pathways induced by death receptor signalling in normal and malignantly transformed hepatocytes. Our project aims to understand and predict the basic biological system that governs pro- and anti-apoptotic signalling in normal versus transformed hepatocytes triggered by death receptor signalling. We will build Dynamic Nested Effects Models (D-NEM) based on our data to identify critical points for pathway regulation. These statistical models will be used to reconstruct pathway activity in hepatocytes. In addition to providing specific insight into apoptosis signalling on a systems level in normal versus transformed cells, we expect that our study will also lead to new insights on principal mechanisms of inflammation-induced tumourigenesis and of therapy resistant tumours. Thereby, these studies will increase our knowledge as to how resistance can be overcome in a tumour-specific manner, ultimately providing new and improved approaches to therapy and diagnosis.

Acronym	ApoNET
Project Results (after finalisation)	Understanding complex biological pathways and networks on a systems level requires knowledge of its units, structures and temporal processes. The ApoNET research project (http://www.apoptosis-networks.eu) aimed at developing computational models to reconstruct the regulation of signalling networks. The project combined the scientific expertise of three European project partners in high-throughput biology, computational modeling and translational research. Michael Boutros and his team at the Department for Cell and Molecular Biology within the University of Heidelberg and the DKFZ work on signalling networks using model systems and human cells. At the Tumour Immunology Unit within the Faculty of Medicine, Imperial College London, Henning Walczak's team is identifying new ways of treating cancer and inflammatory diseases. Rainer Spang leads the Computational Diagnostics Group at the Institute for Functional Genomics within the Regensburg reconstructing cell signalling pathways. Making use of recent technological advancements the ApoNET consortium investigated signalling pathway structures in normal and malignantly transformed liver cells. Liver cancer is one of the most common forms of cancer worldwide. Therapeutic options are still limited, because tumour cells often become resistant to conventional drugs - mostly as they fail to undergo programmed cell death (apoptosis). The network of signalling cascades determining whether a cell enters the apoptotic pathway or survives is complex and only partially understood. Our project aimed at shedding more light onto these processes and their dysregulation in cancer by developing improved statistical models based on gene regulatory networks. As a result we have developed novel computational pathway modelling methods as a tool to reconstruct complex signalling networks. In parallel we generated gene expression data by high-throughput RNA-sequencing of perturbed and unperturbed signalling pathways. Data were fed into the modelling pipeline to reconstruct signalling networks on a systems level and to identify critical steps in pathway regulation as potential targets for therapeutic intervention. Our study provided new insight into the signalling pathway cross talk in liver cancer cells. Furthermore, we found new evidence that another pathway originally not included in the study influences signal transduction in the inflammatory pathways analysed.
Network	ERASysBio+
Call	ERASysBio+-2008-01

Project partner

Number	Name	Role	Country
1	University of Heidelberg	Coordinator	Germany
2	Imperial College London	Partner	United Kingdom
3	University of Regensburg	Partner	Germany