Modelling cancer development Carcinogenesis is a complex process involving activation or silencing of various signalling pathways. A European consortium decided to model the combined influence of two cancer-related pathways in the development of liver cancer. Health © Thinkstock The liver is a vital organ of multiple functions, including protein synthesis, detoxification and production of digestive enzymes. Understanding how cells establish the structure of the liver and how they behave during regeneration or cancer formation is poorly understood. To contribute to knowledge in this area, the EU-funded Cancersys project focused on developing a model of liver architecture and hepatocellular carcinoma. Firstly, project members established a procedure for tissue spatial-temporal modelling based on confocal laser scans, image processing and three-dimensional tissue reconstruction. This technique was applied to understand liver microarchitecture during cancer formation. The Cancersys model captured liver lobule structure, focusing on veins, and normal and malignant cell types. It facilitated the analysis of various parameters such as cell proliferation status and rate, cell death rate and three-dimensional cell orientation during tumour formation. In a second step, the beta catenin and ras signalling pathways were integrated in the model. The aim was to predict the impact of the activation of these cancer-related pathways on single cell decision and tissue organisation. By coupling the modelling approach with whole genome expression profiling from hepatocytes with activated beta-catenin or ras signalling, scientists identified negative interactions between both pathways. Signalling through beta-catenin led to attenuation of expression of genes that are positively regulated by the ras signalling module and vice versa. Project scientists planned to test candidate molecules responsible for this interaction in transgenic mice of inducible beta-catenin and ras signalling. The Cancersys model offered a predictive approach for determining the role of cancer-related signalling cascades in hepatocellular carcinoma. Partners are hopeful that their model will lead to the design of effective intervention and therapeutic strategies against cancer.
