An international group of scientists from six countries bring together their expertise to develop a combined experimental and systems biology platform for predictive modelling of cancer signalling. The EU Horizon 2020 funded project, co-ordinated by Alacris Theranostics GmbH, Berlin, will run for 5 years with a budget of almost €11 million.
Only a few decades ago, cancer was invariably a fatal disease. Nowadays, cancer screening and ever-emerging new therapies have significantly decreased the mortality rate, despite the higher incidence of cancer in the ageing European population. However, the great molecular complexity and heterogeneity exhibited by most cancers, is – still – a huge challenge in cancer treatment.
Recent technological developments have enabled the generation of molecular datasets that are exponentially increasing the knowledge base on cancer. Yet, a systems biology based approach is required to understand the cross-talk between pathways as well as the underlying molecular basis of cancer development and progression.
New solutions to optimally exploit this wealth of data for basic research, better treatment and stratification of patients, as well as more efficient targeted drug development are required. The European Research Consortium CanPathPro now takes a unique approach and brings together classic cancer research with omics data and systems biology tools, to develop and validate a new biotechnological application: a combined systems and experimental biology platform for generating and testing cancer signalling hypotheses in biomedical research.
Previous bioinformatic attempts in this direction have been confined to pattern recognition or, at best, modelling of single pathways. Such approaches often cannot take into account the complexity of living organisms, comprising numerous pathways and their cross-talk. These features are of paramount significance in cancer, where signalling complexity is the major determinant of disease progression and drug response.
To achieve its objective, CanPathPro will develop and refine bioinformatic and experimental tools for the evaluation of systems biology modelling predictions. Components comprise highly defined mouse and organotypic experimental systems, next generation sequencing, quantitative proteomics and a systems biology computational model for data integration, visualization and predictive modelling.
The CanPathPro-generated platform will enable the in silico (computer-based) identification of cancer signalling networks that are critical for tumour development and will allow users to predict activation status of individual pathways, following integration of user (or public) data sets in the pathway models.
The in silico modelling and high-performance computing tools will provide completely new solutions for researchers, SMEs and industry for interpretation and analysis of omics data as well as for deriving and testing new hypotheses. Thus, prediction of cancer progression and drug efficacy shall be maximized to, in the long run, significantly improve outcomes for the majority of cancer patients.