Abstract 1296: CanPathPro—development of a platform for predictive pathway modelling using genetically engineered mouse models
Authors: Christoph Wierling, Yann Herault, Jos Jonkers, Aspasia Ploubidou, Lucien Frappart, Jan Hasenauer, Julio Banga, Oliver Rinner, Valeriya Naumova, David Koubi, Bodo Lange
Journal: Cancer Research (2018)

Abstract Omics technologies are generating complex molecular datasets that are exponentially increasing the cancer knowledge base and opening up new therapeutic possibilities. However, current approaches to analysing such data are often confined to statistical and pattern recognition techniques, or at best modelling of a single cellular signalling pathway, rather than the complex cross-talks of pathways that determine cancer onset and progression and response to therapy. 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. CanPathPro (www.canpathpro.eu), an EU Horizon 2020 project, is addressing the challenge of predictive modelling of biological data by developing and refining bioinformatic and experimental tools for the evaluation and control of systems biology modelling predictions. Components comprise highly defined mouse and organotypic experimental systems, next-generation sequencing, SWATH-based proteomics and a systems biology computational model for data integration, visualisation and predictive modelling. Within CanPathPro, genetically engineered mouse models are used to follow the temporal changes occurring during cancer development, including the histology of the tumour, the genome and transcriptome using next-generation sequencing and the (phospho-)proteome using SWATH technology. The systems biology computational model is optimised in an iterative fashion through perturbation experiments of tumor-tissue-derived cell lines and organoids, permitting the validation of pathway and parameter information. In this way, CanPathPro takes a unique approach combining 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. The CanPathPro-generated platform will enable in silico identification of cancer signalling networks 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 innovative approach taken by CanPathPro is set to have broad and significant impact on diverse areas, from cancer research and personalised medicine to drug discovery and development, and ultimately improving outcomes for cancer patients. Citation Format: Christoph Wierling, Yann Herault, Jos Jonkers, Aspasia Ploubidou, Lucien Frappart, Jan Hasenauer, Julio Banga, Oliver Rinner, Valeriya Naumova, David Koubi, Bodo Lange. CanPathPro—development of a platform for predictive pathway modelling using genetically engineered mouse models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1296.