Systems Biology of Colorectal Cancer Symposium, London, UK
The SYSCOL project is multidisciplinary and integrates basic research and clinical research based on patient samples with computational and experimental research. The data generated together with the methods and tools developed within the project will lead to a better understanding of the complex networks of genes and gene regulatory systems behind colorectal cancer. We also expect the methods and tools to be applicable to the study of other types of cancer forms as well as having broader implications on research, prevention and treatment of all multigenic disorders.
SYSCOL brings together a strong team of researchers with complementary expertise in computer science, statistics, medical genetics, genomics and systems biology from across Europe and the US. The research program of this consortium will also build strong ties between medical research, genomics and systems biology groups, thus significantly strengthening medically oriented systems biology research in Europe.
The overall objective of the SYSCOL project is to advance the understanding of the formation of colorectal cancer and increase the likelihood of the development of effective colorectal cancer prediction tools and therapies, with the ultimate aim of reducing mortality rates from colorectal cancer.
SYSCOL aims to systematically map out the changes and variations in the genetic code that increase individuals’ risks of developing colorectal cancer, using the tools of Systems Biology. The variants will be used to identify the mechanisms that are required for colorectal cancer growth and to develop a model for colorectal cancer formation. The model will describe cellular pathways that contribute to tumor formation and explain in detail how the genetic disposition of an individual can activate the expression of genes that cause uncontrolled cell growth and lead to cancer. This model will subsequently be used to discover novel therapeutic targets, guide genetic screening in order to identify individuals with a heightened risk for developing colorectal cancer and to classify patients into subgroups in order to personalise medical treatments. This information can be used to identify novel treatment targets that are more susceptible to drugs than the currently known pathways.
Full program can be found at the SYSCOL webpage:http://syscol-project.eu