Data-driven cancer genome interpretation for personalised cancer treatment

CGI-Clinics aims at improving personalized medicine in oncology by optimizing genomic data interpretation (after sequencing and before advising on compatible targeted therapies). Interpretation is a bottleneck for the full deployment and broad accessibility of Next Generation Sequencing (NGS) in cancer management. The project tackles the 3 main hurdles in the interpretation of cancer mutations: it is not systematic; it deals with a majority of variants of unknown significance, and it fails to empower patients. Currently the interpretation of tumour genomic data relies on the work of experts reviewing scattered databases and resources, in a time-consuming process that may lead to sub-optimal clinical decisions. CGI-Clinics will systematize the interpretation process by integrating relevant public and private databases in a one-stop shop tool, with the possibility to organize virtual molecular tumour boards co-facilitated by reference hospitals. The project will have three phases: setup (to assess needs), validation (a pilot with the 9 clinical partners) and replication (in 30 hospitals across the EU). It will enable democratization of genomic data interpretation (independent of a hospital’s size, resources, and profiling technology) and provide health economics validation. Relying on a systematic automatic learning platform, CGI-Clinics will increase the share of interpretable variants in tumours (from the current 9-12% to at least 50%), and features that constitute biomarkers of drug response. The interpretation process is complex for most cancer patients, alienating them from knowledge of their illness. CGI-Clinics will build EduCGI, a web-based tool to help patients understand the information gained through interpretation of their tumours, facilitating informed discussions with clinicians, and sharing their data for research. Ultimately, the project is built to inform policymakers on cancer management and to empower patients.