Abstract IA08: Heterogeneous data management and integration for living biobanks

After years of enormous research efforts for the systematic cataloguing of genetic alterations with causative function in cancer, their exploitation in clinical oncology is now potentially at reach. Large-scale approaches for the systematic molecular characterization of human tumors—such as The Cancer Genome Atlas (TCGA)—eventually demonstrated their huge informative potential for the categorization of molecularly circumscribed tumor subpopulations featuring specific genetic lesions. However, the ultimate goal of “personalized medicine” requires the validation of such lesions as therapeutic targets and the definition of biomarkers for accurate prediction of sensitivity to rational treatments. These aims are not fulfilled yet, as the technical limitations and the descriptive essence of endeavors such as TCGA limited researchers' ability to link sequencing data with clinical outcomes in terms of prognosis and response to treatments. As a consequence of this, Nature was recently stating that: The end of TCGA (expected at the end of 2015) represents an opportunity for the field to balance its cancer-genomics projects more evenly between cataloguing mutations and studying their functional significance. Functional studies have had short shrift, whereas “sequencing a simple concept, and easier to communicate to policy-makers and the public” has taken the lead. Correcting that imbalance will lead to exciting discoveries for science and for patients (see Nature 508, 287-288; 2014). Patient-derived xenografts (PDX) offer new means to face this issue by combining the flexibility of preclinical analysis with the instructive value of population-based studies. A deep biological and molecular characterization of a large number of established tumor grafts could afford PDX-based approaches with the necessary statistical robustness for conducting reliable genotype-response correlation studies at the population level. To this aim, international efforts are on-going to constitute consortia, in which different groups from multiple countries share PDX models and their bio-molecular characterization in order to establish a higher-order resource available for the scientific community. Among these, EurOPDX puts together researchers from 14 EU countries that overall generated 1500+ PDX models from 30+ tumor types. These collaborative frameworks offer unique opportunities for the generation, development and validation of new hypotheses in cancer treatment and diagnosis. However, the