Cancers are genetic disease arising from the accumulation of multiple molecular alterations in affected cells. Large-scale genomic, transcriptomic and proteomic analyses have established comprehensive catalogues of molecules which are altered in their structure and/or abundance in malignant tumors as compared to healthy tissues. Far less developed are concepts and methods to integrate data from different sources and to directly interrogate gene functions on a large scale in order to differentiate “driver” alterations, which directly contribute to tumor progression, from indolent “passenger” alterations. As a consequence, examples of successful translation of knowledge generated from “omics” approaches into novel clinical concepts and applications are scarce.Pancreatic cancer is a prime example of this dilemma. Representing the 4th to 5th most common cause of cancer related deaths, it is a disease with a major socioeconomic impact. Despite enormous advances in the identification of molecular changes associated with the disease, new treatment options have not emerged. Thus, 5-year survival rates remain unchanged at a dismal 6%, the lowest for all solid tumors.Using pancreatic cancer as a model disease, the goal of this integrative project is to develop novel cellular and animal models, as well as novel strategies to generate, analyze and integrate large scale metabolic and transcriptomic data from these models, in order to systematically characterize and validate novel targets for therapeutic intervention. In addition to the general tumor cell population, special consideration will be given to sub-populations of tumor-initiating cells, a.k.a. tumor stem cells.To this end, the consortium comprises i) SMEs with strong focus on technology development, ii) clinical and academic partners with extensive experience in pancreatic cancer molecular biology and management of pancreatic cancer patients, and iii) technology and data analysis experts from academic groups.