We propose a novel, data-driven concept of an integrated cell, iCell, that integrates several types of systems-level genomic data. We construct iCells of cancers and the corresponding healty tissues. We identify new genes involved in cancer, many of which have previously been of unknown function and cannot be identified as different in cancer in any specific data type in isolation from others. We biologically validate that they have a role in cancer and find additional support via retrospective survival analyses of thousands of patients. Our methodology is universal and enables integrative comparisons of diverse molecular data over cells and tissues.