Cancer gene profiling has greatly profited from the progress in high-throughput technologies, including microarray-, sequencing-, and bioinformatics-based methods. The flood of data generated during the last decade has provoked a panel of "-omics" fields that significantly changed our understanding of malignant diseases. However, while the terms "-omics" and "-ome" in principle refer to the completeness of a genetic approach, we are in fact far from a complete understanding of cancer progression. We may understand gene expression patterns better and successfully use gene signatures for outcome prediction and prognosis, but truly promising molecular targets still have to find their way into novel therapeutic concepts. In this chapter, we will show how more comprehensive strategies, integrating multiple layers of genetic information, might in the future provide a more profound functional understanding of cancer.