Insights into gliomagenesis: systems biology unravels key pathways

One of the most important steps in the genesis of a tumor is the acquisition of both genetic and epigenetic alterations. Although a significant number of cancer-related genes have been identified in the past few decades [1], the emergence of technologies that allow genome-wide screening for alterations in large collections of tumors has affected the field of cancer biology in a dramatic way. The picture that is emerging is that most tumors are genetically heterogeneous and accumulate a large number of genetic and epigenetic alterations. The current level of genetic heterogeneity observed in tumors is, nevertheless, expected to increase in the next few years with the emergence of next-generation sequencing technologies. Collectively, these technologies allow the detection of rare genetic variants present in less than 10% of the tumor cells and that cannot be detected by conventional Sanger sequencing.Given this, the major challenges in cancer genomics nowadays are: to discriminate alterations that are causally involved and drive tumorigenesis (the drivers) from those that have been accumulated by chance and are neutral to the process (the passengers); to understand the synergistic effects of these alterations on critical cell signaling pathways and on tumor behavior; and to use all this information to improve disease management and patient survival.Although the driver genetic alterations are important in terms of developing new effective therapeutic strategies, the passengers are also important in the sense that they constitute a supply of genetic alterations that can be used by the tumor to respond to a new set of environmental conditions. For example, passenger genetic alterations do not contribute to tumor growth but can be important in the resistance of a tumor to a chemo- or radiotherapeutic strategy.How can we identify drivers? One way is to define an expected number of mutations per gene, using the mutation rate, and identify genes with more mutations than an