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 , 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 can not 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 . one way is to define an expected number of mutations per gene , using the mutation rate , and identify genes with more mutations than an expected threshold . this strategy assumes that genes that are mutated more frequently than expected are more likely to be drivers . several reports have used this strategy for the identification of cancer - related genes and driver alterations [ 2 - 4 ] . another possibility is to use a systems biology approach , in which genetic alterations are evaluated in the context of pathways , networks and functional modules [ 5 - 7 ] . instead of looking at specific genes , the systems biology approach prioritizes higher levels of genetic organization and depends extensively on computational methods that integrate and analyze data from different sources and platforms . for example , data on somatic mutations occurring in breast and colorectal tumors have been integrated with other types of data to provide a network - based view of genetic alterations occurring in these types of tumor . in another example , our group has recently integrated different types of data on genes coding for cell surface proteins to identify possible new targets for glioblastoma and colorectal tumors . survival rates are usually measured in months and the most used therapy produces a median survival of only 15 months . cancer genomics is important for gliomas in the sense that it may help to define classes of patient with distinct prognoses and/or responses to therapeutic strategies . recent reports from a johns hopkins university group   and from the cancer genome atlas research network   have provided a much broader view of the genetic alterations occurring in gliomas . although these studies have found single genes that seem to be important in gliomagenesis - such as idh1 , encoding isocitrate dehydrogenase 1 , which is often mutated in patients with a specific type of glioblastoma , the most lethal type of glioma   - the major pattern that emerged from these studies was extremely complex , with many new genetic alterations occurring in dozens of genes in each tumor . which alterations contribute to the development of cancer more recently , a systems biology approach was used by bredel et al .   to describe a network model of cooperative genetic changes in gliomas and , most importantly , to evaluate its clinical relevance in terms of patient survival . .   assumed that different genetic alterations act together to facilitate gliomagenesis in a coordinated and cooperative manner . they carried out genomic profiling on 45 glioma specimens and identified several altered regions spread along different chromosomes showing significant associations . interestingly , genes within the regions showing a significant association have a more dramatic change in their expression level than genes mapped to random genetic alterations . furthermore , the authors   noted a greater propensity for downregulation in gene expression within the significant regions . genes showing a high level of association with glioma - genesis were then mapped into the context of a network of protein - protein or functional interactions . this network was enriched with functional modules related to promotion of tumors and developmental pathways . using this network , the authors   selected a group of genes showing higher connectivity , assuming that alterations in those genes would affect more genes within the network . the association profile of these ' hub ' genes and the genes interacting with them was validated by an independent panel of 456 gliomas from several centers in the united states and the cancer genome atlas . this validated set of associations was significantly linked to poor survival rate in different groups of patients with gliomas . genes with a higher connectivity include pold2 , cycs , myc , akr1c3 , yme1l1 , anxa7 and pdcd4 . others [ 5 - 7 ] will have a significant impact on the development of diagnostic and therapeutic protocols . if the notion that gliomagenesis is the product of multiple reciprocal genetic alterations stands , this will explain the poor performance of therapeutic interventions that target a single gene product . bredel and colleagues   illustrate this point by showing that even a gene as prominent in gliomagenesis as the epidermal growth factor receptor gene egfr does not act in isolation , but rather in concert with other genetic alterations ; this predicts that the targeting of multiple genes will be more effective than monotherapeutic approaches . recently , the systems biology approach has been used to stratify breast cancer patients for personalized therapies , and for breast tumors an expression signature of dozens of genes has been used as a prognostic tool to guide adjuvant treatment decisions . it is reasonable to assume that this scenario is also true for other tumor types .
technological advances have enabled a better characterization of all the genetic alterations in tumors . 
 a picture that emerges is that tumor cells are much more genetically heterogeneous than originally expected . 
 thus , a critical issue in cancer genomics is the identification of the genetic alterations that drive the genesis of a tumor . 
 recently , a systems biology approach has been used to characterize such alterations and find associations between them and the process of gliomagenesis . here 
 , we discuss some implications of this strategy for the development of new therapeutic and diagnostic protocols for cancer .