One Step Forward Toward Identification of the Genetic Signature of Glioblastomas

Abstract

CANCER IS A DISEASE OF THE GENOME AT THE LEVEL of gene expression, epigenetic modifications such as DNA methylation, and DNA alterations. For more than 3 decades, many lines of research have shown that acquisition of genetic changes is a major and required step in the development of most cancers. First, ionizing radiation and chemicals that damage DNA and cause mutations also cause cancer. Second, genomic alterations such as translocations that result in the production of a specific gene fusion product are associated with some types of cancer. Such is the case for the translocations between chromosomes 9 and 22 in chronic myeloid leukemia and the translocation between chromosomes 15 and 17 in acute promyelocytic leukemia. Third, the introduction of genomic DNA from human cancer cells into normal cells can render the normal cells cancerous. In the past 2 decades, many genomic alterations have been identified in cancer. Sequencing of the human genome and improved high-throughput DNA sequencing technologies have provided the tools for a comprehensive identification of the most common genetic alterations as well as nongenetic changes in the genome in cancer cells. Identification of these alterations has the potential to unveil the Achilles’ heel of many different forms of cancer. The feasibility of this approach is exemplified by the use of imatinib for the treatment of chronic myeloid leukemia, as the drug effectively blocks the deleterious activity of the single genetic alteration triggering the disease. However, most solid tumors, including glioblastoma multiforme (GBM), the deadliest of all brain tumors, exhibit a much more diverse pattern of genetic alterations, which until recently had not been comprehensively characterized. Two recent studies of genetic and functional genomic changes throughout the genome in GBM have pointed at key genes and pathways that are altered at the DNA level, at the expression level, or at both. Parsons and colleagues resequenced the coding regions of 20 661 genes and examined expression of these genes with next-generation DNA sequencing technologies in 22 glioblastomas and identified both known and new key changes in this cancer. In another study, a consortium of scientists in The Cancer Genome Atlas studied genetic, epigenetic, and genomic alterations in 206 GBM tumors compared with controls and identified several known and several new genes that play a role in the development of the disease. Two articles in this issue of JAMA take this global genomic approach a step further by identifying and validating networks of altered genes that may play a crucial role in the development and progression of GBM, providing additional potential targets for novel therapies. While numerous recurrent genetic abnormalities have been discovered in cancer, identifying which ones act as indispensable contributors of disease development and progression and which ones act as mere bystanders is a major challenge that hitherto has not been met. This problem has become particularly acute recently with new next-generation DNA sequencing technologies that sample many more base pairs, even to the level of sequencing of whole genomes, than classic Sanger sequencing. This vastly increased capability has allowed investigators to begin identifying a very large number of DNA sequence changes, especially in cancer, so distinguishing which ones are of functional significance and contribute to cancer phenotypes in primary or secondary ways is becoming a critical issue. To begin addressing this problem, Bredel et al hypothesized that a combination of distinct chromosomal alterations work together to facilitate gliomagenesis in a cooperative fashion. Their starting material consisted of 45 glioma specimens of varying morphology, which were assessed for the presence of altered gene dosage by using a complementary DNA microarray containing more than 40 000 elements corresponding to more than 27 000 gene clusters, thus providing extensive coverage of known proteincoding genes. Bredel et al identified 9 networking regions on chromosomes 1, 7, 8, 9, 10, 12, 13, 19, 20, and 22, displaying 37 associations. Then, by analyzing a different set of 219 GBMs that were collected and studied by The Cancer Genome Atlas, the same approach revealed a similar association and