CHAPTER 100 Molecular Genetics and the Development of Targets for Glioma Therapy
The modern-day classic Death Be Not Proud by John Gunther chronicled the events surrounding the diagnosis, treatment, and eventual death of his teenage son Johnny, who died of glioblastoma more than half a century ago.1 The anguish he felt as he watched his son suffer was tempered by the belief that someday, perhaps even soon enough for Johnny, there would be a cure or an effective treatment of this horrible disease.
Molecular Genetics of Cancer: The Origins of Cancer Genetics
Our general understanding of the molecular genetics of cancer pathogenesis has advanced significantly in the past 30 years, but the foundations for these discoveries were laid a century ago in 1910, when Peyton Rous, having just graduated from medical school, discovered that cancer could be transmitted from cell culture to animals by using a cell-free ultrafiltrate containing an avian virus. He surmised that certain elements carried by the virus were the cause of cancer! His work lay dormant for many years and was revived in part by Watson and Crick’s groundbreaking discovery that deoxyribonucleic acid (DNA) polymers contained the code necessary for the transmission and interpretation of genetic information.2 Within years of this seminal discovery there was consensus that the cancer-causing element discovered by Rous was in fact v-src, a viral gene capable of transforming infected cells.3 Harold Varmus and Michael Bishop later proved that a mammalian version of the Rous viral cancer gene, called c-src, also caused tumors in mammals. It is now clear that mammalian genes gone awry are the cause of cancer.
Molecular Genetic Tools and the Study of Cancer
DNA Manipulation Techniques in Cancer
Genetic Manipulation in Vivo
Gene Expression in Mice
To verify that a gene defect is the cause of a disease, it is necessary to evaluate the in vivo biologic consequences of genetic alterations. This can be accomplished by using transgenic or knockout mice. Such genetic manipulation of disease-associated genes results in genetically engineered models (GEMs) of disease.4 Genetic manipulation in mice is now fairly sophisticated, and gene expression can be induced or halted in animals with remarkable temporal and cell-specific specificity.
Transgenic Mice
With this technology, human genes can be transferred to animals and their ability to cause disease ascertained. By linking the gene of interest with a tissue-specific promoter, expression can be restricted to a particular organ or cell type. Transgenic mice can also be used to measure the activity of signal transduction pathways or other molecular functions of a cell. For example, p53 activity can be measured by introducing the consensus sequence for p53 binding upstream of the firefly luciferase gene, thereby inducing transcription of the luciferase gene upon p53 binding. The luciferase gene converts a substrate called luciferin into light, and the photons emitted from the reaction can be measured directly by a camera. Emission of light from living organisms is known as bioluminescence. In the p53/luciferase scenario, mice that produce luciferase after p53 binding will convert luciferin into a bioluminescence signal, and this signal serves as an indirect measurement of the DNA binding activity of p53.5 The potential applications of transgene technology in mice are virtually unlimited, and glioma mouse models are beginning to use transgenic animals to measure the proliferation rates of tumors, measure the status of tumor signal transduction pathways, and study a host of other events that occur during the genesis of glioma.
Conditional Knockouts
Conditional knockout mice are created by introducing agents that selectively remove genetically engineered sequences from mouse chromosomes.4 In one such system, known as Cre-lox, the knockout mice are created as described earlier, except that palindromic loxP sites flank the target gene DNA construct. The Cre recombinase protein identifies loxP sites, and the DNA sequence between flanking loxP sites can be excised by the Cre protein to yield a functional knockout. The advantage of this system is that Cre expression can be spatially restricted to certain cell types through the use of tissue-specific promoters. Moreover, Cre constructs may be engineered so that Cre expression is induced only when certain drugs are administered to an animal expressing the Cre transgene. Such temporal and spatial control of knockout genes enables realistic modeling of carcinogenesis because this system can re-create a multistep biologic situation in which specific genes are deleted or overexpressed at specific junctures during tumor progression.
Somatic Cell Gene Transfer
Somatic cell gene transfer involves the transfer of DNA to nongermline cells, often using retroviruses engineered to contain specific genes.4 The concept of somatic cell gene transfer dates back to the discovery of Rous sarcoma virus (RSV) by Rous. Injection of RSV into the organs of several different types of animals results in the formation of tumors because of transfer of the v-src oncogene to somatic cells. However, RSV-based somatic cell gene transfer has some serious disadvantages: (1) there is no control over the type of cells infected by the virus and (2) the use of RSV somatic cell gene transfer allows the examination of only one oncogene.
One somatic cell gene transfer system that obviates these problems is the RCAS/tv-a system.4 This system combines transgene technology with viral infection to achieve cell-specific, gene-specific somatic cell transfer of a number of different oncogenes. Replication-competent avian leukemia virus (ALV) family splice acceptor (RCAS) vectors can be engineered to contain specific genes. Moreover, the RCAS virus specifically infects cells that express the ALV type a receptor tv-a. Thus, in transgenic animals engineered to express tv-a only in certain cell types, RCAS vectors can be used to deliver oncogenes in a cell type–specific manner.
DNA Hybridization Techniques and Array Platform Technologies
Fluorescence In Situ Hybridization
Cancer, especially in its most malignant forms, progresses by accumulating multiple errors in the genome of affected organisms. Many of the genetic errors occurring in cancer specifically affect genes that normally function to repair damaged DNA. As a result of errors in DNA damage response mechanisms, the entire genome of an affected organism becomes prone to error, thereby leading to a phenomenon called genomic instability. One consequence of genomic instability is that damaged genomic DNA is prone to single- and double-strand breaks. At a chromosomal level, these breaks can result in very large losses, gains, or translocations of chromosomal regions. These chromosomal areas encode genes or regulatory elements of genes involved in cancer initiation and progression, and identification of these abnormal chromosomal regions is important for a general understanding of cancer biology. As a consequence, cytogenetics, which encompasses the study of chromosomal structure, has become a central part of cancer biology.6
Comparative Genomic Hybridization Arrays
Although FISH has significantly advanced our progress in the discovery of abnormal target genes and chromosomes, the technique is imperfect for solid tumors in that it requires preparation of tumor metaphase chromosomal spreads that do not differ markedly from normal tissue. Because advanced solid tumors acquire many chromosomal abnormalities, it is often impossible to interpret tumor chromosomal spreads with accuracy inasmuch as chromosomes in solid tumors are often altered beyond recognition. To combat this problem, a variant of FISH called comparative genomic hybridization (CGH) was invented in the early 1990s.6 CGH obviates the need for chromosome spreads by using differentially labeled test and reference genomic DNA oligonucleotide samples, which can then be applied onto genomic DNA microarrays. CGH arrays permit unprecedented ability to evaluate chromosomal abnormalities in cancer. In particular, this technique is especially sensitive for the identification of changes in DNA copy number, such as the increases in gene copy number that occur at the epidermal growth factor receptor (EGFR) locus in a significant number of glioblastomas.
Single Nucleotide Polymorphism Genotyping Arrays
Single nucleotide polymorphism (SNP) analysis is a powerful molecular genetic tool capable of identifying changes in DNA copy number, point mutations, and LOH.6 SNPs are nonfunctional point mutations in the genome that occur at a frequency of about 1% in the human genome. They occur at a frequency of one SNP every few hundred base pairs of genomic DNA. Because many SNPs have been sequenced, they can be used to compare the haplotypes of cancer genomes with other nontumor DNA from the same individual. Moreover, because the genomic location of SNPs is known, changes in the SNP genotype of tumor DNA identify genomic regions that can be further analyzed by PCR to detect precise DNA aberrations (point mutations, deletions, insertions, and so on) that underlie the changes in SNP haplotype. Furthermore, because of the availability of microarray platforms, up to 500,000 SNPs can be analyzed in a single experiment, thus allowing excellent genomic resolution.
Gene Expression Arrays
CGH, FISH, and SNP techniques identify changes in genomic DNA. Although these platforms can be used to make inferences about gene expression, they do not provide direct data about the transcription of these genes from DNA to messenger RNA (mRNA). The importance of studying changes in gene expression is aptly represented by the expression pattern of vascular endothelial growth factor (VEGF) during the genesis of glioma. Although the VEGF gene is rarely mutated in glioblastoma multiforme (GBM), VEGF mRNA and protein levels are often markedly elevated, which leads to an increase in tumor angiogenesis and virulence.7
Applying Molecular Genetic Tools to Glioma Analysis
Phillips and colleagues recently used both gene expression and CGH profiling of high-grade gliomas to explore genes that correlate with patient survival.8 Using gene expression microarrays, they identified three gene clusters that correlate with patient survival. Consistent with these findings, CGH analysis of patients with shorter survival showed frequent loss of the phosphatase and tensin homologue from chromosome 10 (PTEN) tumor suppressor locus and gains at the EGFR and phosphatidylinositol-3′-kinase (PI3K) oncogene loci in comparison to patients with longer survival.
Perhaps the most comprehensive single genetic analysis study of human gliomas to date comes from the efforts of The Cancer Genome Atlas (TCGA), a national initiative whose goal is to identify and catalogue the wide array of genetic aberrations that cause cancer.9 TCGA uses a number of genetic tools, including CGH, SNP genotyping, PCR genotyping, gene expression arrays, microRNA profiling, and DNA methylation arrays, to characterize a cancer specimen. Using 206 GBM samples in a pilot study, the group has identified hitherto unknown genetic aberrations that probably contribute to glioma genesis. In particular, they identified novel deletions of NF1 and PARK2 in glioma samples and characterized NF1