Glioblastoma, the most aggressive primary brain tumor in humans, exhibits a large degree of molecular heterogeneity. Understanding the molecular pathology of a tumor and its linkage to behavior is an important foundation for developing and evaluating approaches to clinical management. Here we integrate array-comparative genomic hybridization and array-based gene expression profiles to identify relationships between DNA copy number aberrations, gene expression alterations, and survival in 34 patients with glioblastoma. Unsupervised clustering on either profile resulted in similar groups of patients, and groups defined by either method were associated with survival. The high concordance between these separate molecular classifications suggested a strong association between alterations on the DNA and RNA levels. We therefore investigated relationships between DNA copy number and gene expression changes. Loss of chromosome 10, a predominant genetic change, was associated not only with changes in the expression of genes located on chromosome 10 but also with genome-wide differences in gene expression. We found that CHI3L1/YKL-40 was significantly associated with both chromosome 10 copy number loss and poorer survival. Immortalized human astrocytes stably transfected with CHI3L1/YKL-40 exhibited changes in gene expression similar to patterns observed in human tumors and conferred radioresistance and increased invasion in vitro. Taken together, the results indicate that integrating DNA and mRNA-based tumor profiles offers the potential for a clinically relevant classification more robust than either method alone and provides a basis for identifying genes important in glioma pathogenesis.

https://cancerres.aacrjournals.org/content/canres/65/5/1678.full.pdf

Integrated array-comparative genomic hybridization and expression array profiles identify clinically relevant molecular subtypes of glioblastoma

Advances in high-throughput technologies allow for measurements of many types of omics data, yet the meaningful integration of several different data types remains a significant challenge. Another important and difficult problem is the discovery of molecular disease subtypes characterized by relevant clinical differences, such as survival. Here we present a novel approach, called perturbation clustering for data integration and disease subtyping (PINS), which is able to address both challenges. The framework has been validated on thousands of cancer samples, using gene expression, DNA methylation, noncoding microRNA, and copy number variation data available from the Gene Expression Omnibus, the Broad Institute, The Cancer Genome Atlas (TCGA), and the European Genome-Phenome Archive. This simultaneous subtyping approach accurately identifies known cancer subtypes and novel subgroups of patients with significantly different survival profiles. The results were obtained from genome-scale molecular data without any other type of prior knowledge. The approach is sufficiently general to replace existing unsupervised clustering approaches outside the scope of bio-medical research, with the additional ability to integrate multiple types of data.

/pdf/a-novel-approach-for-data-integration-and-disease-subtyping-4o5k18pbrj.pdf

A novel approach for data integration and disease subtyping

Conventional cytogenetic and comparative genomic hybridization (CGH) studies in brain malignancies have shown that glioblastoma multiforme (GBM) is characterized by complex structural and numerical alterations. However, the limited resolution of these techniques has precluded the precise identification of detailed specific gene copy number alterations. We performed a genome-wide survey of gene copy number changes in 20 primary GBMs by CGH on cDNA microarrays. A novel amplicon at 4p15, and previously uncharacterized amplicons at 13q32-34 and 1q32 were detected and are analyzed here. These amplicons contained amplified genes not previously reported. Other amplified regions containg well-known oncogenes in GBMs were also detected at 7p12 (EGFR), 7q21 (CDK6), 4q12 (PDGFRA), and 12q13-15 (MDM2 and CDK4). In order to identify the putative target genes of the amplifications, and to determine the changes in gene expression levels associated with copy number change events, we carried out parallel gene expression profiling analyses using the same cDNA microarrays. We detected overexpression of the novel amplified genes SLA/LP and STIM2 (4p15), and TNFSF13B and COL4A2 (13q32-34). Some of the candidate target genes of amplification (EGFR, CDK6, MDM2, CDK4, and TNFSF13B) were tested in an independent set of 111 primary GBMs by using FISH and immunohistological assays. The novel candidate 13q-amplification target TNFSF13B was amplified in 8% of the tumors, and showed protein expression in 20% of the GBMs. This high-resolution analysis allowed us to propose novel candidate target genes such as STIM2 at 4p15, and TNFSF13B or COL4A2 at 13q32-34 that could potentially contribute to the pathogenesis of these tumors and which would require futher investigations. We showed that overexpression of the amplified genes could be attributable to gene dosage and speculate that deregulation of those genes could be important in the development and progression of GBM. Our findings highlight the important influence in GBM of signaling pathways such as the PI3K/AKT, consistent with the invasive features of this tumor.

/pdf/identification-of-novel-candidate-target-genes-in-amplicons-2iri56va80.pdf

Identification of novel candidate target genes in amplicons of Glioblastoma multiforme tumors detected by expression and CGH microarray profiling

Glioblastoma is a therapeutic challenge as a highly infiltrative, proliferative, and resistant tumor. Among novel therapeutic approaches, proteasome inhibition is very promising in controlling cell cycle and inducing apoptosis. This study investigated the effect of ritonavir, a protease inhibitor of the HIV and a proteasome modulator, on glioma cells. The hypothesis was that proteasome modulation, mainly by only inhibiting proteasome chymotrypsin-like activity, could be sufficient to control tumor progression. The experiments were done on a human glioblastoma-derived GL15 cell line and a rat nitrosourea-induced gliosarcoma 9L cell line. Culturing conditions included monolayer cultures, transplantations into brain slices, and transplantations into rat striata. The study demonstrates that ritonavir, by inhibiting the chymotrypsin-like activity of the proteasome, has cytostatic and cytotoxic effects on glioma cells, and can induce resistances in vitro. Ritonavir was unable to control tumor growth in vivo, likely because the therapeutic dose was not reached in the tumor in vivo. Nevertheless, ritonavir might also be beneficial, by decreasing tumor infiltration, in the reduction of the deleterious peritumor edema in glioblastoma.

/pdf/effects-of-the-proteasome-inhibitor-ritonavir-on-glioma-2x3qc4tzbu.pdf

Effects of the proteasome inhibitor ritonavir on glioma growth in vitro and in vivo

To identify target genes for the hemizygous deletions of chromosome 13 that are recurrently observed in malignant gliomas, we performed genome-wide DNA copy-number analysis using array-based comparative genomic hybridization and gene expression analysis using an oligonucleotide-array. The response gene to complement 32 (RGC32) at 13q14.11 was identified as a deletion target, and its expression was frequently silenced in glioma cell lines compared with normal brain. Levels of RGC32 mRNA tended to decrease toward higher grades of primary astrocytomas, especially in tumors with mutations of p53. Expression of RGC32 mRNA was dramatically increased by exogenous p53 in a p53-mutant glioma cell line, and also by endogenous p53 in response to DNA damage in p53+/+ colon-cancer cells, but not in isogenic p53-/- cells. Chromatin immunoprecipitation and reporter assays demonstrated binding of endogenous p53 protein to the promoter region of the RGC32 gene, implying p53-dependent transcriptional activity. Transiently and stably overexpressed RGC32 suppressed the growth of glioma cells, probably owing to induction of G2/M arrest. Immunocytochemical analysis revealed a concentration of RGC32 protein at the centrosome during mitosis. RGC32 formed a protein complex with polo-like kinase 1 and was phosphorylated in vitro. These observations implied a novel mechanism by which p53 might negatively regulate cell-cycle progression by way of this newly identified transcriptional target. Our results provide the first evidence that RGC32 might be a possible tumor-suppressor for glioma, that it is directly induced by p53, and that it mediates the arrest of mitotic progression.

/pdf/rgc32-a-novel-p53-inducible-gene-is-located-on-centrosomes-50poordsbs.pdf

RGC32, a novel p53-inducible gene, is located on centrosomes during mitosis and results in G2/M arrest.

Various genomic alterations have been detected in glioblastoma Chromosome 7p, with the epidermal growth factor receptor locus, together with chromosome 10q, with the phosphatase and tensin homologue deleted in chromosome 10 and deleted in malignant brain tumors-1 loci, and chromosome 9p, with the cyclin-dependent kinase inhibitor 2A locus, are among the most frequently damaged chromosomal regions in glioblastoma In this study, we evaluated the genetic status of 32 glioblastomas by comparative genomic hybridization; the sensitivity of comparative genomic hybridization versus differential polymerase chain reaction to detect deletions at the phosphatase and tensin homologue deleted in chromosome 10, deleted in malignant brain tumors-1, and cyclin-dependent kinase inhibitor 2A loci and amplifications at the cyclin-dependent kinase 4 locus; the frequency of genetic lesions (gain or loss) at 16 different selected loci (including oncogenes, tumor-suppressor genes, and proliferation markers) mapping on 13 different chromosomes; and the possible existence of a statistical association between any pair of molecular markers studied, to subdivide the glioblastoma entity molecularly Comparative genomic hybridization showed that the most frequent region of gain was chromosome 7p, whereas the most frequent losses occurred on chromosomes 10q and 13q The only statistically significant association was found for 7p gain and 10q loss

Ana Palacio

Papers

Chromosomal abnormalities in human glioblastomas: gain in chromosome 7p correlating with loss in chromosome 10q