NFKBIA deletion in glioblastomas.

BACKGROUND: Amplification and activating mutations of the epidermal growth factor receptor (EGFR) oncogene are molecular hallmarks of glioblastomas. We hypothesized that deletion of NFKBIA (encoding nuclear factor of κ-light polypeptide gene enhancer in B-cells inhibitor-α), an inhibitor of the EGFR-signaling pathway, promotes tumorigenesis in glioblastomas that do not have alterations of EGFR. METHODS: We analyzed 790 human glioblastomas for deletions, mutations, or expression of NFKBIA and EGFR. We studied the tumor-suppressor activity of NFKBIA in tumor-cell culture. We compared the molecular results with the outcome of glioblastoma in 570 affected persons. RESULTS: NFKBIA is often deleted but not mutated in glioblastomas; most deletions occur in nonclassical subtypes of the disease. Deletion of NFKBIA and amplification of EGFR show a pattern of mutual exclusivity. Restoration of the expression of NFKBIA attenuated the malignant phenotype and increased the vulnerability to chemotherapy of cells cultured from tumors with NFKBIA deletion; it also reduced the viability of cells with EGFR amplification but not of cells with normal gene dosages of both NFKBIA and EGFR. Deletion and low expression of NFKBIA were associated with unfavorable outcomes. Patients who had tumors with NFKBIA deletion had outcomes that were similar to those in patients with tumors harboring EGFR amplification. These outcomes were poor as compared with the outcomes in patients with tumors that had normal gene dosages of NFKBIA and EGFR. A two-gene model that was based on expression of NFKBIA and O(6)-methylguanine DNA methyltransferase was strongly associated with the clinical course of the disease. CONCLUSIONS: Deletion of NFKBIA has an effect that is similar to the effect of EGFR amplification in the pathogenesis of glioblastoma and is associated with comparatively short survival.

A network model of a cooperative genetic landscape in brain tumors.

CONTEXT: Gliomas, particularly glioblastomas, are among the deadliest of human tumors. Gliomas emerge through the accumulation of recurrent chromosomal alterations, some of which target yet-to-be-discovered cancer genes. A persistent question concerns the biological basis for the coselection of these alterations during gliomagenesis. OBJECTIVES: To describe a network model of a cooperative genetic landscape in gliomas and to evaluate its clinical relevance. DESIGN, SETTING, AND PATIENTS: Multidimensional genomic profiles and clinical profiles of 501 patients with gliomas (45 tumors in an initial discovery set collected between 2001 and 2004 and 456 tumors in validation sets made public between 2006 and 2008) from multiple academic centers in the United States and The Cancer Genome Atlas Pilot Project (TCGA). MAIN OUTCOME MEASURES: Identification of genes with coincident genetic alterations, correlated gene dosage and gene expression, and multiple functional interactions; association between those genes and patient survival. RESULTS: Gliomas select for a nonrandom genetic landscape-a consistent pattern of chromosomal alterations-that involves altered regions ("territories") on chromosomes 1p, 7, 8q, 9p, 10, 12q, 13q, 19q, 20, and 22q (false-discovery rate-corrected P<.05). A network model shows that these territories harbor genes with putative synergistic, tumor-promoting relationships. The coalteration of the most interactive of these genes in glioblastoma is associated with unfavorable patient survival. A multigene risk scoring model based on 7 landscape genes (POLD2, CYCS, MYC, AKR1C3, YME1L1, ANXA7, and PDCD4) is associated with the duration of overall survival in 189 glioblastoma samples from TCGA (global log-rank P = .02 comparing 3 survival curves for patients with 0-2, 3-4, and 5-7 dosage-altered genes). Groups of patients with 0 to 2 (low-risk group) and 5 to 7 (high-risk group) dosage-altered genes experienced 49.24 and 79.56 deaths per 100 person-years (hazard ratio [HR], 1.63; 95% confidence interval [CI], 1.10-2.40; Cox regression model P = .02), respectively. These associations with survival are validated using gene expression data in 3 independent glioma studies, comprising 76 (global log-rank P = .003; 47.89 vs 15.13 deaths per 100 person-years for high risk vs low risk; Cox model HR, 3.04; 95% CI, 1.49-6.20; P = .002) and 70 (global log-rank P = .008; 83.43 vs 16.14 deaths per 100 person-years for high risk vs low risk; HR, 3.86; 95% CI, 1.59-9.35; P = .003) high-grade gliomas and 191 glioblastomas (global log-rank P = .002; 83.23 vs 34.16 deaths per 100 person-years for high risk vs low risk; HR, 2.27; 95% CI, 1.44-3.58; P<.001). CONCLUSIONS: The alteration of multiple networking genes by recurrent chromosomal aberrations in gliomas deregulates critical signaling pathways through multiple, cooperative mechanisms. These mutations, which are likely due to nonrandom selection of a distinct genetic landscape during gliomagenesis, are associated with patient prognosis.

Monosomy of chromosome 10 associated with dysregulation of epidermal growth factor signaling in glioblastomas.

CONTEXT: Glioblastomas--uniformly fatal brain tumors--often have both monosomy of chromosome 10 and gains of the epidermal growth factor receptor (EGFR) gene locus on chromosome 7, an association for which the mechanism is poorly understood. OBJECTIVES: To assess whether coselection of EGFR gains on 7p12 and monosomy 10 in glioblastomas promotes tumorigenic epidermal growth factor (EGF) signaling through loss of the annexin A7 (ANXA7) gene on 10q21.1-q21.2 and whether ANXA7 acts as a tumor suppressor gene by regulating EGFR in glioblastomas. DESIGN, SETTING, AND PATIENTS: Multidimensional analysis of gene, coding sequence, promoter methylation, messenger RNA (mRNA) transcript, protein data for ANXA7 (and EGFR), and clinical patient data profiles of 543 high-grade gliomas from US medical centers and The Cancer Genome Atlas pilot project (made public 2006-2008; and unpublished, tumors collected 2001-2008). Functional analyses using LN229 and U87 glioblastoma cells. MAIN OUTCOME MEASURES: Associations among ANXA7 gene dosage, coding sequence, promoter methylation, mRNA transcript, and protein expression. Effect of ANXA7 haploinsufficiency on EGFR signaling and patient survival. Joint effects of loss of ANXA7 and gain of EGFR expression on tumorigenesis. RESULTS: Heterozygous ANXA7 gene deletion is associated with significant loss of ANXA7 mRNA transcript expression (P = 1 x 10(-15); linear regression) and a reduction (mean [SEM]) of 91.5% (2.3%) of ANXA7 protein expression compared with ANXA7 wild-type glioblastomas (P = .004; unpaired t test). ANXA7 loss of function stabilizes the EGFR protein (72%-744% increase in EGFR protein abundance) and augments EGFR transforming signaling in glioblastoma cells. ANXA7 haploinsufficiency doubles tumorigenic potential of glioblastoma cells, and combined ANXA7 knockdown and EGFR overexpression promotes tumorigenicity synergistically. The heterozygous loss of ANXA7 in approximately 75% of glioblastomas in the The Cancer Genome Atlas plus infrequency of ANXA7 mutation (approximately 6% of tumors) indicates its role as a haploinsufficiency gene. ANXA7 mRNA transcript expression, dichotomized at the median, associates with patient survival in 191 glioblastomas (log-rank P = .008; hazard ratio [HR], 0.667; 95% confidence interval [CI], 0.493-0.902; 46.9 vs 74.8 deaths/100 person-years for high vs low ANXA7 mRNA expression) and with a separate group of 180 high-grade gliomas (log-rank P = .00003; HR, 0.476; 95% CI, 0.333-0.680; 21.8 vs 50.0 deaths/100 person-years for high vs low ANXA7 mRNA expression). Deletion of the ANXA7 gene associates with poor patient survival in 189 glioblastomas (log-rank P = .042; HR, 0.686; 95% CI, 0.476-0.989; 54.0 vs 80.1 deaths/100 person-years for wild-type ANXA7 vs ANXA7 deletion). CONCLUSION: Haploinsufficiency of the tumor suppressor ANXA7 due to monosomy of chromosome 10 provides a clinically relevant mechanism to augment EGFR signaling in glioblastomas beyond that resulting from amplification of the EGFR gene.

Integrated high-resolution genome-wide analysis of gene dosage and gene expression in human brain tumors.

A hallmark genomic feature of human brain tumors is the presence of multiple complex structural and numerical chromosomal aberrations that result in altered gene dosages. These genetic alterations lead to widespread, genome-wide gene expression changes. Both gene expression as well as gene copy number profiles can be assessed on a large scale using microarray methodology. The integration of genetic data with gene expression data provides a particularly effective approach for cancer gene discovery. Utilizing an array of bioinformatics tools, we describe an analysis algorithm that allows for the integration of gene copy number and gene expression profiles as a first-pass means of identifying potential cancer gene targets in human (brain) tumors. This strategy combines circular binary segmentation for the identification of gene copy number alterations, and gene copy number and gene expression data integration with a modification of signal-to-noise ratio computation and random permutation testing. We have evaluated this approach and confirmed its efficacy in the human glioma genome.

Tumor necrosis factor-alpha-induced protein 3 as a putative regulator of nuclear factor-kappaB-mediated resistance to O6-alkylating agents in human glioblastomas.

PURPOSE: Pre-existing and acquired drug resistance are major obstacles to the successful treatment of glioblastomas. METHODS: We used an integrated resistance model and genomics tools to globally explore molecular factors and cellular pathways mediating resistance to O6-alkylating agents in glioblastoma cells. RESULTS: We identified a transcriptomic signature that predicts a common in vitro and in vivo resistance phenotype to these agents, a proportion of which is imprinted recurrently by gene dosage changes in the resistant glioblastoma genome. This signature was highly enriched for genes with functions in cell death, compromise, and survival. Modularity was a predominant organizational principle of the signature, with functions being carried out by groups of interacting molecules in overlapping networks. A highly significant network was built around nuclear factor-kappaB (NF-kappaB), which included the persistent alterations of various NF-kappaB pathway elements. Tumor necrosis factor-alpha-induced protein 3 (TNFAIP3) was identified as a new regulatory component of a putative cytoplasmic signaling cascade that mediates NF-kappaB activation in response to DNA damage caused by O6-alkylating agents. Expression of the corresponding zinc finger protein A20 closely mirrored the expression of the TNFAIP3 transcript, and was inversely related to NF-kappaB activation status in the resistant cells. A prediction model based on the resistance signature enabled the subclassification of an independent, validation cohort of 31 glioblastomas into two outcome groups (P = .037) and revealed TNFAIP3 as part of an optimized four-gene predictor associated significantly with patient survival (P = .022). CONCLUSION: Our results offer strong evidence for TNFAIP3 as a key regulator of the cytoplasmic signaling to activate NF-kappaB en route to O6-alkylating agent resistance in glioblastoma cells. This pathway may be an attractive target for therapeutic modulation of glioblastomas.

Functional network analysis reveals extended gliomagenesis pathway maps and three novel MYC-interacting genes in human gliomas.

Gene expression profiling has proven useful in subclassification and outcome prognostication for human glial brain tumors. The analysis of biological significance of the hundreds or thousands of alterations in gene expression found in genomic profiling remains a major challenge. Moreover, it is increasingly evident that genes do not act as individual units but collaborate in overlapping networks, the deregulation of which is a hallmark of cancer. Thus, we have here applied refined network knowledge to the analysis of key functions and pathways associated with gliomagenesis in a set of 50 human gliomas of various histogenesis, using cDNA microarrays, inferential and descriptive statistics, and dynamic mapping of gene expression data into a functional annotation database. Highest-significance networks were assembled around the myc oncogene in gliomagenesis and around the integrin signaling pathway in the glioblastoma subtype, which is paradigmatic for its strong migratory and invasive behavior. Three novel MYC-interacting genes (UBE2C, EMP1, and FBXW7) with cancer-related functions were identified as network constituents differentially expressed in gliomas, as was CD151 as a new component of a network that mediates glioblastoma cell invasion. Complementary, unsupervised relevance network analysis showed a conserved self-organization of modules of interconnected genes with functions in cell cycle regulation in human gliomas. This approach has extended existing knowledge about the organizational pattern of gene expression in human gliomas and identified potential novel targets for future therapeutic development.

High-resolution genome-wide mapping of genetic alterations in human glial brain tumors.

High-resolution genome-wide mapping of exact boundaries of chromosomal alterations should facilitate the localization and identification of genes involved in gliomagenesis and may characterize genetic subgroups of glial brain tumors. We have done such mapping using cDNA microarray-based comparative genomic hybridization technology to profile copy number alterations across 42,000 mapped human cDNA clones, in a series of 54 gliomas of varying histogenesis and tumor grade. This gene-by-gene approach permitted the precise sizing of critical amplicons and deletions and the detection of multiple new genetic aberrations. It has also revealed recurrent patterns of occurrence of distinct chromosomal aberrations as well as their interrelationships and showed that gliomas can be clustered into distinct genetic subgroups. A subset of detected alterations was shown predominantly associated with either astrocytic or oligodendrocytic tumor phenotype. Finally, five novel minimally deleted regions were identified in a subset of tumors, containing putative candidate tumor suppressor genes (TOPORS, FANCG, RAD51, TP53BP1, and BIK) that could have a role in gliomagenesis.

DNA topoisomerase IIalpha and Her-2/neu gene dosages in pediatric malignant gliomas.

Pediatric malignant non-brainstem glioma (PMNBG) is a rare tumor that accounts for only about five percent of childhood intracranial neoplasms. DNA topoisomerase IIalpha (TIIalpha) is a novel marker of cell-cycle turnover and a target of high-risk chemotherapy in PMNBG. We have shown that TIIalpha protein expression strongly correlates with event-free and overall survival in these malignancies. The molecular mechanism causing the varying TIIalpha protein expression in PMNBG remains unknown. Utilizing a combined approach of immunocytochemistry-based morphology guidance, laser-assisted microdissection and quantitative real-time PCR, we report a low-level co-amplification of the neighboring TIIalpha and Her-2/neu gene loci on chromosome 17q11-q22 in one of seventeen examined PMNBGs. Analysis of both genes by real-time PCR in the crude tumor samples without prior tissue heterogeneity reduction via laser microdissection, resulted in loss of detection of amplification of the syngeneic Her-2/neu locus. Gene dosage assessment in a microscopically distant tumor area revealed no amplification of either gene. Our results suggest that low-level amplification of the TIIalpha gene locus may be a sporadic mechanism of increased TIIalpha protein expression in PMNBG, which can coincide with low-level amplification of Her-2/neu. The observed intratumor genetic heterogeneity for TIIalpha in PMNBGs may have an impact on the relevance of TIIalpha as a biological constituent of outcome in these neoplasms.

Amplification of whole tumor genomes and gene-by-gene mapping of genomic aberrations from limited sources of fresh-frozen and paraffin-embedded DNA.

Sufficient quantity of genomic DNA can be a bottleneck in genome-wide analysis of clinical tissue samples. DNA polymerase Phi29 can be used for the random-primed amplification of whole genomes, although the amplification may introduce bias in gene dosage. We have performed a detailed investigation of this technique in archival fresh-frozen and formalin-fixed/paraffin-embedded tumor DNA by using cDNA microarray-based comparative genomic hybridization. Phi29 amplified DNA from matched pairs of fresh-frozen and formalin-fixed/paraffin-embedded tumor samples with similar efficiency. The distortion in gene dosage representation in the amplified DNA was nonrandom and reproducibly involved distinct genomic loci. Regional amplification efficiency was significantly linked to regional GC content of the template genome. The biased gene representation in amplified tumor DNA could be effectively normalized by using amplified reference DNA. Our data suggest that genome-wide gene dosage alterations in clinical tumor samples can be reliably assessed from a few hundred tumor cells. Therefore, this amplification method should lend itself to high-throughput genetic analyses of limited sources of tumor, such as fine-needle biopsies, laser-microdissected tissue, and small paraffin-embedded specimens.

Genomics-based hypothesis generation: a novel approach to unravelling drug resistance in brain tumours?

No currently available chemotherapy seems likely to substantially improve outcome in most patients with brain tumours. Several resistance-associated cellular factors, which were discovered in other cancer models, have also been identified in brain tumours. Although these mechanisms play some part in resistance in brain tumours, they are not sufficient to explain the poor clinical response to chemotherapy. There could be other brain-tumour-specific genetic profiles that are associated with tumour sensitivity to chemotherapy. There is increasing awareness that drug resistance in brain tumours is not a result of changes in single molecular pathways but is likely to involve a complex network of regulatory dynamics. Further insights into chemoresistance in brain tumours could come with comprehensive characterisation of their gene expression, as well as the genetic changes occurring in response to chemotherapy. Recent progress in high-throughput bioanalytical methods for genome-wide studies has made possible a novel research model of initial hypothesis generation followed by functional testing of the generated hypothesis.