Project description:This SuperSeries is composed of the following subset Series:; GSE13136: Identification of candidate neuroblastoma genes by combining genomic and expression microarrays: expression data; GSE13137: Identification of candidate neuroblastoma genes by combining genomic and expression microarrays: SNP data Experiment Overall Design: Refer to individual Series
Project description:Gene expression analysis was performed on 30 Neuroblastomas to identify genes whose transcription is significantly altered by recurrent chromosomal alterations. Genomic copy number losses and gains had been delineated in the tumours using FISH and SNP arrays. We have identified genes significantly altered by 7 recurrent alterations: 1p, 3p, 4p, 10q and 11q loss, 2p and 17q gain, and genes co-amplified and over-expressed as a result of MYCN amplification. Subsequently, correlation of microarray data with survival and expression within rodent neuroblastomas were used to identify genes likely to be involved in the disease progression, and identified a significant excess of differentially expressed genes which correlated with survival within the minimally altered regions on 17q and 4p Identifying genes whose expression is consistently altered by chromosomal gains or losses is an important step in defining genes of biological relevance in a wide variety of tumour types. However, additional criteria are needed to discriminate further among the large number of candidate genes identified. This is particularly true for neuroblastoma, where multiple genomic copy number changes of proven prognostic value exist. We have used Affymetrix microarrays and a combination of fluorescent in-situ hybridisation and single nucleotide polymorphism (SNP) microarrays to establish expression profiles and delineate copy number alterations in 30 primary neuroblastomas. Correlation of microarray data with patient survival and analysis of expression within rodent neuroblastoma cell lines were then used to further define genes likely to be involved in the disease process. Using this approach we identify >1000 genes within 8 recurrent genomic alterations (loss of 1p, 3p, 4p, 10q and 11q, 2p gain, 17q gain, and the MYCN amplicon) whose expression is consistently altered by copy number change. Of these, 84 correlate with patient survival, with the minimal regions of 17q gain and 4p loss being significantly enriched for such genes. Orthologues of all but one of these genes on 17q are overexpressed in rodent neuroblastoma cell lines. A significant excess of SNPs whose copy number correlates with survival is also observed on proximal 4p in stage 4 tumours, and we find that deletion of 4p is associated with improved outcome in an extended cohort of tumours. These results define the major impact of genomic copy number alterations upon transcription within neuroblastoma, and highlight genes on distal 17q and proximal 4p for downstream analyses. They also suggest that integration of discriminators such as survival and comparative gene expression with microarray data may be useful in the identification of critical genes within regions of loss or gain in many human cancers. Keywords: Disease State Analysis
Project description:Gene expression analysis was performed on 30 Neuroblastomas to identify genes whose transcription is significantly altered by recurrent chromosomal alterations. Genomic copy number losses and gains had been delineated in the tumours using FISH and SNP arrays. We have identified genes significantly altered by 7 recurrent alterations: 1p, 3p, 4p, 10q and 11q loss, 2p and 17q gain, and genes co-amplified and over-expressed as a result of MYCN amplification. Subsequently, correlation of microarray data with survival and expression within rodent neuroblastomas were used to identify genes likely to be involved in the disease progression, and identified a significant excess of differentially expressed genes which correlated with survival within the minimally altered regions on 17q and 4p; Identifying genes whose expression is consistently altered by chromosomal gains or losses is an important step in defining genes of biological relevance in a wide variety of tumour types. However, additional criteria are needed to discriminate further among the large number of candidate genes identified. This is particularly true for neuroblastoma, where multiple genomic copy number changes of proven prognostic value exist. We have used Affymetrix microarrays and a combination of fluorescent in-situ hybridisation and single nucleotide polymorphism (SNP) microarrays to establish expression profiles and delineate copy number alterations in 30 primary neuroblastomas. Correlation of microarray data with patient survival and analysis of expression within rodent neuroblastoma cell lines were then used to further define genes likely to be involved in the disease process. Using this approach we identify >1000 genes within 8 recurrent genomic alterations (loss of 1p, 3p, 4p, 10q and 11q, 2p gain, 17q gain, and the MYCN amplicon) whose expression is consistently altered by copy number change. Of these, 84 correlate with patient survival, with the minimal regions of 17q gain and 4p loss being significantly enriched for such genes. Orthologues of all but one of these genes on 17q are overexpressed in rodent neuroblastoma cell lines. A significant excess of SNPs whose copy number correlates with survival is also observed on proximal 4p in stage 4 tumours, and we find that deletion of 4p is associated with improved outcome in an extended cohort of tumours. These results define the major impact of genomic copy number alterations upon transcription within neuroblastoma, and highlight genes on distal 17q and proximal 4p for downstream analyses. They also suggest that integration of discriminators such as survival and comparative gene expression with microarray data may be useful in the identification of critical genes within regions of loss or gain in many human cancers. Experiment Overall Design: Chromosomal gains and losses were delineated in Stage 4 neuroblastomas to facilitate, in combination with expression array data, the identification of genes within regions of gain and loss whose expression is significantly altered by copy number change.
Project description:Contemporary high throughput technologies permit the rapid identification of transcription factor (TF) target genes on a genome-wide scale, yet the functional significance of TFs requires knowledge of target gene expression patterns, cooperating TFs and cis-regulatory element (CRE) structures. Here we investigated the myogenic regulatory network downstream of the Drosophila zinc finger TF Lame duck (Lmd) by combining both previously published and newly performed genomic data sets, including chromatin immunoprecipitation sequencing (ChIP-seq), genome-wide mRNA profiling, cell-specific expression patterns of putative transcriptional targets, analysis of histone mark signatures, studies of TF co-occupancy by additional mesodermal regulators, TF binding site determination using protein binding microarrays (PBMs), and machine learning of candidate CRE motif compositions. Our findings suggest that Lmd orchestrates an extensive myogenic regulatory network, a conclusion supported by the identification of Lmd-dependent genes, histone signatures of Lmd-bound genomic regions, and the relationship of these features to cell-specific gene expression patterns. The heterogeneous co-occupancy of Lmd-bound regions with additional mesodermal regulators revealed that different transcriptional inputs are used to mediate similar myogenic gene expression patterns. Machine learning further demonstrated diverse combinatorial motif patterns within tissue-specific Lmd-bound regions. PBM analysis established the complete spectrum of Lmd DNA binding specificities, and site-directed mutagenesis of Lmd and additional, newly discovered motifs in known enhancers demonstrated the critical role of these TF binding sites in supporting full enhancer activity. Collectively, these findings provide new insights into the transcriptional codes regulating muscle gene expression, and offer a generalizable approach for similar studies in other systems. Examination of Lmd occupancy to genomic DNA from sorted mesodermal cells
Project description:Background: Neuroblastoma is a childhood cancer in which many children still have poor outcomes, emphasising the need to better understand its pathogenesis. Despite recent genome-wide mutation analyses, most neuroblastomas do not contain recognisable driver mutations, suggesting that epigenetic changes could underlie many cases. Methods: To discover genes that become epigenetically deregulated during neuroblastoma tumorigenesis, we compared neuroblastomas to their neural crest precursor cells, using genome-wide DNA methylation analysis; probing CpG island promoter microarrays with methyl CpG-immunoprecipitated DNA. Results: We identified 93 genes that were significantly differently methylated between neuroblastoma cell lines and neural crest cells, of which 26 (28%) were hypermethylated and 67 (72%) were hypomethylated. Concentrating on hypermethylated genes to identify candidate tumour suppressor loci, we found the cell engulfment and adhesion factor gene MEGF10 to be epigenetically repressed by DNA hypermethylation or by H3K27/K9 methylation in neuroblastoma cell lines. MEGF10 showed significantly down-regulated expression in neuroblastoma tumour samples; furthermore patients with the lowest-expressing tumours had reduced relapse-free survival. Knock-down of MEGF10 expression in neuroblastoma cell lines promoted cell growth. Conclusion: Our results suggest that MEGF10 is a clinically relevant, epigenetically-deregulated neuroblastoma tumour suppressor.
Project description:Gene expression analysis was performed on 30 Neuroblastomas to identify genes whose transcription is significantly altered by recurrent chromosomal alterations. Genomic copy number losses and gains had been delineated in the tumours using FISH and SNP arrays. We have identified genes significantly altered by 7 recurrent alterations: 1p, 3p, 4p, 10q and 11q loss, 2p and 17q gain, and genes co-amplified and over-expressed as a result of MYCN amplification. Identifying genes whose expression is consistently altered by chromosomal gains or losses is an important step in defining genes of biological relevance in a wide variety of tumour types. However, additional criteria are needed to discriminate further among the large number of candidate genes identified. This is particularly true for neuroblastoma, where multiple genomic copy number changes of proven prognostic value exist. We have used Affymetrix microarrays and a combination of fluorescent in-situ hybridisation and single nucleotide polymorphism (SNP) microarrays to establish expression profiles and delineate copy number alterations in 30 primary neuroblastomas. Experiment Overall Design: 30 neuroblastomas were obtained from patients of all stages (10 patients - stage 1, 2, 3 or 4s disease, 20 patients - stage 4 disease). RNA samples were extracted and analysed using Affymetrix Human Genome U133 Plus 2.0 Arrays. Patient were treated according to the United Kingdom Childrenâs Cancer Study Group [UKCCSG], European Neuroblastoma Study Group and Localised Neuroblastoma European Study Group protocols.
Project description:Co-amplification at chromosomes 8p11-8p12 and 11q12-11q14 occurs often in breast tumors, suggesting possible cooperation between genes in these regions in oncogenesis. We used high resolution array comparative genomic hybridization (array CGH) to map the minimal amplified regions. The 8p and 11q amplicons are complex and consist of at least four amplicon cores at each site. Candidate genes mapping to these regions were identified by combining copy number and RNA and protein expression analyses. Funcational analysis for transformation was further carried out with candidate genes to determine candidate oncogenes.
Project description:The specific genes that influence neuroblastoma biology and are targeted by genomic alterations remain largely unknown. We quantified mRNA expression in a highly annotated series of 101 prospectively collected diagnostic neuroblastoma primary tumors and the expression profiles were determined using Affymetrix U95Av2 arrays. Comparisons between the sample groups allow the identification of genes with localized expression patterns. This study demonstrates that the genomic data can be used to subcategorize the disease into molecular subsets and the regional copy number alterations are correlated with a broad number of transcriptional alterations genome wide. This data also suggests that multiple genes from several discrete regions of the human genome co-operate to supress neuroblastoma tumorigenesis and progression. Keywords: Disease state analysis, genetic modification