Array-based gene expression, CGH and tissue data define a 12q24 gain in neuroblastic tumors with prognostic implication
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE18144 | GEO | 2010/05/05
SECONDARY ACCESSION(S): PRJNA119473
REPOSITORIES: GEO
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Project description:BACKGROUND: Neuroblastoma has successfully served as a model system for the identification of neuroectoderm-derived oncogenes. However, in spite of various efforts, only a few clinically useful prognostic markers have been found. Here, we present a framework, which integrates DNA, RNA and tissue data to identify and prioritize genetic events that represent clinically relevant new therapeutic targets and prognostic biomarkers for neuroblastoma. METHODS: A single-gene resolution aCGH profiling was integrated with microarray-based gene expression profiling data to distinguish genetic copy number alterations that were strongly associated with transcriptional changes in two neuroblastoma cell lines. FISH analysis using a hotspot tumor tissue microarray of 37 paraffin-embedded neuroblastoma samples and in silico data mining for gene expression information obtained from previously published studies including up to 445 healthy nervous system samples and 123 neuroblastoma samples were used to evaluate the clinical significance and transcriptional consequences of the detected alterations and to identify subsequently activated gene(s). RESULTS: In addition to the anticipated high-level amplification and subsequent overexpression of MYCN, MEIS1, CDK4 and MDM2 oncogenes, the aCGH analysis revealed numerous other genetic alterations, including microamplifications at 2p and 12q24.11. Most interestingly, we identified and investigated the clinical relevance of a previously poorly characterized amplicon at 12q24.31. FISH analysis showed low-level gain of 12q24.31 in 14 of 33 (42%) neuroblastomas. Patients with the low-level gain had an intermediate prognosis in comparison to patients with MYCN amplification (poor prognosis) and to those with no MYCN amplification or 12q24.31 gain (good prognosis) (P = 0.001). Using the in silico data mining approach, we identified elevated expression of five genes located at the 12q24.31 amplicon in neuroblastoma (DIABLO, ZCCHC8, RSRC2, KNTC1 and MPHOSPH9). Among these, DIABLO showed the strongest activation suggesting a putative role in neuroblastoma progression. CONCLUSIONS: The presented systematic and rapid framework, which integrates aCGH, gene expression and tissue data to obtain novel targets and biomarkers for cancer, identified a low-level gain of the 12q24.31 as a potential new biomarker for neuroblastoma progression. Furthermore, results of in silico data mining suggest a new neuroblastoma target gene, DIABLO, within this region, whose functional and therapeutic role remains to be elucidated in follow-up studies.
| S-EPMC2873396 | biostudies-literature
Project description:This SuperSeries is composed of the following subset Series: GSE18139: Array-based gene expression in neuroblastic tumors GSE18143: aCGH of neuroblastic tumors Refer to individual Series
2010-05-05 | E-GEOD-18144 | biostudies-arrayexpress
Project description:Title: Array-based gene expression, CGH and tissue data define a 12q24 gain in neuroblastic tumors with prognostic implication. Background: Neuroblastoma has successfully served as a model system for the identification of neuroectoderm-derived oncogenes. However, in spite of various efforts, only a few clinically useful prognostic markers have been found. Here, we present a framework, which integrates DNA, RNA and tissue data to identify and prioritize genetic events that represent clinically relevant new therapeutic targets and prognostic biomarkers for neuroblastoma. Methods: A single-gene resolution aCGH profiling was integrated with microarray-based gene expression profiling data to distinguish genetic copy number alterations that were strongly associated with transcriptional changes in two neuroblastoma cell lines. FISH analysis using a hotspot tumour tissue microarray of 37 paraffin-embedded neuroblastoma samples and in silico data mining for gene expression information obtained from previously published studies including up to 445 healthy nervous system samples and 123 neuroblastoma samples were used to evaluate the clinical significance and transcriptional consequences of the detected alterations and to identify subsequently activated gene(s). Results: In addition to the anticipated high-level amplification and subsequent overexpression of MYCN, MEIS1, CDK4 and MDM2 oncogenes, the aCGH analysis revealed numerous other genetic alterations, including microamplifications at 2p and 12q24.11. Most interestingly, we identified and investigated the clinical relevance of a previously poorly characterized amplicon at 12q24.31. FISH analysis showed low-level gain of 12q24.31 in 14 of 33 (42%) neuroblastomas. Patients with the low-level gain had an intermediate prognosis in comparison to patients with MYCN amplification (poor prognosis) and to those with no MYCN amplification or 12q24.31 gain (good prognosis) (P = 0.001). Using the in silico data mining approach, we identified elevated expression of five genes located at the 12q24.31 amplicon in neuroblastoma (DIABLO, ZCCHC8, RSRC2, KNTC1 and MPHOSPH9). Among these, DIABLO showed the strongest activation suggesting a putative role in neuroblastoma progression. Conclusions: The presented systematic and rapid framework, which integrates aCGH, gene expression and tissue data to obtain novel targets and biomarkers for cancer, identified a low-level gain of the 12q24.31 as a potential new biomarker for neuroblastoma progression. Furthermore, results of in silico data mining suggest a new neuroblastoma target gene, DIABLO, within this region, whose functional and therapeutic role remains to be elucidated in follow-up studies.
2010-05-05 | GSE18139 | GEO
Project description:Title: Array-based gene expression, CGH and tissue data define a 12q24 gain in neuroblastic tumors with prognostic implication. Background: Neuroblastoma has successfully served as a model system for the identification of neuroectoderm-derived oncogenes. However, in spite of various efforts, only a few clinically useful prognostic markers have been found. Here, we present a framework, which integrates DNA, RNA and tissue data to identify and prioritize genetic events that represent clinically relevant new therapeutic targets and prognostic biomarkers for neuroblastoma. Methods: A single-gene resolution aCGH profiling was integrated with microarray-based gene expression profiling data to distinguish genetic copy number alterations that were strongly associated with transcriptional changes in two neuroblastoma cell lines. FISH analysis using a hotspot tumour tissue microarray of 37 paraffin-embedded neuroblastoma samples and in silico data mining for gene expression information obtained from previously published studies including up to 445 healthy nervous system samples and 123 neuroblastoma samples were used to evaluate the clinical significance and transcriptional consequences of the detected alterations and to identify subsequently activated gene(s). Results: In addition to the anticipated high-level amplification and subsequent overexpression of MYCN, MEIS1, CDK4 and MDM2 oncogenes, the aCGH analysis revealed numerous other genetic alterations, including microamplifications at 2p and 12q24.11. Most interestingly, we identified and investigated the clinical relevance of a previously poorly characterized amplicon at 12q24.31. FISH analysis showed low-level gain of 12q24.31 in 14 of 33 (42%) neuroblastomas. Patients with the low-level gain had an intermediate prognosis in comparison to patients with MYCN amplification (poor prognosis) and to those with no MYCN amplification or 12q24.31 gain (good prognosis) (P = 0.001). Using the in silico data mining approach, we identified elevated expression of five genes located at the 12q24.31 amplicon in neuroblastoma (DIABLO, ZCCHC8, RSRC2, KNTC1 and MPHOSPH9). Among these, DIABLO showed the strongest activation suggesting a putative role in neuroblastoma progression. Conclusions: The presented systematic and rapid framework, which integrates aCGH, gene expression and tissue data to obtain novel targets and biomarkers for cancer, identified a low-level gain of the 12q24.31 as a potential new biomarker for neuroblastoma progression. Furthermore, results of in silico data mining suggest a new neuroblastoma target gene, DIABLO, within this region, whose functional and therapeutic role remains to be elucidated in follow-up studies. High-resolution aCGH was utilized to identify novel genetic alterations in two neuroblastoma cell lines, NGP and IMR-32. Through the integration of gene copy number and gene expression data, the impact of copy number changes on expression levels was determined. Fluorescence in situ hybridization (FISH) on a tissue microarray (TMA) format was used to assess the clinical significance of the identified copy number increase at 12q24.31 in neuroblastoma patients. Finally, we used in silico data mining of publicly available transcriptomics data, to evaluate the transcriptional consequences of the detected 12q24.31 alteration and to identify subsequently activated gene(s). Here, gene expression analysis of the NGP and IMR-32 cell lines was performed. A pooled sample of 16 cancer cell lines was used as reference.
2010-05-27 | E-GEOD-18139 | biostudies-arrayexpress
Project description:Array-based comparative genomic hybridization is a high resolution method for measuring chromosomal copy number changes. Here we present a validated protocol using in-house spotted oligonucleotide libraries for array comparative genomic hybridization (CGH). This oligo array CGH platform yields reproducible results and is capable of detecting single copy gains, multi-copy amplifications as well as homozygous and heterozygous deletions as small as 100 kb with high resolution. A human oligonucleotide library was printed on amine binding slides. Arrays were hybridized using a hybstation and analysed using BlueFuse feature extraction software, with >95% of spots passing quality control. The protocol allows as little as 300 ng of input DNA and a 90% reduction of Cot-1 DNA without compromising quality. High quality results have also been obtained with DNA from archival tissue. Finally, in addition to human oligo arrays, we have applied the protocol successfully to mouse oligo arrays. We believe that this oligo-based platform using 'off-the-shelf' oligo libraries provides an easy accessible alternative to BAC arrays for CGH, which is cost-effective, available at high resolution and easily implemented for any sequenced organism without compromising the quality of the results.
| S-EPMC1316119 | biostudies-literature
Project description:BACKGROUND: Malignant peripheral nerve sheath tumors (MPNSTs) are rare and highly aggressive soft tissue tumors showing complex chromosomal aberrations. In order to identify recurrent chromosomal regions of gain and loss, and thereby novel gene targets of potential importance for MPNST development and/or progression, we have analyzed DNA copy number changes in seven high-grade MPNSTs using microarray-based comparative genomic hybridization (array CGH). RESULTS: Considerable more gains than losses were observed, and the most frequent minimal recurrent regions of gain included 1q24.1-q24.2, 1q24.3-q25.1, 8p23.1-p12, 9q34.11-q34.13 and 17q23.2-q25.3, all gained in five of seven samples. The 17q23.2-q25.3 region was gained in all five patients with poor outcome and not in the two patients with disease-free survival. cDNA microarray analysis and quantitative real-time reverse transcription PCR were used to investigate expression of genes located within these regions. The gene lysyl oxidase-like 2 (LOXL2) was identified as a candidate target for the 8p23.1-p12 gain. Within 17q, the genes topoisomerase II-alpha (TOP2A), ets variant gene 4 (E1A enhancer binding protein, E1AF) (ETV4) and baculoviral IAP repeat-containing 5 (survivin) (BIRC5) showed increased expression in all samples compared to two benign tumors. Increased expression of these genes has previously been associated with poor survival in other malignancies, and for TOP2A, in MPNSTs as well. In addition, we have analyzed the expression of five micro RNAs located within the 17q23.2-q25.3 region, but none of them showed high expression levels compared to the benign tumors. CONCLUSION: Our study shows the potential of using DNA copy number changes obtained by array CGH to predict the prognosis of MPNST patients. Although no clear correlations between the expression level and patient outcome were observed, the genes TOP2A, ETV4 and BIRC5 are interesting candidate targets for the 17q gain associated with poor survival.
| S-EPMC2442610 | biostudies-literature
Project description:BackgroundArray-based Comparative Genomic Hybridization (CGH) data have been used to infer phylogenetic relationships. However, the reliability of array CGH analysis to determine evolutionary relationships has not been well established. In most CGH work, all species and strains are compared to a single reference species, whose genome was used to design the array. In the accompanying work, we critically evaluated CGH-based phylogeny using simulated competitive hybridization data. This work showed that a limited number of conditions, principally the tree topology and placement of the reference taxon in the tree, had a strong effect on the ability to recover the correct tree topology. Here, we add to our simulation study by testing the use of CGH as a phylogenetic tool with experimental CGH data from competitive hybridizations between N. crassa and other Neurospora species. In the discussion, we add to our empirical study of Neurospora by reanalyzing of data from a previous CGH phylogenetic analysis of the yeast sensu stricto complex.ResultsArray ratio data for Neurospora and related species were normalized with loess, robust spline, and linear ratio based methods, and then used to construct Neighbor-Joining and parsimony trees. These trees were compared to published phylogenetic analyses for Neurospora based on multilocus sequence analysis (MLSA). For the Neurospora dataset, the best combination of methods resulted in recovery of the MLSA tree topology less than half the time. Our reanalysis of a yeast dataset found that trees identical to established phylogeny were recovered only by pruning taxa - including the reference taxon - from the analysis.ConclusionOur results indicate that CGH data can be problematic for phylogenetic analysis. Success fluctuates based on the methods utilized to construct the tree and the taxa included. Selective pruning of the taxa improves the results - an impractical approach for normal phylogenetic analysis. From the more successful methods we make suggestions on the normalization and post-normalization methods that work best in estimating genetic distance between taxa.
| S-EPMC3206521 | biostudies-literature
Project description:The goal of this study was to characterize and classify pulmonary neuroendocrine tumors based on Array Comparative Genomic Hybridization (aCGH). Using aCGH, we performed karyotype analysis of 33 small cell lung cancer (SCLC) tumors, 13 SCLC cell lines, 19 bronchial carcinoids, and 9 gastrointestinal (GI) carcinoids. In contrast to the relatively stable karyotypes of carcinoid tumors, the karyotypes of SCLC tumors and cell lines were highly aberrant. High copy number (CN) gains were detected in SCLC tumors and cell lines in cytogenetic bands encoding JAK2, FGFR1, and MYC family members. In some of those samples, the CN of these genes exceeded 100, suggesting that they could represent driver alterations and potential drug targets in subgroups of SCLC patients. Recurrent CN alterations of a total of 203 genes, including the RB1 gene, and 59 microRNAs, most of which locate in the DLK1-DIO3 domain, were observed in SCLC tumors, bronchial carcinoids and carcinoids of GI origin; in contrast, CN alterations of the TP53 gene and the MYC family members were observed more frequently in SCLC. These findings suggest the existence of partially shared tumor-specific CN alterations in these tumors. Furthermore, we demonstrated that the aCGH profile of SCLC cell lines highly resemble that of clinical SCLC specimens. Finally, by analyzing potential drug targets, we provide a genomics based rationale for targeting the AKT-mTOR and apoptosis pathways in SCLC.
2010-04-22 | GSE21468 | GEO
Project description:BackgroundArray-based comparative genomic hybridization (array-CGH) is a recently developed technique for analyzing changes in DNA copy number. As in all microarray analyses, normalization is required to correct for experimental artifacts while preserving the true biological signal. We investigated various sources of systematic variation in array-CGH data and identified two distinct types of spatial effect of no biological relevance as the predominant experimental artifacts: continuous spatial gradients and local spatial bias. Local spatial bias affects a large proportion of arrays, and has not previously been considered in array-CGH experiments.ResultsWe show that existing normalization techniques do not correct these spatial effects properly. We therefore developed an automatic method for the spatial normalization of array-CGH data. This method makes it possible to delineate and to eliminate and/or correct areas affected by spatial bias. It is based on the combination of a spatial segmentation algorithm called NEM (Neighborhood Expectation Maximization) and spatial trend estimation. We defined quality criteria for array-CGH data, demonstrating significant improvements in data quality with our method for three data sets coming from two different platforms (198, 175 and 26 BAC-arrays).ConclusionWe have designed an automatic algorithm for the spatial normalization of BAC CGH-array data, preventing the misinterpretation of experimental artifacts as biologically relevant outliers in the genomic profile. This algorithm is implemented in the R package MANOR (Micro-Array NORmalization), which is described at http://bioinfo.curie.fr/projects/manor and available from the Bioconductor site http://www.bioconductor.org. It can also be tested on the CAPweb bioinformatics platform at http://bioinfo.curie.fr/CAPweb.
| S-EPMC1523216 | biostudies-literature
Project description:BackgroundThe 15q11-q13 region contains many low copy repeats and is well known for its genomic instability. Several syndromes are associated with genomic imbalance or copy-number-neutral uniparental disomy. We report on two patients: Patient 1 is a boy with developmental delay and autism; and Patient 2 is a girl with developmental delay, hypotonia and dysmorphism. We performed analyses to delineate their dosage in the 15q region, determine whether the patients' dosage correlates with phenotypic severity, and whether genes in the amplified regions are significantly associated with identified functional networks.ResultsFor the proximal region of 15q, molecular cytogenetic analysis with Agilent oligonucleotide array showed a copy number of 3 for Patient 1 and a copy number of 4 for Patient 2. Fluorescent in situ hybridization analysis of Patient 2 showed two different populations of cells with different marker chromosomes. Methylation analysis of the amplified region showed that the extra copies of small nuclear ribonucleoprotein polypeptide N gene were of maternal origin. Phenotypic severity did not correlate with the size and dosage of 15q, or whether the amplification is interstitial or in the form of a supernumerary marker. Pathway analysis showed that in Patient 2, the main functional networks that are affected by the genes from the duplicated/triplicated regions are developmental disorder, neurological disease and hereditary disease.ConclusionsThe 15q11-q13 gains that were found in both patients could explain their phenotypic presentations. This report expands the cohort of patients for which 15q11-q13 duplications are molecularly characterized.
| S-EPMC4067100 | biostudies-literature