Prevalence of Copy-number neutral LOH in glioblastomas revealed by analysis of laser-microdissected tissues
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE10922 | GEO | 2009/03/01
SECONDARY ACCESSION(S): PRJNA107227
REPOSITORIES: GEO
Similar Datasets
Project description:We have employed a laser capture microdissection technique and single nucleotide polymorphism arrays to characterize genomic alterations associated with the development of glioblastomas. Combined analysis of LOH and copy number revealed that more than half of the identified 254 LOH loci showed no copy number alteration, indicating the presence of copy-number neutral LOH Keywords: DNA copy number, Loss of heterozygosity Affymetrix 50K SNP mapping arrays were used to profile 14 primary glioblastomas (GBMs) with matched blood DNA samples. Loss of heterozygosity (LOH) and copy number abnormality (CNA) profiles were derived from each tumour-blood pair.
2009-03-01 | E-GEOD-10922 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the following subset Series: GSE22544: Integration of transcript expression, copy number and LOH analysis of infiltrating ductal carcinoma of the breast: expression analysis GSE22839: Integration of transcript expression, copy number and LOH analysis of infiltrating ductal carcinoma of the breast: copy number analysis Refer to individual Series
2010-07-16 | E-GEOD-22840 | biostudies-arrayexpress
Project description:Screening for gene copy-number alterations (CNAs) has improved by applying genome-wide microarrays, where SNP arrays also allow analysis of loss of heterozygozity (LOH). We here analyzed 10 chronic lymphocytic leukemia (CLL) samples using four different high-resolution platforms: BAC arrays (32K), oligonucleotide arrays (185K, Agilent), and two SNP arrays (250K, Affymetrix and 317K, Illumina). Cross-platform comparison revealed 29 concordantly detected CNAs, including known recurrent alterations, which confirmed that all platforms are powerful tools when screening for large aberrations. However, detection of 32 additional regions present in 2-3 platforms illustrated a discrepancy in detection of small CNAs, which often involved reported copy-number variations. LOH analysis revealed concordance of mainly large regions, but showed numerous, small nonoverlapping regions and LOH escaping detection. Evaluation of baseline variation and copy-number ratio response showed the best performance for the Agilent platform and confirmed the robustness of BAC arrays. Accordingly, these platforms demonstrated a higher degree of platform-specific CNAs. The SNP arrays displayed higher technical variation, although this was compensated by high density of elements. Affymetrix detected a higher degree of CNAs compared to Illumina, while the latter showed a lower noise level and higher detection rate in the LOH analysis. Large-scale studies of genomic aberrations are now feasible, but new tools for LOH analysis are requested.
2008-12-10 | GSE13557 | GEO
Project description:Structural changes of chromosomes play important roles in the carcinogenesis of colorectal carcinoma (CRC). Here, by using SNP-typing arrays, we have tried to screen for recurrent chromosome copy number changes and loss-of-heterozygosity in the genome of colorectal carcinoma. Genomic DNA was isolated from tumor and paired normal tissues of CRC (n=94), and was hybridized to Affymetrix Mapping 50K Xba 240 arrays. Chromosome copy number and LOH likelihood score was inferred at every SNP locus with CNAG2.0 software (http://www.genome.umin.jp). Keywords: Comparative genomic hybridization
2008-08-21 | GSE11417 | GEO
Project description:Introduction: A major challenge in the interpretation of genomic profiling data generated from breast cancer samples is the identification of driver genes as distinct from bystander genes which do not impact tumorigenesis. One way to assess the relative importance of alterations in the transcriptome profile is to combine complementary analyses that assess changes in the copy number alterations (CNAs). This integrated analysis permits the identification of genes with altered expression that map within specific chromosomal regions that demonstrate copy number alterations, providing a mechanistic approach to identify the 'driver genes’. Methods: We have performed whole genome analysis of CNAs using the Affymetrix 250K Mapping array on 22 infiltrating ductal carcinoma samples (IDCs). Analysis of transcript expression alterations was performed using the Affymetrix U133 Plus2.0 array on 16 IDC samples. Twelve IDC samples were analyzed using both platforms and the data integrated. We also incorporated data from LOH analysis to identify genes showing loss of expression in LOH regions. Results: Copy number analysis results demarcated smaller boundaries for many previously reported CNAs, and in some cases, the CNAs were defined as more than a single contiguous event. Additionally, we were able to assign driver genes to these commonly reported regions using a rigorous methodology. For example, RAB25 showed a large increased expression in the tumors and mapped to the commonly reported amplification at 1q22. We also identified 5 genes in the 8q24 amplicon and TSEN4 in the 17q25 amplified region. LOH analysis confirmed some previously reported regions, and integration with copy number data determined that the detected LOH were copy neutral events. Finally, we have identified several RXR pathways that demonstrated down-regulation in IDC whose members may represent further targets of therapeutic intervention. Conclusion: We have demonstrated the utility of the application of integrated analysis using high-resolution CGH and whole genome transcript analysis for detecting driver genes in IDC. The high resolution platform allowed a refined demarcation of CNAs, and gene expression profiling provided a mechanism to detect genes directly impacted by the CNA. This is the first report of LOH in IDC using a high resolution platform.
2010-06-24 | GSE22544 | GEO
Project description:Structural changes of chromosomes play important roles in the carcinogenesis of colorectal carcinoma (CRC). Here, by using SNP-typing arrays, we have tried to screen for recurrent chromosome copy number changes and loss-of-heterozygosity in the genome of colorectal carcinoma. Genomic DNA was isolated from tumor and paired normal tissues of CRC (n=94), and was hybridized to Affymetrix Mapping 50K Xba 240 arrays. Chromosome copy number and LOH likelihood score was inferred at every SNP locus with CNAG2.0 software (http://www.genome.umin.jp). Experiment Overall Design: Tumor samples and paired normal tissues (n=94 for each) were hybridized to the microarrays. Signal intensity data as well as genotype data were compared between a pair of tumor and normal samples with CNAG2.0. The resultant copy number and LOH likelihood score for each sample are thus calculated from two datasets (tumor and normal).
2008-10-26 | E-GEOD-11417 | biostudies-arrayexpress
Project description:Introduction: A major challenge in the interpretation of genomic profiling data generated from breast cancer samples is the identification of driver genes as distinct from bystander genes which do not impact tumorigenesis. One way to assess the relative importance of alterations in the transcriptome profile is to combine complementary analyses that assess changes in the copy number alterations (CNAs). This integrated analysis permits the identification of genes with altered expression that map within specific chromosomal regions that demonstrate copy number alterations, providing a mechanistic approach to identify the 'driver genes’. Methods: We have performed whole genome analysis of CNAs using the Affymetrix 250K Mapping array on 22 infiltrating ductal carcinoma samples (IDCs). Analysis of transcript expression alterations was performed using the Affymetrix U133 Plus2.0 array on 16 IDC samples. Twelve IDC samples were analyzed using both platforms and the data integrated. We also incorporated data from LOH analysis to identify genes showing loss of expression in LOH regions. Results: Copy number analysis results demarcated smaller boundaries for many previously reported CNAs, and in some cases, the CNAs were defined as more than a single contiguous event. Additionally, we were able to assign driver genes to these commonly reported regions using a rigorous methodology. For example, RAB25 showed a large increased expression in the tumors and mapped to the commonly reported amplification at 1q22. We also identified 5 genes in the 8q24 amplicon and TSEN4 in the 17q25 amplified region. LOH analysis confirmed some previously reported regions, and integration with copy number data determined that the detected LOH were copy neutral events. Finally, we have identified several RXR pathways that demonstrated down-regulation in IDC whose members may represent further targets of therapeutic intervention. Conclusion: We have demonstrated the utility of the application of integrated analysis using high-resolution CGH and whole genome transcript analysis for detecting driver genes in IDC. The high resolution platform allowed a refined demarcation of CNAs, and gene expression profiling provided a mechanism to detect genes directly impacted by the CNA. This is the first report of LOH in IDC using a high resolution platform.
2010-07-17 | GSE22839 | GEO
Project description:Screening for gene copy-number alterations (CNAs) has improved by applying genome-wide microarrays, where SNP arrays also allow analysis of loss of heterozygozity (LOH). We here analyzed 10 chronic lymphocytic leukemia (CLL) samples using four different high-resolution platforms: BAC arrays (32K), oligonucleotide arrays (185K, Agilent), and two SNP arrays (250K, Affymetrix and 317K, Illumina). Cross-platform comparison revealed 29 concordantly detected CNAs, including known recurrent alterations, which confirmed that all platforms are powerful tools when screening for large aberrations. However, detection of 32 additional regions present in 2-3 platforms illustrated a discrepancy in detection of small CNAs, which often involved reported copy-number variations. LOH analysis revealed concordance of mainly large regions, but showed numerous, small nonoverlapping regions and LOH escaping detection. Evaluation of baseline variation and copy-number ratio response showed the best performance for the Agilent platform and confirmed the robustness of BAC arrays. Accordingly, these platforms demonstrated a higher degree of platform-specific CNAs. The SNP arrays displayed higher technical variation, although this was compensated by high density of elements. Affymetrix detected a higher degree of CNAs compared to Illumina, while the latter showed a lower noise level and higher detection rate in the LOH analysis. Large-scale studies of genomic aberrations are now feasible, but new tools for LOH analysis are requested. 10 chronic lymphocytic leukemia (CLL) samples was analyzed using four different high-resolution platforms: 32K BAC arrays, 185K Agilent oligonucleotide arrays, 250K Affymetrix SNP arrays and 317K Illumina SNP arrays.
2008-12-10 | E-GEOD-13557 | biostudies-arrayexpress
Project description:High-resolution microarray-based whole genome genotyping (WGG) techniques based on SNP analysis have successfully been applied in cancer genomics to study gene copy number alterations and allele-specific aberrations such as loss-of-heterozygosity (LOH). Problems in data interpretation arise when WGG is applied on tumor tissue specimens, in which normal cell components and tumor subpopulations frequently exist. Such heterogeneity may lead to reduced detection of cancer cell specific genomic alterations. To circumvent problems with sample heterogeneity, we propose using a segmentation strategy derived from DNA copy number analysis for detection of LOH and allelic imbalance. We generated an experimental dilution series of a tumor cell line mixed with its paired normal cell line and simulated data for such dilutions to test the strategy. We also used data sets generated on both Affymetrix and Illumina WGG platforms, including paired tumor-normal samples and tumors previously characterized by FISH. We tested the segmentation strategy against several reported algorithms. We demonstrate high sensitivity and specificity of the segmentation strategy for detecting both minute and gross allelic imbalances originating from DNA copy number gain, loss, and neutral events in tumor specimens. For example, hemizygous copy number loss can be detected in samples containing only 20-25% tumor cells. Furthermore, the strategy can identify cell subpopulation specific events and accurately estimate the fraction of cells affected by an allelic imbalance. Thus, the segmentation strategy extends the usefulness of WGG platforms for investigation of allelic imbalances in heterogeneous tumor genomes.
2008-09-18 | GSE11976 | GEO
Project description:Introduction: A major challenge in the interpretation of genomic profiling data generated from breast cancer samples is the identification of driver genes as distinct from bystander genes which do not impact tumorigenesis. One way to assess the relative importance of alterations in the transcriptome profile is to combine complementary analyses that assess changes in the copy number alterations (CNAs). This integrated analysis permits the identification of genes with altered expression that map within specific chromosomal regions that demonstrate copy number alterations, providing a mechanistic approach to identify the 'driver genesâ. Methods: We have performed whole genome analysis of CNAs using the Affymetrix 250K Mapping array on 22 infiltrating ductal carcinoma samples (IDCs). Analysis of transcript expression alterations was performed using the Affymetrix U133 Plus2.0 array on 16 IDC samples. Twelve IDC samples were analyzed using both platforms and the data integrated. We also incorporated data from LOH analysis to identify genes showing loss of expression in LOH regions. Results: Copy number analysis results demarcated smaller boundaries for many previously reported CNAs, and in some cases, the CNAs were defined as more than a single contiguous event. Additionally, we were able to assign driver genes to these commonly reported regions using a rigorous methodology. For example, RAB25 showed a large increased expression in the tumors and mapped to the commonly reported amplification at 1q22. We also identified 5 genes in the 8q24 amplicon and TSEN4 in the 17q25 amplified region. LOH analysis confirmed some previously reported regions, and integration with copy number data determined that the detected LOH were copy neutral events. Finally, we have identified several RXR pathways that demonstrated down-regulation in IDC whose members may represent further targets of therapeutic intervention. Conclusion: We have demonstrated the utility of the application of integrated analysis using high-resolution CGH and whole genome transcript analysis for detecting driver genes in IDC. The high resolution platform allowed a refined demarcation of CNAs, and gene expression profiling provided a mechanism to detect genes directly impacted by the CNA. This is the first report of LOH in IDC using a high resolution platform. 16 IDC samples analyzed with the U133 Plus 2.0 array compared to 4 normal control samples.
2010-07-29 | E-GEOD-22544 | biostudies-arrayexpress