Unknown,Transcriptomics,Genomics,Proteomics

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CytoScanHD array Data for Colerectal Tumor and Normal Samples

ABSTRACT: Genomic abnormalities leading to colorectal cancer (CRC) include somatic events causing copy number aberrations (CNAs) as well as copy neutral manifestations such as loss of heterozygosity (LOH) and uniparental disomy (UPD). We studied the causal effect of these events by analyzing high resolution cytogenetic microarray data of 15 tumor-normal paired samples. We detected 144 genes affected by CNAs. A subset of 91 genes are known to be CRC related yet high GISTIC scores indicate 24 genes on chromosomes 7, 8, 18 and 20 to be strongly relevant. Combining GISTIC ranking with functional analyses and degree of loss/gain we identify three genes in regions of significant loss (ATP8B1, NARS, and ATP5A1) and eight in regions of gain (CTCFL, SPO11, ZNF217, PLEKHA8, HOXA3, GPNMB, IGF2BP3 and PCAT1) as novel in their association with CRC. Pathway analysis indicates TGF-β signaling pathway to be affected by the cytogenetic events causing CRC as evidenced by the action of genes impacted by CNAs on SMAD family of proteins. Finally, LOH and UPD collectively affected nine cancer related genes. Transcription factor binding sites on regions of >35% copy number loss/gain influenced 16 CRC genes. Our analysis shows patient specific CRC manifestations at the genomic level and that these different events affect individual CRC patients differently. Copy number analysis of Affymetrix CytoScanHD arrays was performed for 15 Tumors and 15 Adjacent Normals from Colorectal Tissue was used as reference for the study.

ORGANISM(S): Homo sapiens

SUBMITTER: Sathish Periyasamy

PROVIDER: E-GEOD-47204 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:We analysed, by last-generation high-resolution SNP arrays, Normal Karyotype (NK)-AML patients at diagnosis (Dx) and remission (R) phases, in order to determine the number of tumor-associated copy number abnormalities (CNAs) and copy neutral-loss of heterozygosity (CN-LOH) regions per patient and to identify possible recurring genomic abnormalities. The number of tumor-associated CNAs was detemined after comparison of 11 matched Dx/R samples using stringent conditions able to reduce the number of false positive CNAs. 8 additional unmatched Dx samples were included in the analysis of recurring CNAs and for detection of broad CN-LOH segments. With the exception of a single outlier case, a low number of CNAs per patient was detected (median value of 1 somatic loss or gain per patient). However, a high prevalence of CNAs (60-70% of the patients showed at least 1 tumor-associated gain or loss) and few recurring CNAs were observed, thus providing new hints towards identification of cooperating mutations. An extensive search of all CN-LOH regions > 1 Mb revealed only 3 broad regions (terminal 12Mb of 22q, terminal 27Mb of 1p and the whole chromosome 21) in three patients out of 19 (16%). CN-LOH of the whole chromosome 21 was responsible for homozygosity of a missense mutation (R80C) of RUNX1/AML1. Our study suggests that a relative submicroscopic copy number stability NK-AML genomes is associated with low recurrence of specific CNAs and CN-LOH in NK-AML patient population. Nineteen AML bone marrow samples were collected at the time of diagnosis (>90% blasts), defined as karyotypically-normal on the basis of standard metaphase cytogenetics (MC) and analysed by the Affymetrix SNP 6.0 arrays. In 11 of such cases (matched Dx) we obtained a bone marrow sample at the remission phase (matched R) of comparable high quality as evaluated by Contrast QC and MAPD values. In 8 cases (unmatched Dx) the corresponding R sample was not available or was not of comparable quality. As a reference set the publicly available data from 270 HapMap individuals were used.

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.

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CytoScanHD array Data for Colerectal Tumor and Normal Samples

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