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Transcription profiling of human diffusely infiltrating astrocytic tumours, grades II, III and IV

ABSTRACT: This study aims at investigating differential gene expression in human diffusely infiltrating astrocytic tumours, grades II, III and IV. A total of 63 tumours were assessed using the Affymetrix U133A GeneChip. Samples comprised in this GEO submission are identical to those in submission GSE1993 with the exception of two pilocytic astrocytoma tumours (grade I) that have not been included. The study aims not only at discovering the main expression differences between astrocytic tumours of distinct histological grades but also wishes to correlate these findings with the known histopathological and biological hallmarks of astrocytoma progression. Further, the study aims at correlating gene expression with previously obtained genomic information for several loci known to be involved in astrocytoma tumour progression. Experiment Overall Design: A total of 63 tumours were assessed using the Affymetrix U133A GeneChip.

ORGANISM(S): Homo sapiens

SUBMITTER: Petalidis Lawrence

PROVIDER: S-ECPF-GEOD-2727 | biostudies-other |

REPOSITORIES: biostudies-other

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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. 16 IDC samples analyzed with the U133 Plus 2.0 array compared to 4 normal control samples.

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Transcription profiling of human diffusely infiltrating astrocytic tumours, grades II, III and IV

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