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Series GSE22544 Query DataSets for GSE22544
Status Public on Jun 24, 2010
Title Integration of transcript expression, copy number and LOH analysis of infiltrating ductal carcinoma of the breast: expression analysis
Organism Homo sapiens
Experiment type Expression profiling by array
Summary 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.
 
Overall design 16 IDC samples analyzed with the U133 Plus 2.0 array compared to 4 normal control samples.
 
Contributor(s) Hawthorn L
Citation(s) 20799942
Submission date Jun 23, 2010
Last update date Mar 25, 2019
Contact name Lesleyann Hawthorn
E-mail(s) lhawthorn@mcg.edu
Phone 7067214384
Fax 7067211660
Organization name Medical College of Georgia Cancer Center
Department Molecular Oncology
Street address 1120 15th St
City Augusta
State/province GA
ZIP/Postal code 30912
Country USA
 
Platforms (1)
GPL570 [HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array
Samples (20)
GSM559616 Patient 1, IDC
GSM559617 Patient 2, IDC
GSM559618 Patient 4, IDC
This SubSeries is part of SuperSeries:
GSE22840 Integration of transcript expression, copy number and LOH analysis of infiltrating ductal carcinoma of the breast
Relations
BioProject PRJNA129103

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE22544_RAW.tar 93.8 Mb (http)(custom) TAR (of CEL)
Processed data included within Sample table

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