NCBI Logo
GEO Logo
   NCBI > GEO > Accession DisplayHelp Not logged in | LoginHelp
GEO help: Mouse over screen elements for information.
          Go
Series GSE26338 Query DataSets for GSE26338
Status Public on Jun 20, 2011
Title Genomic analysis identifies unique signatures predictive of brain, lung, and liver relapse
Organism Homo sapiens
Experiment type Expression profiling by array
Summary The ability to predict metastatic potential is of clinical and biological importance. Numerous metastasis/relapse predictors exist for breast cancer patients; however, what is less well established is whether predicting metastasis to specific organs sites is feasible. In this study we sought to determine: 1) the degree to which gene signatures vary across tumors and their metastases, 2) if genomic intrinsic subtypes associate with particular organs of relapse, and 3) if other genomic signatures can predict spread to specific organs. Using a gene expression microarray data set of >1000 breast tumors and metastases, we observed that >90% of 298 gene signatures were similarly expressed between matched pairs of breast tumors and metastases; those most altered were reflective of cell types including fibroblasts and immune cells. Significant associations were identified between tumor subtypes and organ of first relapse. Among these, HER2-enriched tumors were significantly associated with liver, and Basal-like and Claudin-low tumors with brain and lung. Correspondingly, previously published brain and lung metastasis signatures, along with embryonic stem cell and tumor initiating cell signatures, were also associated with Basal-like and Claudin-low subtypes. These signatures strongly correlated with low Differentiation Scores (DS) and, to a lesser extent, high proliferation. Interestingly, within Basal-like and Claudin-low tumors, low DS further predicted for brain and lung metastases. In total, intrinsic subtype and DS provide clinically useful information that identifies the distant organ sites that should be most closely monitored for signs of disease recurrence.
 
Overall design 414 samples profiled on Agilent microarrays.
 
Contributor(s) Harrell CJ
Citation(s) 21671017
Submission date Dec 28, 2010
Last update date Nov 17, 2017
Contact name Charles M. Perou
E-mail(s) cperou@med.unc.edu
Organization name University of North Carolina at Chapel Hill
Department Professor of Genetics, and Pathology & Laboratory Medicine; Lineberger Comprehensive Cancer Center
Street address 12-044 Lineberger Comprehensive Cancer Center CB# 7295
City Chapel Hill
State/province NC
ZIP/Postal code 27599-7264
Country USA
 
Platforms (7)
GPL885 Agilent-011521 Human 1A Microarray G4110A (Feature Number version)
GPL887 Agilent-012097 Human 1A Microarray (V2) G4110B (Feature Number version)
GPL1197 Agilent Human 1A Oligo V2+UNC_custom array
Samples (414)
GSM21709 H1A9529-0094C
GSM21710 H1A6433-2989V2
GSM21711 H1A6261-1490V2
Relations
BioProject PRJNA136915

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
GSE26338_RAW.tar 11.9 Mb (http)(custom) TAR
Processed data included within Sample table

| NLM | NIH | GEO Help | Disclaimer | Accessibility |
NCBI Home NCBI Search NCBI SiteMap