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Genome-wide analysis of in-trans correlations between copy number and expression with application to human breast cancer

ABSTRACT: Background: Genomic instability is a hallmark of cancer and is frequently reflected in the DNA copy number profile and the expression profile of genes. Methodology is needed to compare array-CGH data and microarray expression data in order to unveil effects of DNA copy number alterations of a gene on the expression of the gene itself (in-cis effects) and on other genes (in-trans effects). Results: We present a method for detection of gene dosage effects on gene expression that first searches for genome-wide in-cis associations between copy number and expression, and then investigates in-trans effects of these genes. A key element of the method is a correction step to eliminate potential confounding effects of in-cis associations when searching for in-trans associations. This facilitates reliable detection of local in-trans associations (i.e. associations within a chromosome) and alleviates the problem of co-occurring copy number aberrations across the genome. Applying the method to data collected from breast carcinomas from 20 women, we found 422 genes with expression levels that are highly correlated to DNA copy number (in-cis) in certain regions of the genome. Of these, 109 (26%) had significant trans-correlation with the expression levels of a large number of genes (20 or more). The strongest trans-regulators were also differentially expressed in subgroups that were found on the basis of expression data by classification of the tumors to previously defined breast cancer subtypes. A study of the most significant in-trans correlated genes yields significant enrichment of certain cancer related pathways and GO terms. Conclusions: We introduce a method for the joint comparative analysis of expression and copy number profiles for the discovery and investigation of in-cis and in-trans regulatory mechanisms. Using data from 20 primary human breast cancers, a number of significant in-trans regulatory genes were found and their biological relevance indicated, calling for the application of the methods on larger data sets. Keywords: Correlations between copy number and gene expression, breast cancer

ORGANISM(S): Homo sapiens

PROVIDER: GSE10583 | GEO | 2010/07/01

SECONDARY ACCESSION(S): PRJNA107849

REPOSITORIES: GEO

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Genome-wide analysis of in-trans correlations between copy number and expression with application to human breast cancer

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