Abstract

28 Background: Inflammatory breast cancer (IBC) is an aggressive form of BC poorly defined at the molecular level. We aim to perform genome-wide analyses of copy number variation and gene expression to identify genes reproducibly associated with survival in IBC patients. Methods: We performed concurrent genome-wide microarray analyses of copy number variable regions (CNVRs) and gene expression in IBC patients. Fifty-six pairs of breast cancer and normal specimens from IBC patients were analyzed by using Affymetrix SNP 6.0 and Affymetrix U133 plus 2.0 microarrays. To investigate genomic alterations, we used an Affymetrix Genome-Wide Human SNP 6.0 array containing 1.8 million SNP and CNV probes in total. The microarray data were imported into the Partek Genomic Suite to perform CNV analysis. Ingenuity Pathway Analysis was carried out to describe gene-gene interaction networks and canonical pathways. Cox regression model was used to evaluate the association between expression of these CNV-driven genes and survival outcomes. Results: The genomic landscape of frequent copy number variable regions (CNVRs) in at least 35% of samples was revealed. Further statistical analysis for genes located in the CNVRs identified 387 genes differentially expressed between tumor and normal tissues (p < 0.001). We demonstrated the concordance between copy number variations and gene expression changes by elevated Pearson correlation coefficients. Fisher’s exact test identified five canonical pathways that were significantly enriched among the 387 CNV-driven genes. Pathway analysis revealed two major dysregulated functions in IBC: survival regulation via Rac/PAK and PTEN/PI3K/AKT signaling pathway. Further validation using three independent cohorts demonstrated prediction of survival. Conclusions: We identified genes/pathways that may serve as prognostic markers for IBC patients by integrating gene expression profiles and copy number variations.

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