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AJR Am J Roentgenol. 2012 Sep;199(3):654-63. doi: 10.2214/AJR.11.7824.

Radiogenomic analysis of breast cancer using MRI: a preliminary study to define the landscape.

Author information

1
Department of Radiological Sciences and Radiology-Pathology Program, University of California-Los Angeles, David Geffen School of Medicine, Los Angeles, CA 90095-1721, USA.

Abstract

OBJECTIVE:

Molecular profiling studies have defined the increasing importance of gene expression phenotyping in breast cancer. However, the relationship between global transcriptomic profiles and the information provided by breast MRI remains to be examined. In this pilot study, our aim was to provide a preliminary radiogenomic association map linking MR image phenotypes to underlying global gene expression patterns in breast cancer.

MATERIALS AND METHODS:

From a multiinstitutional study, a total of 353 patients with a diagnosis of breast cancer were examined for gene expression analysis. Radiogenomic analysis was then performed on a subset of these patients (n = 10) who also underwent breast MRI. Two radiologists evaluated each MRI study across 26 predefined imaging phenotypes. Analyses were performed to correlate the expression and imaging data and to define associations between specific MR image phenotypes and gene sets of interest.

RESULTS:

High-level analysis revealed 21 imaging traits that were globally correlated (p < 0.05), with 71% of the total genes measured in patients with breast cancer. A significant correlation was identified between heterogeneous enhancement patterns and a previously described interferon breast cancer subtype (p < 0.01). We also identified 12 imaging traits that significantly correlated (false discovery rate < 0.25) with gene sets related to breast cancer and 11 traits correlated (false discovery rate < 0.25) to prognostic gene sets (van't Veer, wound response, and hypoxia metagene signatures) using gene enrichment analysis.

CONCLUSION:

Radiogenomic analysis of breast cancer with MRI is a novel approach to understanding the underlying molecular biology of breast cancers.

PMID:
22915408
DOI:
10.2214/AJR.11.7824
[Indexed for MEDLINE]

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