Gene Expression Profiling of Breast Cancer according to Mammographic Microcalcifications

Abstract

Introduction: Mammographic microcalcifications are important in early detection and diagnosis of breast cancer. However, the underlying biological mechanisms of microcalcifications and the association between microcalcifications and prognosis of breast cancer are largely unknown. This study was to investigate association between mammographic microcalcifications and gene expression profiles of breast cancer using microarray analysis. Methods: Gene expression analysis was performed using Affymetrix GeneChip® Human Gene 2.0 ST arrays in 168 breast cancer patients (median age, 50.0 years

range, 21-79 years). Mammographic microcalcifications of these patients were reviewed by three radiologists and were grouped into no microcalcification (n=99), low-to-intermediate (n=37) and highly (n=32) suspicious microcalcifications group. To identify differentially expressed genes (DEGs) between three groups, the one-way analysis of variance was carried out with post hoc comparisons made with Tukey's honest significant difference test and P value < 0.05 was applied. To explore biological meaning behind DEGs, we used DAVID for gene ontology analysis and BioLattice for clustering analysis. Results: Total 2551 genes showed different expressions in comparison of three groups

1838 DEGs (955 up-regulated and 883 down-regulated) in highly suspicious microcalcifications/no microcalcification comparison and 484 DEGs (342 up-regulated and 142 down-regulated) in highly suspicious/low-to-intermediate microcalcifications comparison, 457 DEGs (126 up-regulated and 331 down-regulated) in low-to-intermediate/no microcalcification comparison were discovered. GO analysis revealed that immune, defense and inflammatory response were decreased in highly suspicious microcalcifications group when it compared to no microcalcification group. Clustering analysis using BioLattice also discovered that immune system is associated with mammographic microcalcifications in total population and human epidermal growth factor receptor 2-negative subgroup. Conclusions: Gene expression patterns are different according to the status of mammographic microcalcifications in breast cancer. Breast cancers with mammographic microcalcifications are associated with decreased immune system activity.