Gene expression profiling of breast cancer cell lines in response to soy isoflavones using a pangenomic microarray approach

Abstract

Although the rate of breast cancer differs between women in Asian and Western countries, molecular genetics/genomics basis of this epidemiological observation remains elusive. Moreover, the intake of phytoestrogens is associated with a lower incidence of breast cancer. Genistein and daidzein are the primary soy isoflavones with a chemical structure similar to estrogens. Conceivably, the actions of phytoestrogens on gene expression signatures might mediate their postulated effects on breast cancer pathogenesis. The present study evaluated the transcriptional responsiveness of breast cancer cells to soy phytoestrogens using a whole-genome microarray-based approach. Human breast cancer cell lines and a fibrocystic breast cell line were treated with genistein or daidzein. We identified 278 and 334 differentially expressed genes after genistein or daidzein treatment, respectively, in estrogen-positive (MCF-7) and estrogen-negative (MDA-MB-231, MCF-10a) cells. Hierarchical clustering of this finding revealed a significant modulation, respectively, of 246 or 169 genes after genistein or daidzein exposures. Importantly, the molecular pathways for the differentially expressed genes included those that relate to cell communication, biodegradation of xenobiotics, lipid metabolism, signal transduction, and cell growth/death. These molecular observations collectively contribute to a growing knowledgebase on the putative mechanism(s) of action of phytoestrogens in breast cancer pathogenesis and chemoprevention.

FIG. 1.

M Box Plot for all slides (A), with no normalization, and (B), with normalization within and between arrays. Example of daidzein exposure in corresponding arrays with normalization using a global lowess method, based on the local estimation of intensities and a regression calculation weighted towards similar spots.

FIG. 2.

Hierarchical clustering of the gene expression profiles of (A), daidzein and (B), genistein exposures according to the ER status discrimination between MCF-7, MDA-MB-231 breast cancer cell lines, and MCF-10a fibrocystic breast cell line, performed with TIGR MeV version 4.0.0 using a complete-linkage Pearson correlation method.

FIG. 3.

Volcano-plot of gene expression profile using a differential expression cutoff of twofold. Example of genistein exposure according to the ER status discrimination between the MCF-7, MDA-MB-231 breast cancer cell lines, and MCF-10a fibrocystic breast cell line, performed with TIGR MeV version 4.0.0 using a t-test method. Genes represented over the cutoff line were considered modulated as overexpressed on the right and underexpressed on the left.