Differential gene expression in ERα-positive and ERα-negative breast cancer cells upon leptin stimulation

Paul-Ehrlich-Institute, Langen, Germany.
Endocrine (Impact Factor: 3.88). 02/2013; 44(2). DOI: 10.1007/s12020-013-9897-y
Source: PubMed


In postmenopausal women, adipositas represents a serious risk factor for cancer development and progression. White adipose tissue secretes the 16 kDa hormone leptin which plays a key role in the regulation of appetite and metabolism. An increasing number of reports indicate that leptin also interferes with signal transduction pathways implicated in the development of breast cancer. In our previous study, we identified the estrogen receptor alpha (ERα) as a relevant enhancer of leptin-induced signal transduction leading to transactivation of signal transducer and activator of transcription 3 (Stat3). The purpose of this study is the investigation of specific target gene expression in response to leptin-mediated Stat3 signaling. We performed a comprehensive microarray analysis of ERα-positive and ERα-negative MDA-MB-231 cells upon leptin treatment and identified 49 genes which showed a significant ERα-dependent regulation in leptin-treated MDA-MB-231 cells. There was no intersection with genes which were merely up- or downregulated by ERα expression and only 9 and 11 genes overlapping targets which were regulated by leptin stimulation either in ERα-expressing or ERα-negative MDA-MB-231 cells, respectively. To demonstrate the specificity, expression of three target genes was validated by quantitative real-time PCR. In conclusion, these data imply that leptin can induce a different set of target genes dependent on ERα expression, which might contribute to the development and progression of cancer diseases.

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    • "Moreover, it was determined that estrogen and leptin affected the same receptors and pathways in the arcuate nucleus in the hypothalamus. Molecular studies showed that both hormones had effects on " signal transducer and activator of transcription 3 " (STAT3), and that estrogen increased leptin-induced STAT3 phosphorylation (Binai et al., 2013). However, no study showing a correlation between leptin and leptin receptor polymorphisms and gynecomastia has been published in the literature. "
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    ABSTRACT: Gynecomastia is a benign breast enlargement in males that affects approximately one-third of adolescents. The exact mechanism is not fully understood; however, it has been proposed that estrogen receptors and aromatase enzyme activity may play important roles in the pathogenesis of gynecomastia. While many studies have reported that aromatase enzyme (CYP19) gene polymorphism is associated with gynecomastia, only one study has shown a relationship between estrogen receptor (ER) alpha and beta gene polymorphism and gynecomastia. Thus, the aim of this study was to evaluate the relationships between CYP19 (rs2414096), ER alpha (rs2234693), ER beta (rs4986938), leptin (rs7799039), and leptin receptor (rs1137101) gene polymorphisms and gynecomastia. This study included 107 male adolescents with gynecomastia and 97 controls. Total serum testosterone (T) and estradiol (E2) levels were measured, and DNA was extracted from whole blood using the PCR-RFLP technique. The polymorphic distributions of CYP19, ER alpha, ER beta, leptin and leptin receptor genes were compared. The median E2 level was 12.41 (5.00-65.40) pg/ml in the control group and 16.86 (2.58-78.47) pg/ml in the study group (p<0.001). The median T level was 2.19 (0.04-7.04) ng/ml in the control group and 1.46 (0.13-12.02) ng/ml in the study group (p=0.714). There was a significant relationship between gynecomastia and leptin receptor rs1137101 (p=0.002) and ER beta receptor rs4986938 gene polymorphisms (p=0.002). According to our results, increased E2 level and ER beta gene rs4986938 polymorphism might explain why some adolescents have gynecomastia. Leptin receptor gene rs1137101 polymorphism might affect susceptibility to gynecomastia.
    Gene 03/2014; 541(2). DOI:10.1016/j.gene.2014.03.013 · 2.14 Impact Factor
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    ABSTRACT: Estrogens are known to regulate the proliferation of breast cancer cells and to alter their cytoarchitectural and phenotypic properties, but the gene networks and pathways by which estrogenic hormones regulate these events are only partially understood. We used global gene expression profiling by Affymetrix GeneChip microarray analysis, with KEGG pathway enrichment, PPI network construction, module analysis and text mining methods to identify patterns and time courses of genes that are either stimulated or inhibited by estradiol (E2) in estrogen receptor (ER)-positive MCF-7 human breast cancer cells. Of the genes queried on the Affymetrix Human Genome U133 plus 2.0 microarray, we identified 628(12h), 852(24h) and 880 (48h) differentially expressed genes (DEGs) that showed a robust pattern of regulation by E2. From pathways enrichment analysis, we found out the changes of metabolic pathways of E2 treated samples at each time points. At 12h time point, the changes of metabolic pathways were mainly focused on pathways in cancer, focal adhesion, chemokine signaling pathway. At 24h time point, the changes were mainly enriched in neuroactive ligand-receptor interaction, Cytokine-cytokine receptor interaction and calcium signaling pathway. At 48h time point, the significant pathways were pathways in cancer, regulation of actin cytoskeleton, cell adhesion molecules (CAMs), Axon guidance and ErbB signaling pathway. Of interest, our PPI network analysis and module analysis found that E2 treatment induced enhancement of PRSS23 at the three time points and PRSS23 was in the central position of each module. Text mining results showed that the important genes of DEGs have relationship with signal pathways, such as ERbB pathway (AREG), Wnt pathway (NDP), MAPK pathway (NTRK3, TH), IP3 pathway(TRA@) and some transcript factors (TCF4, MAF). Our studies highlight the diverse gene networks and metabolic and cell regulatory pathways through which E2 operates to achieve its widespread effects on breast cancer cells.
    Gene 08/2013; 533(1). DOI:10.1016/j.gene.2013.08.027 · 2.14 Impact Factor

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