Activation of the glucocorticoid receptor is associated with poor prognosis in estrogen receptor-negative breast cancer

Abstract

Estrogen receptor-negative (ER(-)) breast cancers have limited treatment options and are associated with earlier relapses. Because glucocorticoid receptor (GR) signaling initiates antiapoptotic pathways in ER(-) breast cancer cells, we hypothesized that activation of these pathways might be associated with poor prognosis in ER(-) disease. Here we report findings from a genome-wide study of GR transcriptional targets in a premalignant ER(-) cell line model of early breast cancer (MCF10A-Myc) and in primary early-stage ER(-) human tumors. Chromatin immunoprecipitation with massively parallel sequencing (ChIP-seq) coupled to time-course expression profiling led us to identify epithelial-to-mesenchymal transition (EMT) pathways as an important aspect associated with GR activation. We validated these findings by carrying out a meta-analysis of primary breast tumor gene expression from 1,378 early-stage breast cancer patients with long-term clinical follow-up, confirming that high levels of GR expression significantly correlated with shorter relapse-free survival in ER(-) patients who were treated or untreated with adjuvant chemotherapy. Notably, in ER(+) breast cancer patients, high levels of GR expression in tumors were significantly associated with better outcome relative to low levels of GR expression. Gene expression analysis revealed that ER(-) tumors expressing high GR levels exhibited differential activation of EMT, cell adhesion, and inflammation pathways. Our findings suggest a direct transcriptional role for GR in determining the outcome of poor-prognosis ER(-) breast cancers.

Figures

Figure 1. Relative genomic locations of GR binding regions (GBRs) identified by ChIP-seq

MCF10A-Myc cells were treated with dex (10−6M) or vehicle for one hour followed by GR ChIP-sequencing. Dex-specific GBRs (n=1515) were identified and then mapped to the human genome (NCBI36). The relative percentage of GR binding regions (GBRs) in genic vs. intergenic locations is indicated.

Figure 2. Relative percentage of glucocorticoid-regulated genes with proximal (0–10kb) versus distal (10–100kb) GBR locations

GR direct target genes were identified as having at least one GBR within 100kb of the transcription start site (TSS) and as showing at least 1.5-fold gene expression change at the designated time point following treatment with dex (10−6M) relative to vehicle. The percentage represents the proportion of upregulated (or downregulated) genes with associated GBRs mapping within 10kb (black bars) versus 10 to 100kb (white bars) of the TSS.

Figure 3. Kaplan-Meier estimates of relapse-free survival (RFS) for early stage breast cancer patients with NR3C1-high versus -low tumors, by ESR1 status

Tumors in the top quartile of NR3C1 expression were identified as “NR3C1-high,” while tumors in the bottom quartile of NR3C1 expression were identified as “NR3C1-low.” A, ESR1+ untreated NR3C1-high patients (n=87) had a better outcome (p=0.03, log-rank test; HR=0.60) than NR3C1-low untreated patients (n=151). B, ESR1−/ NR3C1-high patients who did not receive adjuvant chemotherapy (n=71) had a worse outcome (p=0.001, log-rank test; HR=2.23) than NR3C1-low untreated patients (n=61). C, ESR1+/NR3C1-high patients (n=136) who received adjuvant tamoxifen treatment had a significantly better outcome (p=7.75e-8, log-rank test; HR=0.25) than ESR1+ / NR3C1-low adjuvant tamoxifen treated patients (n=68). D, ESR1− / NR3C1-high patients who received adjuvant chemotherapy treatment (n=18) had a significantly worse RFS (p=5.8e-7, log-rank test; HR=6.83) than ESR1− / NR3C1-low adjuvant chemotherapy-treated patients (n=28).

Figure 4. Genes and gene expression pathways associated with NR3C1-high (versus NR3C1-low) tumors divided by ESR1 (ER) status

The number of differentially expressed genes (either 1.5-fold induced or repressed) between the highest versus lowest NR3C1 expression quartiles in ESR1+ and ESR1− breast cancers is shown. GeneGo’s MetaCore gene enrichment pathway analysis was then used to identify highly significant biological pathways from these differentially expressed genes in (ESR1) ER+ and (ESR1) ER− tumors.