Clinical instability of breast cancer markers is reflected in long-term in vitro estrogen deprivation studies.

BACKGROUND: Long-term estrogen deprivation models are widely employed in an in vitro setting to recapitulate the hormonal milieu of breast cancer patients treated with endocrine therapy. Despite the wealth information we have garnered from these models thus far, a comprehensive time-course analysis of the estrogen (ER), progesterone (PR), and human epidermal growth factor 2 (HER-2/neu) receptors on the gene and protein level, coupled with expression array data is currently lacking. We aimed to address this knowledge gap in order to enhance our understanding of endocrine therapy resistance in breast cancer patients. METHODS: ER positive MCF7 and BT474 breast cancer cells were grown in estrogen depleted medium for 10 months with the ER negative MDA-MB-231 cell line employed as control. ER, PR and HER-2/neu expression were analysed at defined short and long-term time points by immunocytochemistry (ICC), and quantitative real-time RT-PCR (qRT-PCR). Microarray analysis was performed on representative samples. RESULTS: MCF7 cells cultured in estrogen depleted medium displayed decreasing expression of ER up to 8 weeks, which was then re-expressed at 10 months. PR was also down-regulated at early time points and remained so for the duration of the study. BT474 cells generally displayed no changes in ER during the first 8 weeks of deprivation, however its expression was significantly decreased at 10 months. PR expression was also down-regulated early in BT474 samples and was absent at later time points. Finally, microarray data revealed that genes and cell processes down-regulated in both cell lines at 6 weeks overlapped with those down-regulated in aromatase inhibitor treated breast cancer patients. CONCLUSIONS: Our data demonstrate that expression of ER, PR, and cell metabolic/proliferative processes are unstable in response to long-term estrogen deprivation in breast cancer cell lines. These results mirror recent clinical findings and again emphasize the utility of LTED models in translational research.

Activated ERK1/2 and phosphorylated oestrogen receptor alpha are associated with improved breast cancer survival in women treated with tamoxifen.

The aim of this study was to investigate the expression of activated (phosphorylated) ERK1/2, oestrogen receptor alpha phosphorylated at S118 (ERalphaS118), and HER2 in primary breast cancer, and to make correlations with the outcome of tamoxifen therapy. We performed immunohistochemical analysis to determine the expression of HER2, ERalphaS118, and activated ERK1/2 in tumours obtained from 279 women with primary breast cancer. HER2 status was also estimated by fluorescence in situ hybridisation. We identified 108 women with ERalpha-positive tumours who had received adjuvant tamoxifen. Activated ERK1/2 (pERK1/2) and ERalphaS118 were found to be associated with each other and with other factors correlated with good prognosis. HER2 was inversely associated with pERK1/2. Positive staining for pERK1/2 (particularly intense staining) indicated better relapse-free survival (P=0.05) and a trend towards better breast cancer-corrected survival in women treated with tamoxifen. To conclude, this study shows that activated ERK1/2 and ERalphaS118 are associated with improved survival. The poorer outcome in HER2-positive women who receive adjuvant tamoxifen cannot be explained by the crosstalk between HER2 and ERalphaS118 via activated ERK1/2 alone.

Gene expression profiling spares early breast cancer patients from adjuvant therapy: derived and validated in two population-based cohorts.

INTRODUCTION: Adjuvant breast cancer therapy significantly improves survival, but overtreatment and undertreatment are major problems. Breast cancer expression profiling has so far mainly been used to identify women with a poor prognosis as candidates for adjuvant therapy but without demonstrated value for therapy prediction. METHODS: We obtained the gene expression profiles of 159 population-derived breast cancer patients, and used hierarchical clustering to identify the signature associated with prognosis and impact of adjuvant therapies, defined as distant metastasis or death within 5 years. Independent datasets of 76 treated population-derived Swedish patients, 135 untreated population-derived Swedish patients and 78 Dutch patients were used for validation. The inclusion and exclusion criteria for the studies of population-derived Swedish patients were defined. RESULTS: Among the 159 patients, a subset of 64 genes was found to give an optimal separation of patients with good and poor outcomes. Hierarchical clustering revealed three subgroups: patients who did well with therapy, patients who did well without therapy, and patients that failed to benefit from given therapy. The expression profile gave significantly better prognostication (odds ratio, 4.19; P = 0.007) (breast cancer end-points odds ratio, 10.64) compared with the Elston-Ellis histological grading (odds ratio of grade 2 vs 1 and grade 3 vs 1, 2.81 and 3.32 respectively; P = 0.24 and 0.16), tumor stage (odds ratio of stage 2 vs 1 and stage 3 vs 1, 1.11 and 1.28; P = 0.83 and 0.68) and age (odds ratio, 0.11; P = 0.55). The risk groups were consistent and validated in the independent Swedish and Dutch data sets used with 211 and 78 patients, respectively. CONCLUSION: We have identified discriminatory gene expression signatures working both on untreated and systematically treated primary breast cancer patients with the potential to spare them from adjuvant therapy.

Thrombospondin-1 expression in relation to p53 status and VEGF expression in human breast cancers.

The aim of the present study was to study the expression and relationship of potential angiogenic factors. Paraffin-embedded tumour sections from 261 breast cancer patients were stained immunohistochemically for thrombospondin (TSP-1) expression. p53 status was previously determined by cDNA-based sequencing, and vascular endothelial growth factor (VEGF) protein expression had been previously analysed using an immunoassay. 241 cancers (92%) had detectable levels of TSP-1. No associations between TSP-1 and p53 status or VEGF were found. No correlations between TSP-1 and relapse-free (P=0.3), breast cancer-corrected (P=0.2) or overall survival (P=0.5) were found. A correlation was found for patients with p53 mutations, but negative p53 expression, with higher VEGF levels (P=0.009), but there was no correlation between this p53 group and those with low TSP-1 levels (P=0.2). In conclusion, TSP-1 expression was not prognostic and was not associated with neither p53-status or VEGF expression.