Estrogen receptor alpha and beta in breast cancer - gene expression profiles and clinical implications

• Breast cancer is the most common malignancy in women in the Western world with about 10% of women developing breast cancer during their lifetime, of which one third will eventually succumb to the metastatic form of the disease. Breast cancer arises from the epithelial cells of the breast mammary gland, but the mechanisms involved in tumor initiation, progression, and metastasis are still not fully understood. However, estrogen and its receptors are believed to play a crucial role in these events. Estrogen receptor alpha (ERalpha) has long been identified as a target for treatment and numerous studies have shown that patients expressing ERalpha are more likely to respond to endocrine therapy such as tamoxifen; however a significant fraction become resistant. Little is known of the role of the second estrogen receptor, estrogen receptor beta (ERbeta), in breast tumor biology and therapy response. This thesis is primarily concerned with investigating the global differences in gene expression between tumors that express and do not express ERalpha and/or ERbeta, and the relationship of such profiles to outcome in the setting of tamoxifen therapy. The present study shows that ERalpha status in primary breast tumor biopsies is associated with a very distinct gene expression profile, as determined by cDNA microarrays, involving a large number of genes (Papers I and III). Only a small fraction of these ERalpha-associated genes have previously been identified as estrogen-responsive in cell culture (Paper I). In addition, not only is the ERalpha status as a binary variable encoded in the gene expression profiles, but also the actual level of protein content can be predicted, as well as the percent cells in the DNA synthesis phase of the cell cycle and other prognostic markers (Paper III). However, predicting response to tamoxifen using gene expression profiles from primary breast tumors was not possible in a cohort of 44 patient with varying ERalpha status and clinical outcome (Paper II). Additionally, a previously published prognosis predictor did not have any prognostic significance in this data, suggesting that different data sets and various tumor/patient/treatment characteristics selected influence the success of an array-based predictor for prognosis (Paper II). Much less is known about the transactivating properties of ERbeta and its relationship to ERalpha and tamoxifen response. Herein, the ERbeta protein is shown to have prognostic value after adjuvant tamoxifen therapy in a large patient set (n=353; Paper IV). However, subgroup analysis shows the effect to be only significant in patients with tumors lacking ERalpha. From cDNA microarray analysis of a subset of these tumors, an ERbeta-associated gene expression profile could be generated from the ERalpha negative group of tumors but not for the ERalpha positive group, further corroborating the notion that ERbeta selectively influences the biological processes in tumors lacking ERalpha (Paper IV). These results suggest that the small subset of ERalpha negative tumors responding to tamoxifen may be explained by the presence of ERbeta, and that ERbeta is not a surrogate marker for ERalpha but is associated with its own biological processes and may respond to tamoxifen via different target genes. In conclusion, together these studies have added to our understanding of the importance of estrogen receptor status and their biological consequences in breast cancer.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Cancer och onkologi (hsv//swe)

MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Cancer and Oncology (hsv//eng)

Keyword

Klinisk biologi

oncology

cancerology

Cytologi

onkologi

cancer

Cytology

artificial neural networks

gene expression profiling

microarray

tamoxifen

adjuvant endocrine therapy

ER

estrogen receptor beta

Breast cancer

estrogen receptor alpha

Clinical biology

Publication and Content Type

dok (subject category)

vet (subject category)