Dataset Information

Cooperative Dynamics of AR and ER Activity in Breast Cancer.

ABSTRACT: Androgen receptor (AR) is expressed in 90% of estrogen receptor alpha-positive (ER+) breast tumors, but its role in tumor growth and progression remains controversial. Use of two anti-androgens that inhibit AR nuclear localization, enzalutamide and MJC13, revealed that AR is required for maximum ER genomic binding. Here, a novel global examination of AR chromatin binding found that estradiol induced AR binding at unique sites compared with dihydrotestosterone (DHT). Estradiol-induced AR-binding sites were enriched for estrogen response elements and had significant overlap with ER-binding sites. Furthermore, AR inhibition reduced baseline and estradiol-mediated proliferation in multiple ER+/AR+ breast cancer cell lines, and synergized with tamoxifen and fulvestrant. In vivo, enzalutamide significantly reduced viability of tamoxifen-resistant MCF7 xenograft tumors and an ER+/AR+ patient-derived model. Enzalutamide also reduced metastatic burden following cardiac injection. Finally, in a comparison of ER+/AR+ primary tumors versus patient-matched local recurrences or distant metastases, AR expression was often maintained even when ER was reduced or absent. These data provide preclinical evidence that anti-androgens that inhibit AR nuclear localization affect both AR and ER, and are effective in combination with current breast cancer therapies. In addition, single-agent efficacy may be possible in tumors resistant to traditional endocrine therapy, as clinical specimens of recurrent disease demonstrate AR expression in tumors with absent or refractory ER.This study suggests that AR plays a previously unrecognized role in supporting E2-mediated ER activity in ER+/AR+ breast cancer cells, and that enzalutamide may be an effective therapeutic in ER+/AR+ breast cancers. Mol Cancer Res; 14(11); 1054-67. ©2016 AACR.

SUBMITTER: D'Amato NC

PROVIDER: S-EPMC5107172 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Cooperative Dynamics of AR and ER Activity in Breast Cancer.

D'Amato Nicholas C NC Gordon Michael A MA Babbs Beatrice B Spoelstra Nicole S NS Carson Butterfield Kiel T KT Torkko Kathleen C KC Phan Vernon T VT Barton Valerie N VN Rogers Thomas J TJ Sartorius Carol A CA Elias Anthony A Gertz Jason J Jacobsen Britta M BM Richer Jennifer K JK

Molecular cancer research : MCR 20160826 11

Androgen receptor (AR) is expressed in 90% of estrogen receptor alpha-positive (ER<sup>+</sup>) breast tumors, but its role in tumor growth and progression remains controversial. Use of two anti-androgens that inhibit AR nuclear localization, enzalutamide and MJC13, revealed that AR is required for maximum ER genomic binding. Here, a novel global examination of AR chromatin binding found that estradiol induced AR binding at unique sites compared with dihydrotestosterone (DHT). Estradiol-induced ...[more]

PMID: 27565181

Similar Datasets

Project description:BackgroundMultiple clinical trials demonstrate consistent but modest benefit of adjuvant extended endocrine therapy (EET) in HR + breast cancer patients. Predictive biomarkers to identify patients that benefit from EET are critical to balance modest reductions in risk against potential side effects of EET. This study compares the performance of the Breast Cancer Index, BCI (HOXB13/IL17BR, H/I), with expression of estrogen (ER), progesterone (PR), and androgen receptors (AR), and Ki67, for prediction of EET benefit.MethodsNode-positive (N+) patients from the Trans-aTTom study with available tissue specimen and BCI results (N = 789) were included. Expression of ER, PR, AR, and Ki67 was assessed by quantitative immunohistochemistry. BCI (H/I) gene expression analysis was conducted by quantitative RT-PCR. Statistical significance of the treatment by biomarker interaction was evaluated by likelihood ratio tests based on multivariate Cox proportional models, adjusting for age, tumor size, grade, and HER2 status. Pearson's correlation coefficients were calculated to evaluate correlations between BCI (H/I) versus ER, PR, AR, Ki67 and AR/ER ratio.ResultsEET benefit, measured by the difference in risk of recurrence between patients treated with tamoxifen for 10 versus 5 years, is significantly associated with increasing values of BCI (H/I) (interaction P = 0.01). In contrast, expression of ER (P = 0.83), PR (P = 0.66), AR (P = 0.78), Ki67 (P = 0.87) and AR/ER ratio (P = 0.84) exhibited no significant relationship with EET benefit. BCI (H/I) showed a very weak negative correlation with ER (r = - 0.18), PR (r = - 0.25), and AR (r = - 0.14) expression, but no correlation with either Ki67 (r = 0.04) or AR/ER ratio (r = 0.02).ConclusionThese findings are consistent with the growing body of evidence that BCI (H/I) is significantly predictive of response to EET and outcome. Results from this direct comparison demonstrate that expression of ER, PR, AR, Ki67 or AR/ER ratio are not predictive of benefit from EET. BCI (H/I) is the only clinically validated biomarker that predicts EET benefit.

Project description:The rates and routes of lethal systemic spread in breast cancer are poorly understood owing to a lack of molecularly characterized patient cohorts with long-term, detailed follow-up data. Long-term follow-up is especially important for those with oestrogen-receptor (ER)-positive breast cancers, which can recur up to two decades after initial diagnosis1-6. It is therefore essential to identify patients who have a high risk of late relapse7-9. Here we present a statistical framework that models distinct disease stages (locoregional recurrence, distant recurrence, breast-cancer-related death and death from other causes) and competing risks of mortality from breast cancer, while yielding individual risk-of-recurrence predictions. We apply this model to 3,240 patients with breast cancer, including 1,980 for whom molecular data are available, and delineate spatiotemporal patterns of relapse across different categories of molecular information (namely immunohistochemical subtypes; PAM50 subtypes, which are based on gene-expression patterns10,11; and integrative or IntClust subtypes, which are based on patterns of genomic copy-number alterations and gene expression12,13). We identify four late-recurring integrative subtypes, comprising about one quarter (26%) of tumours that are both positive for ER and negative for human epidermal growth factor receptor 2, each with characteristic tumour-driving alterations in genomic copy number and a high risk of recurrence (mean 47-62%) up to 20 years after diagnosis. We also define a subgroup of triple-negative breast cancers in which cancer rarely recurs after five years, and a separate subgroup in which patients remain at risk. Use of the integrative subtypes improves the prediction of late, distant relapse beyond what is possible with clinical covariates (nodal status, tumour size, tumour grade and immunohistochemical subtype). These findings highlight opportunities for improved patient stratification and biomarker-driven clinical trials.

Dataset Information

Cooperative Dynamics of AR and ER Activity in Breast Cancer.

Publications

Cooperative Dynamics of AR and ER Activity in Breast Cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets