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      Tamoxifen Action in ER-Negative Breast Cancer

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      1 , 1 , 2 , 3
      Signal transduction insights
      tamoxifen, breast cancer

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          Abstract

          Breast cancer is a highly heterogeneous disease. Tamoxifen is a selective estrogen receptor (ER) modulator and is mainly indicated for the treatment of breast cancer in postmenopausal women and postsurgery neoadjuvant therapy in ER-positive breast cancers. Interestingly, 5–10% of the ER-negative breast cancers have also shown sensitivity to tamoxifen treatment. The involvement of molecular markers and/or signaling pathways independent of ER signaling has been implicated in tamoxifen sensitivity in the ER-negative subgroup. Studies reveal that variation in the expression of estrogen-related receptor alpha, ER subtype beta, tumor microenvironment, and epigenetics affects tamoxifen sensitivity. This review discusses the background of the research on the action of tamoxifen that may inspire future studies to explore effective therapeutic strategies for the treatment of ER-negative and triple-negative breast cancers, the latter being an aggressive disease with worse clinical outcome.

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          Most cited references83

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          Tamoxifen in the treatment of breast cancer.

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            Role of the estrogen receptor coactivator AIB1 (SRC-3) and HER-2/neu in tamoxifen resistance in breast cancer.

            AIB1 (SRC-3) is an estrogen receptor (ER) coactivator that, when overexpressed in cultured cells, can reduce the antagonist activity of tamoxifen-bound ERs. Signaling through the HER-2 receptor pathway activates AIB1 by phosphorylation. To determine whether high AIB1 expression alone or together with HER-2 reduces the effectiveness of tamoxifen in breast cancer patients, we quantified expression of AIB1 and HER-2 in tumors from breast cancer patients with long-term clinical follow-up who received either no adjuvant therapy or adjuvant tamoxifen therapy after breast cancer surgery. AIB1 and HER-2 protein levels in tumors from 316 breast cancer patients were determined using western blot analysis. Molecular variables (e.g., expression of AIB1, ER, progesterone receptor, p53, Bcl-2), tumor characteristics, and patient outcome were assessed using Spearman rank correlation. Disease-free survival (DFS) curves were derived from Kaplan-Meier estimates, and the curves were compared by log-rank tests. The effect of AIB1 on DFS adjusted for other prognostic factors was assessed by multivariable analysis using the Cox proportional hazards model. All statistical tests were two-sided. High AIB1 expression in patients not receiving adjuvant tamoxifen therapy was associated with better prognosis and longer DFS (P =.018, log-rank test). In contrast, for patients who did receive tamoxifen therapy, high AIB1 expression was associated with worse DFS (P =.049, log-rank test), which is indicative of tamoxifen resistance. The test for interaction between AIB1 expression and tamoxifen therapy was statistically significant (P =.004). When expression of AIB1 and HER-2 were considered together, patients whose tumors expressed high levels of both AIB1 and HER-2 had worse outcomes with tamoxifen therapy than all other patients combined (P =.002, log-rank test). The antitumor activity of tamoxifen in patients with breast cancer may be determined, in part, by tumor levels of AIB1 and HER-2. Thus, AIB1 may be an important diagnostic and therapeutic target.
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              The contribution of gene expression profiling to breast cancer classification, prognostication and prediction: a retrospective of the last decade.

              In the last decade, the development of microarrays and the ability to perform massively parallel gene expression analysis of human tumours were received with great excitement by the scientific community. The promise of microarrays was of apocalyptic dimensions, with some experts envisaging that it would be a matter of a few years for this technology to replace traditional clinicopathological markers in clinical practice and treatment decision-making. The replacement of histopathology by high-tech and more objective approaches to cancer diagnosis, prognostication and prediction was, at that time, a foregone conclusion. Ten years after the initial publications of translational research studies using microarrays, one cannot deny that this technology has changed the way breast cancer is perceived. It has brought the concept of breast cancer heterogeneity to the forefront of cancer research, and the fact that distinct subtypes of breast cancer are completely different diseases that affect the same anatomical site. Furthermore, it has led to the development of prognostic and predictive 'gene signatures', which are yet to be fully incorporated into clinical practice. Importantly, though, the prognostic and predictive power of microarrays has been shown to be complementary to, rather than a replacement for, traditional clinicopathological parameters. Here we endeavour to provide a fair and balanced assessment of what microarray-based gene expression analysis has taught us in the last decade and its contribution to breast cancer classification, prognostication and prediction.
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                Author and article information

                Journal
                101535812
                38533
                Sign Transduct Insights
                Sign Transduct Insights
                Signal transduction insights
                1178-6434
                25 February 2016
                10 February 2016
                15 March 2016
                : 5
                : 1-7
                Affiliations
                [1 ]Department of Biology, Yeshiva University, New York, NY, USA
                [2 ]Department of Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, NY, USA
                [3 ]Albert Einstein Cancer Center, Albert Einstein College of Medicine, Bronx, NY, USA
                Author notes
                CORRESPONDENCE: mholz@ 123456yu.edu
                Article
                NIHMS762369
                10.4137/STI.S29901
                4792287
                26989346
                b754f705-7c9d-4773-9768-911392abd87d

                This is an open-access article distributed under the terms of the Creative Commons CC-BY-NC 3.0 License.

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                tamoxifen,breast cancer
                tamoxifen, breast cancer

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