Experimental models of endocrine responsive breast cancer: strengths, limitations, and use.

Breast cancers characterized by expression of estrogen receptor-alpha; ESR1) represent approximately 70% of all new cases and comprise the largest molecular subtype of this disease. Despite this high prevalence, the number of adequate experimental models of ER+ breast cancer is relatively limited. Nonetheless, these models have proved very useful in advancing understanding of how cells respond to and resist endocrine therapies, and how the ER acts as a transcription factor to regulate cell fate signaling. We discuss the primary experimental models of ER+ breast cancer including 2D and 3D cultures of established cell lines, cell line- and patient-derived xenografts, and chemically induced rodent models, with a consideration of their respective general strengths and limitations. What can and cannot be learned easily from these models is also discussed, and some observations on how these models may be used more effectively are provided. Overall, despite their limitations, the panel of models currently available has enabled major advances in the field, and these models remain central to the ability to study mechanisms of therapy action and resistance and for hypothesis testing that would otherwise be intractable or unethical in human subjects.

MYC regulates the unfolded protein response and glucose and glutamine uptake in endocrine resistant breast cancer.

BACKGROUND: About 70% of all breast cancers are estrogen receptor alpha positive (ER+) and are treated with antiestrogens. However, 50% of ER + tumors develop resistance to these drugs (endocrine resistance). In endocrine resistant cells, an adaptive pathway called the unfolded protein response (UPR) is elevated that allows cells to tolerate stress more efficiently than in sensitive cells. While the precise mechanism remains unclear, the UPR can trigger both pro-survival and pro-death outcomes that depend on the nature and magnitude of the stress. In this study, we identified MYC, an oncoprotein that is upregulated in endocrine resistant breast cancer, as a regulator of the UPR in glucose-deprived conditions. METHODS: ER+ human breast cancer cell lines (LCC1, LCC1, LY2 and LCC9) and rat mammary tumors were used to confirm upregulation of MYC in endocrine resistance. To evaluate functional relevance of proteins, siRNA-mediated inhibition or small molecule inhibitors were used. Cell density/number was evaluated with crystal violet assay; cell cycle and apoptosis were measured by flow cytometry. Relative quantification of glutamine metabolites were determined by mass spectrometry. Signaling molecules of the UPR, apoptosis or autophagy pathways were investigated by western blotting. RESULTS: Increased MYC function in resistant cells correlated with increased dependency on glutamine and glucose for survival. Inhibition of MYC reduced cell growth and uptake of both glucose and glutamine in resistant cells. Interestingly, in glucose-deprived conditions, glutamine induced apoptosis and necrosis, arrested autophagy, and triggered the unfolded protein response (UPR) though GRP78-IRE1α with two possible outcomes: (i) inhibition of cell growth by JNK activation in most cells and, (ii) promotion of cell growth by spliced XBP1 in the minority of cells. These disparate effects are regulated, at different signaling junctions, by MYC more robustly in resistant cells. CONCLUSIONS: Endocrine resistant cells overexpress MYC and are better adapted to withstand periods of glucose deprivation and can use glutamine in the short term to maintain adequate metabolism to support cell survival. Our findings reveal a unique role for MYC in regulating cell fate through the UPR, and suggest that targeting glutamine metabolism may be a novel strategy in endocrine resistant breast cancer.

Exposure to excess estradiol or leptin during pregnancy increases mammary cancer risk and prevents parity-induced protective genomic changes in rats.

Using a preclinical model, we investigated whether excess estradiol (E2) or leptin during pregnancy affects maternal mammary tumorigenesis in rats initiated by administering carcinogen 7,12-dimethylbenz(a)anthracene (DMBA) on day 50. Two weeks later, rats were mated, and pregnant dams were treated daily with 10 µg of 17ß-estradiol, 15 µg of leptin, or vehicle from gestation day 8 to 19. Tumor development was assessed separately during weeks 1 to 12 and 13 to 22 after DMBA administration, because pregnancy is known to induce a transient increase in breast cancer risk, followed by a persistent reduction. Parous rats developed less (32%) mammary tumors than nulliparous rats (59%, P < 0.001), and the majority (93%) of tumors in the parous rats appeared before week 13 (vs. 41% in nulliparous rats), indicating that pregnancy induced a transient increase in breast cancer risk. Parous rats exposed to leptin (final tumor incidence 65%) or E2 (45%) during pregnancy developed mammary tumors throughout the tumor-monitoring period, similar to nulliparous control rats, and the incidence was significantly higher in both the leptin- and E2-exposed dams after week 12 than in the vehicle-exposed parous dams (P < 0.001). The mammary glands of the exposed parous rats contained significantly more proliferating cells (P < 0.001). In addition, the E2- or leptin-treated parous rats did not exhibit the protective genomic signature induced by pregnancy and seen in the parous control rats. Specifically, these rats exhibited downregulation of genes involved in differentiation and immune functions and upregulation of genes involved in angiogenesis, growth, and epithelial-to-mesenchymal transition.

Glucose-regulated protein 78 controls cross-talk between apoptosis and autophagy to determine antiestrogen responsiveness.

While more than 70% of breast cancers express estrogen receptor-α (ER+), endocrine therapies targeting these receptors often fail. The molecular mechanisms that underlie treatment resistance remain unclear. We investigated the potential role of glucose-regulated protein 78 (GRP78) in mediating estrogen resistance. Human breast tumors showed increased GRP78 expression when compared with normal breast tissues. However, GRP78 expression was reduced in ER+ breast tumors compared with HER2-amplifed or triple-negative breast tumors. ER+ antiestrogen-resistant cells and ER+ tumors with an acquired resistant antiestrogen phenotype were both shown to overexpress GRP78, which was not observed in cases of de novo resistance. Knockdown of GRP78 restored antiestrogen sensitivity in resistant cells, and overexpression of GRP78 promoted resistance in sensitive cells. Mechanistically, GRP78 integrated multiple cellular signaling pathways to inhibit apoptosis and stimulate prosurvival autophagy, which was dependent on TSC2/AMPK-mediated mTOR inhibition but not on beclin-1. Inhibition of autophagy prevented GRP78-mediated endocrine resistance, whereas caspase inhibition abrogated the resensitization that resulted from GRP78 loss. Simultaneous knockdown of GRP78 and beclin-1 synergistically restored antiestrogen sensitivity in resistant cells. Together, our findings reveal a novel role for GRP78 in the integration of cellular signaling pathways including the unfolded protein response, apoptosis, and autophagy to determine cell fate in response to antiestrogen therapy.

Endoplasmic reticulum stress, the unfolded protein response, and gene network modeling in antiestrogen resistant breast cancer.

Lack of understanding of endocrine resistance remains one of the major challenges for breast cancer researchers, clinicians, and patients. Current reductionist approaches to understanding the molecular signaling driving resistance have offered mostly incremental progress over the past 10 years. As the field of systems biology has begun to mature, the approaches and network modeling tools being developed and applied therein offer a different way to think about how molecular signaling and the regulation of critical cellular functions are integrated. To gain novel insights, we first describe some of the key challenges facing network modeling of endocrine resistance, many of which arise from the properties of the data spaces being studied. We then use activation of the unfolded protein response (UPR) following induction of endoplasmic reticulum stress in breast cancer cells by antiestrogens, to illustrate our approaches to computational modeling. Activation of UPR is a key determinant of cell fate decision making and regulation of autophagy and apoptosis. These initial studies provide insight into a small subnetwork topology obtained using differential dependency network analysis and focused on the UPR gene XBP1. The XBP1 subnetwork topology incorporates BCAR3, BCL2, BIK, NFκB, and other genes as nodes; the connecting edges represent the dependency structures amongst these nodes. As data from ongoing cellular and molecular studies become available, we will build detailed mathematical models of this XBP1-UPR network.

Infant feeding and the incidence of endometrial cancer.

Biological mechanisms could support both an inverse and a direct association between exposure to breast milk in infancy and the risk of cancer. Having been breast-fed has been investigated in relation to the risk of breast and other cancer sites, and conflicting results have been reported. The association between infant feeding and the risk of endometrial cancer has not been explored. From 1976 to 2004, we followed 74,757 cancer-free participants in the Nurses' Health Study who had not undergone hysterectomy. Information on infant feeding was self-reported by study participants. A total of 708 incident cases of endometrial cancer were diagnosed during follow-up. After adjusting for age, family history of endometrial cancer, birth weight, premature birth, and birth order, the incidence of endometrial cancer was not associated with ever having been breast-fed (hazards ratio, 0.94; 95% confidence interval, 0.79-1.11) or duration of having been breast-fed [hazards ratio (95% confidence interval): 1.11 (0.80-1.54), 0.84 (0.62-1.13), 1.02 (0.79-1.31), respectively, for < or =3, 4-8, and > or =9 months of having been breastfed; P for trend = 0.88]. There was no significant effect modification by menopausal status, anthropometric factors (somatotype at age 5 or 10 years, body mass index at age 18 years, or current body mass index), or by other early-life exposures (birth weight, premature birth or exposure to parental smoking in childhood). Additional adjustment for adulthood risk factors of endometrial cancer did not materially change the results. Having been breast-fed was not associated with the incidence of endometrial cancer in this cohort, but statistical power for analyses restricted to premenopausal women was limited.

Antiestrogen resistance in breast cancer and the role of estrogen receptor signaling.

Antiestrogens include agents such as tamoxifen, toremifene, raloxifene, and fulvestrant. Currently, tamoxifen is the only drug approved for use in breast cancer chemoprevention, and it remains the treatment of choice for most women with hormone receptor positive, invasive breast carcinoma. While antiestrogens have been available since the early 1970s, we still do not fully understand their mechanisms of action and resistance. Essentially, two forms of antiestrogen resistance occur: de novo resistance and acquired resistance. Absence of estrogen receptor (ER) expression is the most common de novo resistance mechanism, whereas a complete loss of ER expression is not common in acquired resistance. Antiestrogen unresponsiveness appears to be the major acquired resistance phenotype, with a switch to an antiestrogen-stimulated growth being a minor phenotype. Since antiestrogens compete with estrogens for binding to ER, clinical response to antiestrogens may be affected by exogenous estrogenic exposures. Such exposures include estrogenic hormone replacement therapies and dietary and environmental exposures that directly or indirectly increase a tumor's estrogenic environment. Whether antiestrogen resistance can be conferred by a switch from predominantly ERalpha to ERbeta expression remains unanswered, but predicting response to antiestrogen therapy requires only measurement of ERalpha expression. The role of altered receptor coactivator or corepressor expression in antiestrogen resistance also is unclear, and understanding their roles may be confounded by their ubiquitous expression and functional redundancy. We have proposed a gene network approach to exploring the mechanistic aspects of antiestrogen resistance. Using transcriptome and proteome analyses, we have begun to identify candidate genes that comprise one component of a larger, putative gene network. These candidate genes include NFkappaB, interferon regulatory factor-1, nucleophosmin, and the X-box binding protein-1. The network also may involve signaling through ras and MAPK, implicating crosstalk with growth factors and cytokines. Ultimately, signaling affects the expression/function of the proliferation and/or apoptotic machineries.