Integrated molecular analysis of Tamoxifen-resistant invasive lobular breast cancer cells identifies MAPK and GRM/mGluR signaling as therapeutic vulnerabilities.

Invasive lobular breast cancer (ILC) is an understudied malignancy with distinct clinical, pathological, and molecular features that distinguish it from the more common invasive ductal carcinoma (IDC). Mounting evidence suggests that estrogen receptor-alpha positive (ER+) ILC has a poor response to Tamoxifen (TAM), but the mechanistic drivers of this are undefined. In the current work, we comprehensively characterize the SUM44/LCCTam ILC cell model system through integrated analysis of gene expression, copy number, and mutation, with the goal of identifying actionable alterations relevant to clinical ILC that can be co-targeted along with ER to improve treatment outcomes. We show that TAM has several distinct effects on the transcriptome of LCCTam cells, that this resistant cell model has acquired copy number alterations and mutations that impinge on MAPK and metabotropic glutamate receptor (GRM/mGluR) signaling networks, and that pharmacological inhibition of either improves or restores the growth-inhibitory actions of endocrine therapy.

ERRgamma mediates tamoxifen resistance in novel models of invasive lobular breast cancer.

One-third of all estrogen receptor (ER)-positive breast tumors treated with endocrine therapy fail to respond, and the remainder is likely to relapse in the future. Almost all data on endocrine resistance has been obtained in models of invasive ductal carcinoma (IDC). However, invasive lobular carcinomas (ILC) comprise up to 15% of newly diagnosed invasive breast cancers each year and, whereas the incidence of IDC has remained relatively constant during the last 20 years, the prevalence of ILC continues to increase among postmenopausal women. We report a new model of Tamoxifen (TAM)-resistant invasive lobular breast carcinoma cells that provides novel insights into the molecular mechanisms of endocrine resistance. SUM44 cells express ER and are sensitive to the growth inhibitory effects of antiestrogens. Selection for resistance to 4-hydroxytamoxifen led to the development of the SUM44/LCCTam cell line, which exhibits decreased expression of ERalpha and increased expression of the estrogen-related receptor gamma (ERRgamma). Knockdown of ERRgamma in SUM44/LCCTam cells by siRNA restores TAM sensitivity, and overexpression of ERRgamma blocks the growth-inhibitory effects of TAM in SUM44 and MDA-MB-134 VI lobular breast cancer cells. ERRgamma-driven transcription is also increased in SUM44/LCCTam, and inhibition of activator protein 1 (AP1) can restore or enhance TAM sensitivity. These data support a role for ERRgamma/AP1 signaling in the development of TAM resistance and suggest that expression of ERRgamma may be a marker of poor TAM response.

Human X-box binding protein-1 confers both estrogen independence and antiestrogen resistance in breast cancer cell lines.

Human X-box binding protein-1 (XBP1) is an alternatively spliced transcription factor that participates in the unfolded protein response (UPR), a stress-signaling pathway that allows cells to survive the accumulation of unfolded proteins in the endoplasmic reticulum lumen. We have previously demonstrated that XBP1 expression is increased in antiestrogen-resistant breast cancer cell lines and is coexpressed with estrogen receptor alpha (ER) in breast tumors. The purpose of this study is to investigate the role of XBP1 and the UPR in estrogen and antiestrogen responsiveness in breast cancer. Overexpression of spliced XBP1 [XBP1(S)] in ER-positive breast cancer cells leads to estrogen-independent growth and reduced sensitivity to growth inhibition induced by the antiestrogens Tamoxifen and Faslodex in a manner independent of functional p53. Data from gene expression microarray analyses imply that XBP1(S) acts through regulation of the expression of ER, the antiapoptotic gene BCL2, and several other genes associated with control of the cell cycle and apoptosis. Testing this hypothesis, we show that overexpression of XBP1(S) prevents cell cycle arrest and antiestrogen-induced cell death through the mitochondrial apoptotic pathway. XBP1 and/or the UPR may be a useful molecular target for the development of novel predictive and therapeutic strategies in breast cancer.

Improved diagnostics using polarization imaging and artificial neural networks.

In recent years, there has been an increasing interest in studying the propagation of polarized light in biological cells and tissues. This paper presents a novel approach to cell or tissue imaging using a full Stokes imaging system with advanced polarization image analysis algorithms for improved diagnostics. The key component of the Stokes imaging system is the electrically tunable retarder, enabling high-speed operation of the system to acquire four intensity images sequentially. From the acquired intensity images, four Stokes vector images can be computed to obtain complete polarization information. Polarization image analysis algorithms are then developed to analyze Stokes polarization images for cell or tissue classification. Specifically, wavelet transforms are first applied to the Stokes components for initial feature analysis and extraction. Artificial neural networks (ANNs) are then used to extract diagnostic features for improved classification and prediction. In this study, phantom experiments have been conducted using a prototyped Stokes polarization imaging device. In particular, several types of phantoms, consisting of polystyrene latex spheres in various diameters, were prepared to simulate different conditions of epidermal layer of skin. The experimental results from phantom studies and a plant cell study show that the classification performance using Stokes images is significantly improved over that using the intensity image only.