Project description:One-third of all ER+ breast tumors treated with endocrine therapy fail to respond, and the remainder are 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 diagnosed each year and, while 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 estrogen receptor alpha (ERα) and increased expression of the estrogen-related receptor gamma (ERRγ). Knockdown of ERRγ in SUM44/LCCTam cells by siRNA restores TAM sensitivity, and overexpression of ERRγ blocks the growth-inhibitory effects of TAM in SUM44 and MDA-MB-134 VI lobular breast cancer cells. ERRγ-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 ERRγ/AP1 signaling in the development of TAM resistance, and suggest that expression of ERRγ may be a marker of poor Tamoxifen response.
Project description:Invasive Lobular Carcinoma (ILC), a distinct subtype of breast cancer is hallmarked by E-Cadherin loss, slow proliferation, and hormone receptor positivity. Major challenges in clinical management of ILC is advanced stage at diagnosis, resistance to endocrine therapy, a cornerstone in treating ILC patients, and late recurrence. To elucidate the mechanisms underlying endocrine resistance in ILC, we have generated ILC cell lines (MDA-MB-134-VI and SUM44PE) resistant to tamoxifen, a selective estrogen receptor modulator. Our study reveals methylation mediated silencing of ASS1 and demethylation restored ASS1 expression markedly reducing IC50 for tamoxifen. Treating TAMR cell with Decitabine, a demethylating agent, or Farudodstat, a pyrimidine biosynthesis inhibitor, markedly augmented efficacy of tamoxifen. Collectively, our study unveils ASS1 downregulation as a novel mechanism underlying acquired resistance to tamoxifen in ILC and establishes a metabolic link between ASS1 and nucleic acid biosynthesis. ASS1 can be a potential biomarker and a therapeutic target in tamoxifen resistant ILC patients, warranting further investigation.
Project description: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 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. These samples form a SuperSeries with GSE12708.
Project description:Transcription profiling of human lobular and ductal invasive carcinomas vs normal breast tissue from the same patient to identify gene expression profiles of ductal and lobular carcinomas in relation to normal ductal and lobular cells
Project description:One-third of all ER+ breast tumors treated with endocrine therapy fail to respond, and the remainder are 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 diagnosed each year and, while 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 estrogen receptor alpha (ERα) and increased expression of the estrogen-related receptor gamma (ERRγ). Knockdown of ERRγ in SUM44/LCCTam cells by siRNA restores TAM sensitivity, and overexpression of ERRγ blocks the growth-inhibitory effects of TAM in SUM44 and MDA-MB-134 VI lobular breast cancer cells. ERRγ-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 ERRγ/AP1 signaling in the development of TAM resistance, and suggest that expression of ERRγ may be a marker of poor Tamoxifen response. Experiment Overall Design: Total RNA was extracted from sub-confluent T-25 cm^2 tissue culture flasks of SUM44 and LCCTam cells, then processed and arrayed. Microarray data quality was then assessed using several tools, including those recommended by Affymetrix and a series of additional QC measures. The Robust Multiple-Array Average (RMA) method was used to preprocess the raw gene expression data, as implemented in the Bioconductor project (http://bioconductor.org). We then isolated a reduced dimension dataset that included genes that exhibit â¥2 fold change, p<0.05 and genes with intensity â¥log2(10) in both SUM44 and SUM44/LCCTam groups. Data visualization before and after dimensionality reduction was facilitated by multidimensional scaling as estimated using Principal Component Analysis (PCA) and Discriminant Component Analysis (DCA), to ensure that the global structure of the data was not altered by dimensionality reduction procedures.