scholarly journals Association of tamoxifen resistance and lipid reprogramming in breast cancer

2018 ◽  
Author(s):  
Susanne Hultsch ◽  
Matti Kankainen ◽  
Lassi Paavolainen ◽  
Ruusu-Maaria Kovanen ◽  
Elina Ikonen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cell Lines ◽  
Expression Patterns ◽  
Tamoxifen Resistance ◽  
Tamoxifen Treatment ◽  
Common Mechanism ◽  
Gene Expression Patterns ◽  
Er Positive ◽  
Tamoxifen Resistant

AbstractBackgroundTamoxifen treatment of estrogen receptor (ER)-positive breast cancer reduces mortality by 31%. However, over half of advanced ER-positive breast cancers are intrinsically resistant to tamoxifen and about 40% will acquire the resistance during the treatment.MethodsIn order to explore mechanisms underlying endocrine therapy resistance in breast cancer and to identify new therapeutic opportunities, we created tamoxifen-resistant breast cancer cell lines that represent the luminal A or the luminal B. Gene expression patterns revealed by RNA-sequencing in seven tamoxifen-resistant variants were compared with their isogenic parental cells. We further examined those transcriptomic alterations in a publicly available patient cohort.ResultsWe show that tamoxifen resistance cannot simply be explained by altered expression of individual genes, common mechanism across all resistant variants, or the appearance of new fusion genes. Instead, the resistant cell lines shared altered gene expression patterns associated with cell cycle, protein modification and metabolism, especially with the cholesterol pathway. In the tamoxifen-resistant T-47D cell variants we observed a striking increase of neutral lipids in lipid droplets as well as an accumulation of free cholesterol in the lysosomes. Tamoxifen-resistant cells were also less prone to lysosomal membrane permeabilization (LMP) and not vulnerable to compounds targeting the lipid metabolism. However, the cells were sensitive to disulfiram, LCS-1, and dasatinib.ConclusionAltogether, our findings highlight a major role of LMP prevention in tamoxifen resistance, and suggest novel drug vulnerabilities associated with this phenotype.

scholarly journals NR4A1 Regulates Tamoxifen Resistance by Suppressing ERK Signaling in ER-Positive Breast Cancer

Cells ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1633
Author(s):  
Yu Cheon Kim ◽  
Clara Yuri Kim ◽  
Ji Hoon Oh ◽  
Myoung Hee Kim
Keyword(s):  
Breast Cancer ◽  
Tamoxifen Resistance ◽  
Erk Signaling ◽  
Tamoxifen Treatment ◽  
Loss Of Function ◽  
Mcf7 Cells ◽  
Er Positive ◽  
Tamoxifen Resistant ◽  
Positive Breast Cancer

Endocrine therapy is used to treat estrogen receptor (ER)-positive breast cancer. Tamoxifen is effective against this cancer subtype. Nonetheless, approximately 30% of patients treated with tamoxifen acquire resistance, resulting in therapeutic challenges. NR4A1 plays key roles in processes associated with carcinogenesis, apoptosis, DNA repair, proliferation, and inflammation. However, the role of NR4A1 in tamoxifen-resistant ER-positive breast cancer has not yet been elucidated. Here, we propose that NR4A1 is a promising target to overcome tamoxifen resistance. NR4A1 gene expression was downregulated in tamoxifen-resistant MCF7 (TamR) cells compared to that in MCF7 cells. Kaplan-Meier plots were used to identify high NR4A1 expression correlated with increased survival rates in patients with ER-positive breast cancer following tamoxifen treatment. Gain and loss of function experiments showed that NR4A1 restores sensitivity to tamoxifen by regulating cell proliferation, migration, invasion, and apoptosis. NR4A1 localized to the cytoplasm enhanced the expression of apoptotic factors. In silico and in vitro analyses revealed that NR4A1 enhanced responsiveness to tamoxifen by suppressing ERK signaling in ER-positive breast cancer, suggesting that the NR4A1/ERK signaling axis modulates tamoxifen resistance. These results indicate that NR4A1 could be a potential therapeutic target to overcome tamoxifen resistance in ER-positive breast cancer.

scholarly journals YAP, CTGF, and Cyr61 are overexpressed in tamoxifen-resistant breast cancer and induce transcriptional repression of ERα

2021 ◽  
Author(s):  
Hyungjoo Kim ◽  
Seogho Son ◽  
Yunhyo Ko ◽  
Jeong Eon Lee ◽  
Sangmin Kim ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Transcriptional Repression ◽  
Estrogen Receptor Alpha ◽  
Tamoxifen Resistance ◽  
Tissue Growth ◽  
Tamoxifen Treatment ◽  
Transcriptional Level ◽  
Er Positive ◽  
Tamoxifen Resistant ◽  
Positive Breast Cancer

About 70% of breast cancer overexpresses estrogen receptor alpha (ERα). Tamoxifen, a competitive inhibitor of estrogen that binds to ER, has been widely used as a treatment for ER-positive breast cancer. However, 20-30% of breast cancer is resistant to tamoxifen treatment. The mechanisms underlying tamoxifen resistance remains elusive. We found that Yes-associated protein (YAP), connective tissue growth factor (CTGF), and cysteine-rich angiogenic inducer 61 (Cyr61) are overexpressed, while ERα is downregulated in tamoxifen-resistant breast cancer. Inhibition of YAP, CTGF, and Cyr61 restored ERα and increased sensitivity to tamoxifen. Overexpression of YAP, CTGF, and Cyr61 led to downregulation of ERα and conferred resistance to tamoxifen in ER-positive breast cancer cells. Mechanistically, CTGF and Cyr61 downregulated ERα expression at the transcriptional level by directly binding to the regulatory regions of ERα, leading to increased tamoxifen resistance. Also, CTGF induced Glut3 expression, leading to increased glycolysis, which enhanced cell proliferation and migration in tamoxifen-resistant cells. Together, these results demonstrate a novel role of YAP, CTGF, and Cyr61 in tamoxifen resistance and provide a molecular basis for their function in tamoxifen-resistant breast cancer.

scholarly journals Effects of Herceptin treatment on global gene expression patterns in HER2-amplified and nonamplified breast cancer cell lines

Oncogene ◽  
2003 ◽  
Vol 23 (4) ◽  
pp. 1010-1013 ◽  
Author(s):  
Päivikki Kauraniemi ◽  
Sampsa Hautaniemi ◽  
Reija Autio ◽  
Jaakko Astola ◽  
Outi Monni ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cell Lines ◽  
Cancer Cell ◽  
Breast Cancer Cell ◽  
Expression Patterns ◽  
Global Gene Expression ◽  
Cancer Cell Lines ◽  
Breast Cancer Cell Lines ◽  
Gene Expression Patterns

NTP-mediated changes of gene expression patterns in human cell lines

2013 ◽  
Author(s):  
Lena Bundscherer ◽  
Anke Schmidt ◽  
Annemarie Barton ◽  
Sybille Hasse ◽  
Kristian Wende ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Lines ◽  
Human Cell ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Human Cell Lines

scholarly journals Unique Gene Expression Patterns in Human T-cell Lines Generated from Multiple Sclerosis Patients by Stimulation with a Synthetic MOG Peptide

2005 ◽  
Vol 12 (3) ◽  
pp. 203-209 ◽  
Author(s):  
Mathilda Mandel ◽  
Michael Gurevich ◽  
Gad Lavie ◽  
Irun R. Cohen ◽  
Anat Achiron
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
T Cell ◽  
Cell Lines ◽  
Healthy Subjects ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Gene Expression Patterns ◽  
T Cell Lines ◽  
Myelin Antigens

Multiple sclerosis (MS) is an autoimmune disease where T-cells activated against myelin antigens are involved in myelin destruction. Yet, healthy subjects also harbor T-cells responsive to myelin antigens, suggesting that MS patient-derived autoimmune T-cells might bear functional differences from T-cells derived from healthy individuals. We addressed this issue by analyzing gene expression patterns of myelin oligodendrocytic glycoprotein (MOG) responsive T-cell lines generated from MS patients and healthy subjects. We identified 150 transcripts that were differentially expressed between MS patients and healthy controls. The most informative 43 genes exhibited >1.5-fold change in expression level. Eighteen genes were up-regulated including BCL2, lifeguard, IGFBP3 and VEGF. Twenty five genes were down-regulated, including apoptotic activators like TNF and heat shock protein genes. This gene expression pattern was unique to MOG specific T-cell lines and was not expressed in T-cell lines reactive to tetanus toxin (TTX). Our results indicate that activation in MS that promotes T-cell survival and expansion, has its own state and that the unique gene expression pattern that characterize autoreactive T-cells in MS represent a constellation of factors in which the chronicity, timing and accumulation of damage make the difference between health and disease.

Predicting features of breast cancer with gene expression patterns

2007 ◽  
Vol 108 (2) ◽  
pp. 191-201 ◽  
Author(s):  
Xuesong Lu ◽  
Xin Lu ◽  
Zhigang C. Wang ◽  
J. Dirk Iglehart ◽  
Xuegong Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Expression Patterns ◽  
Gene Expression Patterns

scholarly journals Poly-ADP-Ribosylation of Estrogen Receptor-Alpha by PARP1 Mediates Antiestrogen Resistance in Human Breast Cancer Cells

Cancers ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 43 ◽  
Author(s):  
Nicholas Pulliam ◽  
Jessica Tang ◽  
Weini Wang ◽  
Fang Fang ◽  
Riddhi Sood ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Oxidative Stress ◽  
Estrogen Receptor ◽  
Cancer Cells ◽  
Breast Cancer Cells ◽  
Target Genes ◽  
Tamoxifen Resistance ◽  
Tamoxifen Treatment ◽  
Dependent Manner ◽  
Tamoxifen Resistant

Therapeutic targeting of estrogen receptor-α (ERα) by the anti-estrogen tamoxifen is standard of care for premenopausal breast cancer patients and remains a key component of treatment strategies for postmenopausal patients. While tamoxifen significantly increases overall survival, tamoxifen resistance remains a major limitation despite continued expression of ERα in resistant tumors. Previous reports have described increased oxidative stress in tamoxifen resistant versus sensitive breast cancer and a role for PARP1 in mediating oxidative damage repair. We hypothesized that PARP1 activity mediated tamoxifen resistance in ERα-positive breast cancer and that combining the antiestrogen tamoxifen with a PARP1 inhibitor (PARPi) would sensitize tamoxifen resistant cells to tamoxifen therapy. In tamoxifen-resistant vs. -sensitive breast cancer cells, oxidative stress and PARP1 overexpression were increased. Furthermore, differential PARylation of ERα was observed in tamoxifen-resistant versus -sensitive cells, and ERα PARylation was increased by tamoxifen treatment. Loss of ERα PARylation following treatment with a PARP inhibitor (talazoparib) augmented tamoxifen sensitivity and decreased localization of both ERα and PARP1 to ERα-target genes. Co-administration of talazoparib plus tamoxifen increased DNA damage accumulation and decreased cell survival in a dose-dependent manner. The ability of PARPi to overcome tamoxifen resistance was dependent on ERα, as lack of ERα-mediated estrogen signaling expression and showed no response to tamoxifen-PARPi treatment. These results correlate ERα PARylation with tamoxifen resistance and indicate a novel mechanism-based approach to overcome tamoxifen resistance in ER+ breast cancer.

scholarly journals SIGN: similarity identification in gene expression

2019 ◽  
Vol 35 (22) ◽  
pp. 4830-4833 ◽  
Author(s):  
Seyed Ali Madani Tonekaboni ◽  
Venkata Satya Kumar Manem ◽  
Nehme El-Hachem ◽  
Benjamin Haibe-Kains
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Open Source ◽  
Supervised Learning ◽  
Cancer Patients ◽  
Biomedical Research ◽  
Expression Patterns ◽  
R Package ◽  
Gene Expression Patterns ◽  
Learning Schemes

Abstract Motivation High-throughput molecular profiles of human cells have been used in predictive computational approaches for stratification of healthy and malignant phenotypes and identification of their biological states. In this regard, pathway activities have been used as biological features in unsupervised and supervised learning schemes. Results We developed SIGN (Similarity Identification in Gene expressioN), a flexible open-source R package facilitating the use of pathway activities and their expression patterns to identify similarities between biological samples. We defined a new measure, the transcriptional similarity coefficient, which captures similarity of gene expression patterns, instead of quantifying overall activity, in biological pathways between the samples. To demonstrate the utility of SIGN in biomedical research, we establish that SIGN discriminates subtypes of breast tumors and patients with good or poor overall survival. SIGN outperforms the best models in DREAM challenge in predicting survival of breast cancer patients using the data from the Molecular Taxonomy of Breast Cancer International Consortium. In summary, SIGN can be used as a new tool for interrogating pathway activity and gene expression patterns in unsupervised and supervised learning schemes to improve prognostic risk estimation for cancer patients by the biomedical research community. Availability and implementation An open-source R package is available (https://cran.r-project.org/web/packages/SIGN/).

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