Estrogen-Regulated Genes Predict Survival in Hormone Receptor–Positive Breast Cancers

2006 ◽  
Vol 24 (11) ◽  
pp. 1656-1664 ◽  
Author(s):  
Daniel S. Oh ◽  
Melissa A. Troester ◽  
Jerry Usary ◽  
Zhiyuan Hu ◽  
Xiaping He ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Published Data ◽  
Data Sets ◽  
Breast Cancers ◽  
Outcome Predictor ◽  
Training Set ◽  
Hormone Receptor Positive ◽  
Prognosis Group ◽  
Mcf 7

Purpose The prognosis of a patient with estrogen receptor (ER) and/or progesterone receptor (PR) –positive breast cancer can be highly variable. Therefore, we developed a gene expression–based outcome predictor for ER+ and/or PR+ (ie, luminal) breast cancer patients using biologic differences among these tumors. Materials and Methods The ER+ MCF-7 breast cancer cell line was treated with 17β-estradiol to identify estrogen-regulated genes. These genes were used to develop an outcome predictor on a training set of 65 luminal epithelial primary breast carcinomas. The outcome predictor was then validated on three independent published data sets. Results The estrogen-induced gene set identified in MCF-7 cells was used to hierarchically cluster a 65 tumor training set into two groups, which showed significant differences in survival (P = .0004). Supervised analyses identified 822 genes that optimally defined these two groups, with the poor-prognosis group IIE showing high expression of cell proliferation and antiapoptosis genes. The good prognosis group IE showed high expression of estrogen- and GATA3-regulated genes. Mean expression profiles (ie, centroids) created for each group were applied to ER+ and/or PR+ tumors from three published data sets. For all data sets, Kaplan-Meier survival analyses showed significant differences in relapse-free and overall survival between group IE and IIE tumors. Multivariate Cox analysis of the largest test data set showed that this predictor added significant prognostic information independent of standard clinical predictors and other gene expression–based predictors. Conclusion This study provides new biologic information concerning differences within hormone receptor–positive breast cancers and a means of predicting long-term outcomes in tamoxifen-treated patients.

scholarly journals Polycaprolactone nanofibers as an adjuvant strategy for Tamoxifen release and their cytotoxicity on breast cancer cells

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12124
Author(s):  
Ana D. Pinzón-García ◽  
Ruben Sinisterra ◽  
Maria Cortes ◽  
Fredy Mesa ◽  
Sandra Ramírez-Clavijo
Keyword(s):  
Breast Cancer ◽  
Drug Loading ◽  
Cancer Cell Line ◽  
In Vitro Study ◽  
Local Drug Delivery ◽  
Breast Cancers ◽  
Hormone Receptor Positive ◽  
Tamoxifen Citrate ◽  
Mcf 7

Breast cancer is the second leading cause of death in women, and tamoxifen citrate (TMX) is accepted widely for the treatment of hormone receptor–positive breast cancers. Several local drug-delivery systems, including nanofibers, have been developed for antitumor treatment. Nanofibers are biomaterials that mimic the natural extracellular matrix, and they have been used as controlled release devices because they enable highly efficient drug loading. The purpose of the present study was to develop polycaprolactone (PCL) nanofibers incorporating TMX for use in the treatment of breast tumors. Pristine PCL and PCL-TMX nanofibers were produced by electrospinning and characterized physiochemically using different techniques. In addition, an in vitro study of TMX release from the nanofibers was performed. The PCL-TMX nanofibers showed sustained TMX release up to 14 h, releasing 100% of the TMX. The Resazurin reduction assay was used to evaluate the TMX cytotoxicity on MCF-7 breast cancer cell line and PBMCs human. The PCL-TMX nanofiber was cytotoxic toPBMCs and MCF-7. Based on these results, the PCL-TMX nanofibers developed have potential as an alternative for local chronic TMX use for breast cancer treatment, however tissue tests must be done.

scholarly journals Prediction of PIK3CA mutations from cancer gene expression data

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0241514
Author(s):  
Jun Kang ◽  
Ahwon Lee ◽  
Youn Soo Lee
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Expression Data ◽  
Breast Cancers ◽  
Training Set ◽  
Cancer Dataset ◽  
Test Set ◽  
Pik3ca Mutations ◽  
Tensin Homolog ◽  
Hormone Receptor Positive

Breast cancers with PIK3CA mutations can be treated with PIK3CA inhibitors in hormone receptor-positive HER2 negative subtypes. We applied a supervised elastic net penalized logistic regression model to predict PIK3CA mutations from gene expression data. This regression approach was applied to predict modeling using the TCGA pan-cancer dataset. Approximately 10,000 cases were available for PIK3CA mutation and mRNA expression data. In 10-fold cross-validation, the model with λ = 0.01 and α = 1.0 (ridge regression) showed the best performance, in terms of area under the receiver operating characteristic (AUROC). The final model was developed with selected hyper-parameters using the entire training set. The training set AUROC was 0.93, and the test set AUROC was 0.84. The area under the precision-recall (AUPR) of the training set was 0.66, and the test set AUPR was 0.39. Cancer types were the most important predictors. Both insulin like growth factor 1 receptor (IGF1R) and the phosphatase and tensin homolog (PTEN) were the most significant genes in gene expression predictors. Our study suggests that predicting genomic alterations using gene expression data is possible, with good outcomes.

scholarly journals Challenges in Adjuvant Therapy for Premenopausal Women Diagnosed With Luminal Breast Cancers

2021 ◽  
pp. 1-15
Author(s):  
Ines Vaz-Luis ◽  
Prudence A. Francis ◽  
Antonio Di Meglio ◽  
Vered Stearns
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Side Effects ◽  
Endocrine Therapy ◽  
Hormone Receptor ◽  
Premenopausal Women ◽  
Adjuvant Endocrine Therapy ◽  
Breast Cancers ◽  
Abrupt Decrease ◽  
Hormone Receptor Positive

More than 90% of women with newly diagnosed breast cancer present with stage I to III disease and, with optimal multidisciplinary therapy, are likely to survive their disease. Of these patients, 70% are hormone receptor–positive and candidates for adjuvant endocrine therapy. The adoption of cumulatively better adjuvant treatments contributed to improved outcomes in patients with hormone receptor–positive, early-stage breast cancer. Premenopausal women with hormone receptor–positive breast cancer often present with complex disease and have inferior survival outcomes compared with their postmenopausal counterparts. Risk stratification strategies, including classic clinicopathologic features and newer gene expression assays, can assist in treatment decisions, including adjuvant chemotherapy use and type or duration of endocrine therapy. Gene expression assays may help identify patients who can safely forgo chemotherapy, although to a lesser extent among premenopausal patients, in whom they may play a role only in node-negative disease. Patients at lower risk of recurrence can be adequately treated with tamoxifen alone, whereas higher-risk patients benefit from ovarian function suppression with tamoxifen or an aromatase inhibitor. The role of adding newer therapies such as CDK4/6 inhibitors to adjuvant endocrine therapy is not yet clear. Breast cancer treatments are associated with several side effects, with major impact on patients’ quality of life and treatment adherence, particularly in premenopausal women for whom these side effects may be more prominent as the result of the abrupt decrease in estrogen concentrations. Personalized management of treatment side effects, addressing patients' concerns, and health promotion should be an integral part of the care of premenopausal women diagnosed with luminal breast cancers.

scholarly journals Similarities and Differences in Gene Expression Networks Between the Breast Cancer Cell Line Michigan Cancer Foundation-7 and Invasive Human Breast Cancer Tissues

2021 ◽  
Vol 4 ◽  
Author(s):  
Vy Tran ◽  
Robert Kim ◽  
Mikhail Maertens ◽  
Thomas Hartung ◽  
Alexandra Maertens
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cell Line ◽  
Human Breast Cancer ◽  
Data Sets ◽  
Human Breast ◽  
Data Set ◽  
Cancer Tissues ◽  
Mcf 7

Failure to adequately characterize cell lines, and understand the differences between in vitro and in vivo biology, can have serious consequences on the translatability of in vitro scientific studies to human clinical trials. This project focuses on the Michigan Cancer Foundation-7 (MCF-7) cells, a human breast adenocarcinoma cell line that is commonly used for in vitro cancer research, with over 42,000 publications in PubMed. In this study, we explore the key similarities and differences in gene expression networks of MCF-7 cell lines compared to human breast cancer tissues. We used two MCF-7 data sets, one data set collected by ARCHS4 including 1032 samples and one data set from Gene Expression Omnibus GSE50705 with 88 estradiol-treated MCF-7 samples. The human breast invasive ductal carcinoma (BRCA) data set came from The Cancer Genome Atlas, including 1212 breast tissue samples. Weighted Gene Correlation Network Analysis (WGCNA) and functional annotations of the data showed that MCF-7 cells and human breast tissues have only minimal similarity in biological processes, although some fundamental functions, such as cell cycle, are conserved. Scaled connectivity—a network topology metric—also showed drastic differences in the behavior of genes between MCF-7 and BRCA data sets. Finally, we used canSAR to compute ligand-based druggability scores of genes in the data sets, and our results suggested that using MCF-7 to study breast cancer may lead to missing important gene targets. Our comparison of the networks of MCF-7 and human breast cancer highlights the nuances of using MCF-7 to study human breast cancer and can contribute to better experimental design and result interpretation of study involving this cell line.

scholarly journals SUN-735 Functional Analysis of Testis-Specific Noncoding Genes in Estrogen-Dependent Transcription

2020 ◽  
Vol 4 (Supplement_1) ◽  
Author(s):  
Ramesh Choudhari ◽  
Barbara Yang ◽  
Enrique Ivan Ramos ◽  
Mina Zilaie ◽  
Laura A Sanchez-Michael ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Cells ◽  
Breast Cancer Cells ◽  
Therapeutic Potential ◽  
Critical Role ◽  
Genomic Analysis ◽  
Breast Cancers ◽  
Breast Cancer Patients ◽  
Mcf 7

Abstract Emerging studies have shown that germ cell (GC)-specific genes play critical roles in several cancers. The expression of these genes is tightly regulated and restricted to testis; however, many of them escape regulation and become aberrantly expressed in tumors. Interestingly, our genomic analysis suggests that several of these genes are long noncoding RNAs (lncRNAs) and are located at regions previously considered to be gene deserts in the human genome. In this regard, we used an integrated genomic approach to identify GC-lncRNA genes that are overexpressed in breast cancer. Further, by incorporating gene expression analysis from RNA-seq data from MCF-7 and T47D breast cancer cells, we generated a comprehensive list of estrogen-regulated GC-lncRNA genes. We hypothesize that GC-lncRNA genes regulate estrogen-dependent signaling in breast cancer. The selected genes: (a) CAERRC (Chromatin Associated Estrogen-Regulated RNA in Cancer, (b) LncRNA568, (c) LncRNA16 are primate-specific, and exclusively expressed in testis. All of them are regulated by estrogen, and their expression predicts poor outcome in ERα+ breast cancer patients. They have now been fully annotated (transcription start and stop site, 5’ cap, polyA tail, and exon/intron structure), and cloned. Further, we have created gene-specific KO MCF-7 cell lines using CRISPR to study their molecular roles. Our data suggest that these genes regulate estrogen-dependent gene expression and tumor growth in breast cancer cells. Genome-wide analysis of ERα binding and gene expression data indicate that they play a critical role in the estrogen-dependent transcription. Collectively, our results suggest that GC-genes, including CAERRC, LncRNA568, and LncRNA16, are excellent targets with prognostic and therapeutic potential in ER+ breast cancers.

The Expression of Dopamine Receptors Gene and their Potential Role in Targeting Breast Cancer Cells with Selective Agonist and Antagonist Drugs. Could it be the Novel Insight to Therapy?

2019 ◽  
Vol 16 (2) ◽  
pp. 184-197 ◽  
Author(s):  
Hossein Bakhtou ◽  
Asiie Olfatbakhsh ◽  
Abdolkhaegh Deezagi ◽  
Ghasem Ahangari
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Cells ◽  
Dopamine Receptors ◽  
Breast Cancer Cells ◽  
D2 Receptors ◽  
Healthy Individuals ◽  
Agonist And Antagonist ◽  
The Mean ◽  
Mcf 7

Background:Breast cancer is one of the common causes of mortality for women in Iran and other parts of the world. The substantial increasing rate of breast cancer in both developed and developing countries warns the scientists to provide more preventive steps and therapeutic measures. This study is conducted to investigate the impact of neurotransmitters (e.g., Dopamine) through their receptors and the importance of cancers via damaging immune system. It also evaluates dopamine receptors gene expression in the women with breast cancer at stages II or III and dopamine receptor D2 (DRD2) related agonist and antagonist drug effects on human breast cancer cells, including MCF-7 and SKBR-3.Methods:The patients were categorized into two groups: 30 native patients who were diagnosed with breast cancer at stages II and III, with the mean age of 44.6 years and they were reported to have the experience of a chronic stress or unpleasant life event. The second group included 30 individuals with the mean age of 39 years as the control group. In order to determine the RNA concentration in all samples, the RNA samples were extracted and cDNA was synthesized. The MCF-7 cells and SKBR-3 cells were treated with dopamine receptors agonists and antagonists. The MTT test was conducted to identify oxidative and reductive enzymes and to specify appropriate dosage at four concentrations of dopamine and Cabergoline on MCF-7 and SKBR-3 cells. Immunofluorescence staining was done by the use of a mixed dye containing acridine orange and ethidiume bromide on account of differentiating between apoptotic and necrotic cells. Flow cytometry assay was an applied method to differentiate necrotic from apoptotic cells.Results:Sixty seven and thirty three percent of the patients were related to stages II and III, respectively. About sixty three percent of the patients expressed ER, while fifty seven percent expressed PR. Thirty seven percent of the patients were identified as HER-2 positive. All types of D2-receptors were expressed in PBMC of patients with breast cancer and healthy individuals. The expression of the whole dopamine receptor subtypes (DRD2-DRD4) was carried out on MCF-7 cell line. The results of RT-PCR confirmed the expression of DRD2 on SKBR-3 cells, whereas the other types of D2- receptors did not have an expression. The remarkable differences in gene expression rates between patients and healthy individuals were revealed in the result of the Real-time PCR analysis. The over expression in DRD2 and DRD4 genes of PBMCs was observed in the patients with breast cancer at stages II and III. The great amount of apoptosis and necrosis occurred after the treatment of MCF-7 cells by Cabergoline from 25 to 100 µmolL-1 concentrations.Conclusion:This study revealed the features of dopamine receptors associated with apoptosis induction in breast cancer cells. Moreover, the use of D2-agonist based on dopamine receptors expression in various breast tumoral cells could be promising as a new insight of complementary therapy in breast cancer.

scholarly journals Immune microenvironment and intrinsic subtyping in hormone receptor-positive/HER2-negative breast cancer

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Gaia Griguolo ◽  
Maria Vittoria Dieci ◽  
Laia Paré ◽  
Federica Miglietta ◽  
Daniele Giulio Generali ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Gene Expression Data ◽  
Hormone Receptor ◽  
Tumor Biology ◽  
Expression Data ◽  
Immune Microenvironment ◽  
Immune Infiltrate ◽  
Hormone Receptor Positive ◽  
Her2 Breast Cancer

AbstractLittle is known regarding the interaction between immune microenvironment and tumor biology in hormone receptor (HR)+/HER2− breast cancer (BC). We here assess pretreatment gene-expression data from 66 HR+/HER2− early BCs from the LETLOB trial and show that non-luminal tumors (HER2-enriched, Basal-like) present higher tumor-infiltrating lymphocyte levels than luminal tumors. Moreover, significant differences in immune infiltrate composition, assessed by CIBERSORT, were observed: non-luminal tumors showed a more proinflammatory antitumor immune infiltrate composition than luminal ones.

scholarly journals Role of the NUDT Enzymes in Breast Cancer

2021 ◽  
Vol 22 (5) ◽  
pp. 2267
Author(s):  
Roni H. G. Wright ◽  
Miguel Beato
Keyword(s):  
Breast Cancer ◽  
Signaling Pathways ◽  
Cancer Progression ◽  
Breast Cancers ◽  
Metastatic Colonization ◽  
Hormone Receptor Positive ◽  
Aggressive Cancer ◽  
Cancer Types ◽  
Metastatic Process

Despite global research efforts, breast cancer remains the leading cause of cancer death in women worldwide. The majority of these deaths are due to metastasis occurring years after the initial treatment of the primary tumor and occurs at a higher frequency in hormone receptor-positive (Estrogen and Progesterone; HR+) breast cancers. We have previously described the role of NUDT5 (Nudix-linked to moiety X-5) in HR+ breast cancer progression, specifically with regards to the growth of breast cancer stem cells (BCSCs). BCSCs are known to be the initiators of epithelial-to-mesenchyme transition (EMT), metastatic colonization, and growth. Therefore, a greater understanding of the proteins and signaling pathways involved in the metastatic process may open the door for therapeutic opportunities. In this review, we discuss the role of NUDT5 and other members of the NUDT family of enzymes in breast and other cancer types. We highlight the use of global omics data based on our recent phosphoproteomic analysis of progestin signaling pathways in breast cancer cells and how this experimental approach provides insight into novel crosstalk mechanisms for stratification and drug discovery projects aiming to treat patients with aggressive cancer.

scholarly journals Relationship Between Plasma Estradiol Levels and Estrogen-Responsive Gene Expression in Estrogen Receptor–Positive Breast Cancer in Postmenopausal Women

2010 ◽  
Vol 28 (7) ◽  
pp. 1161-1167 ◽  
Author(s):  
Anita K. Dunbier ◽  
Helen Anderson ◽  
Zara Ghazoui ◽  
Elizabeth J. Folkerd ◽  
Roger A'Hern ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Estrogen Receptor ◽  
Postmenopausal Women ◽  
Multivariable Analysis ◽  
Independent Set ◽  
Breast Cancers ◽  
Plasma Estradiol ◽  
Er Positive ◽  
Positive Breast Cancer

Purpose To determine whether plasma estradiol (E2) levels are related to gene expression in estrogen receptor (ER)–positive breast cancers in postmenopausal women. Materials and Methods Genome-wide RNA profiles were obtained from pretreatment core-cut tumor biopsies from 104 postmenopausal patients with primary ER-positive breast cancer treated with neoadjuvant anastrozole. Pretreatment plasma E2 levels were determined by highly sensitive radioimmunoassay. Genes were identified for which expression was correlated with pretreatment plasma E2 levels. Validation was performed in an independent set of 73 ER-positive breast cancers. Results The expression of many known estrogen-responsive genes and gene sets was highly significantly associated with plasma E2 levels (eg, TFF1/pS2, GREB1, PDZK1 and PGR; P < .005). Plasma E2 explained 27% of the average expression of these four average estrogen-responsive genes (ie, AvERG; r = 0.51; P < .0001), and a standardized mean of plasma E2 levels and ER transcript levels explained 37% (r, 0.61). These observations were validated in an independent set of 73 ER-positive tumors. Exploratory analysis suggested that addition of the nuclear coregulators in a multivariable analysis with ER and E2 levels might additionally improve the relationship with the AvERG. Plasma E2 and the standardized mean of E2 and ER were both significantly correlated with 2-week Ki67, a surrogate marker of clinical outcome (r = −0.179; P = .05; and r = −0.389; P = .0005, respectively). Conclusion Plasma E2 levels are significantly associated with gene expression of ER-positive breast cancers and should be considered in future genomic studies of ER-positive breast cancer. The AvERG is a new experimental tool for the study of putative estrogenic stimuli of breast cancer.

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