RNA-seq data from MCF-7 cells (breast cancer model) treated with soy extracts
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Gong P
PROVIDER: S-ECPF-GEOD-56066 | biostudies-other | 2014
REPOSITORIES: biostudies-other
Similar Datasets
Project description:The MCF-7 were infected with either control adenovirus expressing B-galactosidase (Ad) or adenovirus expressing ERB (AdERbeta) for 72 h. For knockdown of the endogenous ERa in MCF-7 cells, cells were treated with siRNA for 24h (AdERbeta+SiERalpha). Then cells were treated with Veh (0.1% EtOH), 10 nM E2 or 1 uM BEs (botanical extracts) for 24h. Duplicate samples run; treatment after knockdown included a control treatment (V), estradiol (E2) or botanical extracts; genistein (Gen), S-equol, liquiritigenin (Liq)
2014-10-24 | E-GEOD-56066 | biostudies-arrayexpress
Project description:The MCF-7 were infected with either control adenovirus expressing B-galactosidase (Ad) or adenovirus expressing ERB (AdERbeta) for 72 h. For knockdown of the endogenous ERa in MCF-7 cells, cells were treated with siRNA for 24h (AdERbeta+SiERalpha). Then cells were treated with Veh (0.1% EtOH), 10 nM E2 or 1 uM BEs (botanical extracts) for 24h.
2014-10-24 | GSE56066 | GEO
Project description:Enterolactone (EL) is a mammalian enterolignan produced in the intestine as a result of the microbial biotransformation of the dietary lignans. EL is a potential nutraceutical, with several health benefits, including anticancer and antimetastatic properties. Epidemiological data suggest a possible link between EL exposure and breast cancer risk. However, EL binds to estrogen receptor-α, produces estrogen-like effects on gene expression, and induces proliferation of MCF-7 breast cancer cells at a concentration of 10 µM. Here, we present RNA-seq data obtained from MCF-7 breast cancer cells treated with 10 µM EL for a period of 72 h, which captures the transcriptomic alterations associated with cell proliferation. The data are available from Gene Expression Omnibus (GEO, accession number GSE216876).
| S-EPMC10106490 | biostudies-literature
Project description:RNA-seq was performed on breast cancer cell lines and primary tumors RNA-seq was performed on 28 breast cancer cell lines, 42 Triple Negative Breast Cancer (TNBC) primary tumors, and 42 Estrogen Receptor Positive (ER+) and HER2 Negative Breast Cancer primary tumors, 30 uninovlved breast tissue samples that were adjacent to ER+ primary tumors, 5 breast tissue samples from reduction mammoplasty procedures performed on patients with no known cancer, and 21 uninvolved breast tissue samples that were adjacent to TNBC primary tumors.
| S-ECPF-GEOD-58135 | biostudies-other
Project description:BackgroundNowadays, many public repositories containing large microarray gene expression datasets are available. However, the problem lies in the fact that microarray technology are less powerful and accurate than more recent Next Generation Sequencing technologies, such as RNA-Seq. In any case, information from microarrays is truthful and robust, thus it can be exploited through the integration of microarray data with RNA-Seq data. Additionally, information extraction and acquisition of large number of samples in RNA-Seq still entails very high costs in terms of time and computational resources.This paper proposes a new model to find the gene signature of breast cancer cell lines through the integration of heterogeneous data from different breast cancer datasets, obtained from microarray and RNA-Seq technologies. Consequently, data integration is expected to provide a more robust statistical significance to the results obtained. Finally, a classification method is proposed in order to test the robustness of the Differentially Expressed Genes when unseen data is presented for diagnosis.ResultsThe proposed data integration allows analyzing gene expression samples coming from different technologies. The most significant genes of the whole integrated data were obtained through the intersection of the three gene sets, corresponding to the identified expressed genes within the microarray data itself, within the RNA-Seq data itself, and within the integrated data from both technologies. This intersection reveals 98 possible technology-independent biomarkers. Two different heterogeneous datasets were distinguished for the classification tasks: a training dataset for gene expression identification and classifier validation, and a test dataset with unseen data for testing the classifier. Both of them achieved great classification accuracies, therefore confirming the validity of the obtained set of genes as possible biomarkers for breast cancer. Through a feature selection process, a final small subset made up by six genes was considered for breast cancer diagnosis.ConclusionsThis work proposes a novel data integration stage in the traditional gene expression analysis pipeline through the combination of heterogeneous data from microarrays and RNA-Seq technologies. Available samples have been successfully classified using a subset of six genes obtained by a feature selection method. Consequently, a new classification and diagnosis tool was built and its performance was validated using previously unseen samples.
| S-EPMC5697344 | biostudies-literature
Project description:To inquire the a possible mechanism for heparin treatment improved cancer survival, three type of heparins: one standard heparin (unfractionated heparin (UFH), and two of low molecular weight heparin (LMWH) Fragmin and Clexane were used to treat cell for 24 hours. Total RNA was used for cDNA Microarray assay. Untreated cells were used as controls. Cell were treated by three type of heparins one standard heparin (unfractionated heparin (UFH), and two of low molecular weight heparin (LMWH) Fragmin and Clexane (40 IU/ml for each) were used to treat cell for 24 hours. Triplicate samples were prepared.
| S-ECPF-GEOD-26537 | biostudies-other
Project description: Not available
| S-BSST1200 | biostudies-other
Project description:Multidrug resistance (MDR) is a major problem in the treatment of breast cancer. In the present study, next-generation sequencing technology was employed to identify differentially expressed genes in MCF‑7/MDR cells and MCF‑7 cells, and aimed to investigate the underlying molecular mechanisms of MDR in breast cancer. Differentially expressed genes between MCF‑7/MDR and MCF‑7 cells were selected using software; a total of 2085 genes were screened as differentially expressed in MCF‑7/MDR cells. Furthermore, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the DAVID database. Finally, a protein‑protein interaction network was constructed and the hub genes in the network were analyzed using the STRING database. GO annotation demonstrated that the differentially expressed genes were enriched in various biological processes, including 'regulation of cell differentiation', 'cell development', 'neuron development', 'movement of cell or subcellular component' and 'cell morphogenesis involved in neuron differentiation'. Cellular component analysis by GO revealed that differentially expressed genes were enriched in 'plasma membrane region' and 'extracellular matrix' terms. Furthermore, KEGG analysis demonstrated that the target genes were enriched in various pathways, including 'cell adhesion molecules (CAMs)', 'calcium signaling pathway', 'tight junction', 'Wnt signaling pathway' and 'pathways in cancer' terms. A protein‑protein interaction network demonstrated that certain hub genes, including cyclin D1, nitric oxide synthase 3 (NOS3), NOTCH3, brain‑derived neurotrophic factor (BDNF), paired box 6, neuropeptide Y, phospholipase C β (PLCB) 4, PLCB2 and actin α cardiac muscle 1, may be associated with MDR in breast cancer. Subsequently, RT‑qPCR confirmed that the expression of these 9 hub genes was higher in MCF‑7/MDR cells compared with MCF‑7 cells, consistent with the RNA‑sequencing analysis. Additionally, a Cell Counting Kit‑8 assay demonstrated that specific inhibitors of NOS3 and BDNF/neurotrophic receptor tyrosine kinase, type 2 signaling reduced the IC50 of MCF‑7/MDR cells in response to various anticancer drugs, including adriamycin, cisplatin and 5‑fluorouracil. The results of the present study provide novel insights into the mechanism underlying MDR in MCF‑7 cells and may identify novel targets for the treatment of breast cancer.
| S-EPMC5928598 | biostudies-literature
Project description:By measuring messenger RNA levels for all genes in a sample, RNA-seq provides an attractive option to characterize the global changes in transcription. RNA-seq is becoming the widely used platform for gene expression profiling. However, real transcription signals in the RNA-seq data are confounded with measurement and sequencing errors and other random biological/technical variation. To extract biologically useful transcription process from the RNA-seq data, we propose to use the second ODE for modeling the RNA-seq data. We use differential principal analysis to develop statistical methods for estimation of location-varying coefficients of the ODE. We validate the accuracy of the ODE model to fit the RNA-seq data by prediction analysis and 5-fold cross validation. To further evaluate the performance of the ODE model for RNA-seq data analysis, we used the location-varying coefficients of the second ODE as features to classify the normal and tumor cells. We demonstrate that even using the ODE model for single gene we can achieve high classification accuracy. We also conduct response analysis to investigate how the transcription process responds to the perturbation of the external signals and identify dozens of genes that are related to cancer.
| S-EPMC4539434 | biostudies-literature
Project description:Resistance to tamoxifen (Tam), a widely used antagonist of the estrogen receptor (ER), is a common obstacle to successful breast cancer treatment. While adjuvant therapy with Tam has been shown to significantly decrease the rate of disease recurrence and mortality, recurrent disease occurs in one third of patients treated with Tam within 5 years of therapy. A better understanding of gene expression alterations associated with Tam resistance will facilitate circumventing this problem. Using a next generation sequencing approach and a new bioinformatics model, we compared the transcriptomes of Tam-sensitive and Tam-resistant breast cancer cells for identification of genes involved in the development of Tam resistance. We identified differential expression of 1215 mRNA and 513 small RNA transcripts clustered into ERα functions, cell cycle regulation, transcription/translation, and mitochondrial dysfunction. The extent of alterations found at multiple levels of gene regulation highlights the ability of the Tam-resistant cells to modulate global gene expression. Alterations of small nucleolar RNA, oxidative phosphorylation, and proliferation processes in Tam-resistant cells present areas for diagnostic and therapeutic tool development for combating resistance to this anti-estrogen agent.
| S-EPMC3402532 | biostudies-literature