MicroRNA profiling of human breast cancer cell lines using five miRNA microarray platforms
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Git A
PROVIDER: S-ECPF-MTAB-96 | biostudies-other | 2010 May
REPOSITORIES: biostudies-other
Similar Datasets
Project description:Analysis of hybridisation performance and utility in identifying differentially expressed miRNAs of six miRNA microarray platforms using three biological samples in quadruplicate.
2010-02-24 | E-MTAB-96 | biostudies-arrayexpress
Project description:Over the last few years, miRNA microarray platforms have provided great insights into the biological mechanisms underlying the onset and development of several diseases. However, only a few studies have evaluated the concordance between different microarray platforms using methods that took into account measurement error in the data. In this work, we propose the use of a modified version of the Bland-Altman plot to assess agreement between microarray platforms. To this aim, two samples, one renal tumor cell line and a pool of 20 different human normal tissues, were profiled using three different miRNA platforms (Affymetrix, Agilent, Illumina) on triplicate arrays. Intra-platform reliability was assessed by calculating pair-wise concordance correlation coefficients (CCC) between technical replicates and overall concordance correlation coefficient (OCCC) with bootstrap percentile confidence intervals, which revealed moderate-to-good repeatability of all platforms for both samples. Modified Bland-Altman analysis revealed good patterns of concordance for Agilent and Illumina, whereas Affymetrix showed poor-to-moderate agreement for both samples considered. The proposed method is useful to assess agreement between array platforms by modifying the original Bland-Altman plot to let it account for measurement error and bias correction and can be used to assess patterns of concordance between other kinds of arrays other than miRNA microarrays.
| S-EPMC4979053 | biostudies-literature
Project description:two luminal cell lines were added, MCF7 and BT-474 two TNBC cell line were added, MB231 and BT-549 microRNA expression profiles were conpared between the luminal group and the TNBC group
| S-ECPF-GEOD-62022 | biostudies-other
Project description:Although the rate of breast cancer differs between women in Asian and Western countries, molecular genetics/genomics basis of this epidemiological observation remains elusive. Moreover, the intake of phytoestrogens is associated with a lower incidence of breast cancer. Genistein and daidzein are the primary soy isoflavones with a chemical structure similar to estrogens. Conceivably, the actions of phytoestrogens on gene expression signatures might mediate their postulated effects on breast cancer pathogenesis. The present study evaluated the transcriptional responsiveness of breast cancer cells to soy phytoestrogens using a whole-genome microarray-based approach. Human breast cancer cell lines and a fibrocystic breast cell line were treated with genistein or daidzein. We identified 278 and 334 differentially expressed genes after genistein or daidzein treatment, respectively, in estrogen-positive (MCF-7) and estrogen-negative (MDA-MB-231, MCF-10a) cells. Hierarchical clustering of this finding revealed a significant modulation, respectively, of 246 or 169 genes after genistein or daidzein exposures. Importantly, the molecular pathways for the differentially expressed genes included those that relate to cell communication, biodegradation of xenobiotics, lipid metabolism, signal transduction, and cell growth/death. These molecular observations collectively contribute to a growing knowledgebase on the putative mechanism(s) of action of phytoestrogens in breast cancer pathogenesis and chemoprevention.
| S-EPMC3128303 | biostudies-literature
Project description:BackgroundMicroRNAs (miRs) regulate gene expression through translation inhibition of target mRNAs. One of the most promising approaches for cancer therapy is through mimicking or antagonizing the action of miRs. In this report, we analyzed the miRnome profile of several human breast cancer cell lines to determine the influence of estrogen receptor (ER) silencing previously shown to result in epithelial to mesenchymal transition (EMT) and enhanced tumor invasion.MethodsMicroRNA extracted from MDA-MB-231 (de novo ER-) and ER-silenced (acquired ER-) pII and IM-26 or ER-expressing (YS1.2) siRNA transfected derivatives of MCF7 cells was deep sequenced on Illumina NextSeq500. Respective miRnomes were compared with edgeR package in R and Venny2.1 and target prediction performed with miRTarBase. Mimics and inhibitors of selected differentially expressed miRs associated with EMT mediators (miR-200c-3p targeting ZEB1, miR-449a targeting δ-catenin and miR-29a-3p) were transfected into pII cells and mRNA targets, as well as E-cadherin and keratin 19 (epithelial and mesenchymal markers respectively) were measured using taqman PCR.ResultsEach cell line expressed about 20% of the total known human miRnome; There was a high degree of similarity between the 3 tested ER-lines. Out of these expressed miRs, 50-60% were significantly differentially expressed between ER- and ER + lines. Transfection of miR-200c-3p mimic into pII cells down regulated ZEB1 and vimentin, and increased E-cadherin and keratin 19 with accompanying morphological changes, and reduced cell motility, reflecting a reversal back into an epithelial phenotype. On the other hand, transfecting pII with miR-449a inhibitor reduced cell invasion but did not induce EMT. Transfecting pII cell line with the mimic or inhibitor of miR-29a-3p showed no change in EMT markers or cell invasion suggesting that the EMT induced by loss of ER function can be reversed by blocking some but not just any random EMT-associated genes.ConclusionsThese data suggest that differences in miR expression can be exploited not only as mediators (using mimics) and targets (using miR antagonists) for general cancer therapies aimed at regulating either individual or multiple mRNAs, but also to re-sensitize endocrine resistant breast cancers by turning them back into a type that will be susceptible to endocrine agents.
| S-EPMC9307586 | biostudies-literature
Project description:Independent studies have reported that circulating miRNAs have the potential as biomarkers; however, no consolidated guidelines for the discovery process are available. We developed a pipeline using innovative applications of existing bioinformatics methods to (1) face the inapplicability of the classical normalization methods, (2) detect global differences of miRNA distributions between the comparison classes and (3) develop a 'robust’ classifier. 78 samples (26 hemolyzed and 52 non hemolyzed) were 1:2 paired with caliper matching according to disease status, age at drawing and drawing year, starting from a total of 208 hybridized samples collected between 1987 and 2004 (including 94 paired samples according to tumor ER status, age at drawing, drawing year, time from surgery, 7 additional samples from 'no evidence of disease' (NED) patients, 10 references, 1 healthy donor and 2 replicated samples)
| S-ECPF-GEOD-59993 | biostudies-other
Project description:In order to identify the microRNAs differentially expressed according to the estrogen receptor status, total RNAs in triplicate from six breast cancer cell lines with different ERalpha status (ER+: T47D, BT-474, MDA-MB-483; ER-: MDA-MD-436, MDA-MB-231, MDA-MB-468) was extracted by using Trizol reagent and used for microarray experiments.
| S-ECPF-TABM-596 | biostudies-other
Project description:Global miRNA expression profiling of human malignancies is gaining popularity in both basic and clinically driven research. But to date, the majority of such analyses have used microarrays and quantitative real-time PCR. With the introduction of digital count technologies, such as next-generation sequencing (NGS) and the NanoString nCounter System, we have at our disposal, many more options. To make effective use of these different platforms, the strengths and pitfalls of several miRNA profiling technologies were assessed, including a microarray platform, NGS technologies and the NanoString nCounter System. These results were compared to gold-standard quantitative real-time PCR. Comparison of non-small cell lung cancer cell lines grown in vitro (n = 5) and in vivo (n = 5) as xenograft models.
| S-ECPF-GEOD-51501 | biostudies-other
Project description:Global miRNA expression profiling of human malignancies is gaining popularity in both basic and clinically driven research. But to date, the majority of such analyses have used microarrays and quantitative real-time PCR. With the introduction of digital count technologies, such as next-generation sequencing (NGS) and the NanoString nCounter System, we have at our disposal, many more options. To make effective use of these different platforms, the strengths and pitfalls of several miRNA profiling technologies were assessed, including a microarray platform, NGS technologies and the NanoString nCounter System. These results were compared to gold-standard quantitative real-time PCR. Comparison of non-small cell lung cancer cell lines grown in vitro (n = 5) and in vivo (n = 5) as xenograft models.
| S-ECPF-GEOD-51507 | biostudies-other
Project description:MicroRNA profiling represents an important first-step in deducting individual RNA-based regulatory function in a cell, tissue, or at a specific developmental stage. Currently there are several different platforms to choose from in order to make the initial miRNA profiles. In this study we investigate recently developed digital microRNA high-throughput technologies. Four different platforms were compared including next generation SOLiD ligation sequencing and Illumina HiSeq sequencing, hybridization-based NanoString nCounter, and miRCURY locked nucleic acid RT-qPCR. For all four technologies, full microRNA profiles were generated from human cell lines that represent noninvasive and invasive tumorigenic breast cancer. This study reports the correlation between platforms, as well as a more extensive analysis of the accuracy and sensitivity of data generated when using different platforms and important consideration when verifying results by the use of additional technologies. We found all the platforms to be highly capable for microRNA analysis. Furthermore, the two NGS platforms and RT-qPCR all have equally high sensitivity, and the fold change accuracy is independent of individual miRNA concentration for NGS and RT-qPCR. Based on these findings we propose new guidelines and considerations when performing microRNA profiling.
| S-EPMC3793004 | biostudies-literature