RNA-seq of coding and non-coding RNA from miR-522 pulldown in human MDA-MB-468 breast cancer cells
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Tan Shen Mynn
PROVIDER: S-ECPF-MTAB-2112 | biostudies-other |
REPOSITORIES: biostudies-other
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Project description:Identifying miRNA-regulated genes is key to understanding miRNA function. However, many miRNA recognition elements (MREs) do not follow canonical seed base-pairing rules, making identification of bona fide targets challenging. Here, we apply an unbiased sequencing-based systems approach to characterize miR-522, a member of the oncogenic primate-specific chromosome 19 miRNA cluster, highly expressed in poorly differentiated cancers. To identify miRNA targets, we sequenced full-length transcripts captured by a biotinylated miRNA mimic. Within these targets, mostly non-canonical MREs were identified by sequencing RNase-resistant fragments (this dataset).
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Project description:Mammalian target of rapamycin (mTOR) is a serine/threonine kinase involved in multiple intracellular signaling pathways promoting tumor growth. mTOR is aberrantly activated in a significant portion of breast cancers and is a promising target for treatment. Rapamycin and its analogues are in clinical trials for breast cancer treatment. Patterns of gene expression (metagenes) may also be used to simulate a biologic process of effects of a drug treatment. In this study, we tested the hypothesis that the gene-expression signature regulated by rapamycin could predict disease outcome for patients with breast cancer. Results: Colony formation and sulforhodamine B (IC50 < 1nM) assays, and xenograft animals showed that MDA-MB-468 cells were sensitive to treatment with rapamycin. The comparison of in vitro and in vivo gene expression data identified a signature, termed rapamycin metagene index (RMI), of 31 genes upregulated by rapamycin treatment in vitro as well as in vivo (false discovery rate of 10%). In the Miller dataset, RMI was significantly associated with tumor size or lymph node status. High (>75) percentile) RMI was significantly associated with longer survival (P = 0.015). On multivariate analysis, RMI (P = 0.029), tumor size (P = 0.015) and lymph node status (P = 0.01) were prognostic. In van 't Veer study, RMI was not associated with the time to develop distant metastasis (P = 0.41). In Wang dataset, RMI predicted time to disease relapse (P = 0.09). Conclusions: Rapamycin-regulated gene expression signature predicts clinical outcome in breast cancer. This supports the central role of mTOR signaling in breast cancer biology and provides further impetus to pursue mTOR-targeted therapies for breast cancer treatment. Mol Cancer. 2009 Sep 24;8(1):75. Experiment Overall Design: Rapamycin treatment of MDA-MB-468 breast cancer cell line: Experiment Overall Design: MDA-MB-468 cell line was treated by DMSO (vehicle) and 100 nM rapamycin for 24 hours. We sought to identify differentially expressed genes. Experiment Overall Design: Rapamycin treatment of breast tumor xenografts: Experiment Overall Design: MDA-MB-468 cells were inoculated in the mammary fat pad of female nude mice. When resulting tumor volumes had reached 75-150 mm3, the mice were divided in four groups. Groups 1 and 2 received a single injection of DMSO (vehicle) or rapamycin (15 mg/kg) intraperitoneally and sacrificied 24 h later (1-day groups). Groups 3 and 4 received weekly injections of DMSO or rapamycin for 3 weeks and sacrificied 24 h after the last injection (22-day groups).
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Project description:Mammalian target of rapamycin (mTOR) is a serine/threonine kinase involved in multiple intracellular signaling pathways promoting tumor growth. mTOR is aberrantly activated in a significant portion of breast cancers and is a promising target for treatment. Rapamycin and its analogues are in clinical trials for breast cancer treatment. Patterns of gene expression (metagenes) may also be used to simulate a biologic process of effects of a drug treatment. In this study, we tested the hypothesis that the gene-expression signature regulated by rapamycin could predict disease outcome for patients with breast cancer. Results: Colony formation and sulforhodamine B (IC50 < 1nM) assays, and xenograft animals showed that MDA-MB-468 cells were sensitive to treatment with rapamycin. The comparison of in vitro and in vivo gene expression data identified a signature, termed rapamycin metagene index (RMI), of 31 genes upregulated by rapamycin treatment in vitro as well as in vivo (false discovery rate of 10%). In the Miller dataset, RMI was significantly associated with tumor size or lymph node status. High (>75) percentile) RMI was significantly associated with longer survival (P = 0.015). On multivariate analysis, RMI (P = 0.029), tumor size (P = 0.015) and lymph node status (P = 0.01) were prognostic. In van 't Veer study, RMI was not associated with the time to develop distant metastasis (P = 0.41). In Wang dataset, RMI predicted time to disease relapse (P = 0.09). Conclusions: Rapamycin-regulated gene expression signature predicts clinical outcome in breast cancer. This supports the central role of mTOR signaling in breast cancer biology and provides further impetus to pursue mTOR-targeted therapies for breast cancer treatment. Mol Cancer. 2009 Sep 24;8(1):75.
2009-11-20 | GSE18571 | GEO
Project description:BackgroundIncreased transcription of oncogenes like the epidermal growth factor receptor (EGFR) is frequently caused by amplification of the whole gene or at least of regulatory sequences. Aim of this study was to pinpoint mechanistic parameters occurring during egfr copy number gains leading to a stable EGFR overexpression and high sensitivity to extracellular signalling. A deeper understanding of those marker events might improve early diagnosis of cancer in suspect lesions, early detection of cancer progression and the prediction of egfr targeted therapies.MethodsThe basal-like/stemness type breast cancer cell line subpopulation MDA-MB-468 CD44high/CD24-/low, carrying high egfr amplifications, was chosen as a model system in this study. Subclones of the heterogeneous cell line expressing low and high EGF receptor densities were isolated by cell sorting. Genomic profiling was carried out for these by means of SNP array profiling, qPCR and FISH. Cell cycle analysis was performed using the BrdU quenching technique.ResultsLow and high EGFR expressing MDA-MB-468 CD44+/CD24-/low subpopulations separated by cell sorting showed intermediate and high copy numbers of egfr, respectively. However, during cell culture an increase solely for egfr gene copy numbers in the intermediate subpopulation occurred. This shift was based on the formation of new cells which regained egfr gene copies. By two parametric cell cycle analysis clonal effects mediated through growth advantage of cells bearing higher egfr gene copy numbers could most likely be excluded for being the driving force. Subsequently, the detection of a fragile site distal to the egfr gene, sustaining uncapped telomere-less chromosomal ends, the ladder-like structure of the intrachromosomal egfr amplification and a broader range of egfr copy numbers support the assumption that dynamic chromosomal rearrangements, like breakage-fusion-bridge-cycles other than proliferation drive the gain of egfr copies.ConclusionProgressive genome modulation in the CD44+/CD24-/low subpopulation of the breast cancer cell line MDA-MB-468 leads to different coexisting subclones. In isolated low-copy cells asymmetric chromosomal segregation leads to new cells with regained solely egfr gene copies. Furthermore, egfr regain resulted in enhanced signal transduction of the MAP-kinase and PI3-kinase pathway. We show here for the first time a dynamic copy number regain in basal-like/stemness cell type breast cancer subpopulations which might explain genetic heterogeneity. Moreover, this process might also be involved in adaptive growth factor receptor intracellular signaling which support survival and migration during cancer development and progression.
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Project description:Identifying miRNA-regulated genes is key to understanding miRNA function. However, many miRNA recognition elements (MREs) do not follow canonical seed base-pairing rules, making identification of bona fide targets challenging. Here, we apply an unbiased sequencing-based systems approach to characterize miR-522, a member of the oncogenic primate-specific chromosome 19 miRNA cluster, highly expressed in poorly differentiated cancers. To identify miRNA targets, we sequenced full-length transcripts captured by a biotinylated miRNA mimic (this dataset). Within these targets, mostly non-canonical MREs were identified by sequencing RNase-resistant fragments.
2014-06-03 | E-MTAB-2112 | biostudies-arrayexpress
Project description:Identifying miRNA-regulated genes is key to understanding miRNA function. However, many miRNA recognition elements (MREs) do not follow canonical seed base-pairing rules, making identification of bona fide targets challenging. Here, we apply an unbiased sequencing-based systems approach to characterize miR-522, a member of the oncogenic primate-specific chromosome 19 miRNA cluster, highly expressed in poorly differentiated cancers. To identify miRNA targets, we sequenced full-length transcripts captured by a biotinylated miRNA mimic. Within these targets, mostly non-canonical MREs were identified by sequencing RNase-resistant fragments (this dataset).
2014-06-03 | E-MTAB-2119 | biostudies-arrayexpress