Similar Datasets
Project description:Epigenetic gene silencing induced by aberrant DNA methylation is an important mechanism leading to the loss of key cellular pathways in tumorigenesis. Although DNA demethylating agents reverse DNA methylation and have significant cytostatic and cytotoxic effects, it remains elusive whether their effects on cellular phenotypes are solely on reactivation of hypermethylated genes. To address this issue, we constructed LNCaP-derived human prostate cancer cell lines that can pharmacologically induce the expression of fusion gene comprising NFkB transcriptional activation domain (AD) and methyl-CpG binding domain (MBD). Tetracycline induction of NFkB (AD)-MBD protein led to so-called methyl-CpG targeted transcriptional activation (MeTA), as demonstrated by the reactivation of hypermethylated genes such as MT1M, NEFH, and NEFM. The cell proliferation assay indicated that MeTA suppressed the growth of LNCaP cells. Furthermore, both flow cytometry and TUNEL assay clearly demonstrated that MeTA induced apoptosis. In order to search genes responsible for apoptosis, we performed gene expression microarray analysis of MeTA-uninduced and -induced LNCaP cells: Several tumor necrosis factor receptor superfamily (TNFRSF) genes upregulated in accordance with the induction of MeTA. These results suggest that DNA methylation confers cancer cells the ability to avoid apoptosis and MeTA may provide an efficient mean to analyze the change in cancer cell phenotypes by DNA methylation alterations. This is the first report showing that the reactivation of hypermethylated genes by the method other than DNMT inhibition induces growth arrest and apoptosis in cancer cells.
2021-03-02 | GSE74743 | GEO
Project description:We present a meta-dataset comprising of a total of 178 samples including both primary tumors and tumor-free pancreatic tissues from four independent GEO datasets. To minimise inter-platform variation, only datasets generated from the GPL570 platform (Affymetrix Human Genome U133 Plus 2.0 Array) were processed to develop the meta-dataset. Using multiple open source R packages implemented in our previously developed bioinformatics pipeline, each dataset has been preprocessed with RMA normalisation, merged, and batch effect-corrected via Combat method. With increased sample size, the present meta-dataset serves an excellent 'discovery cohort' for discovering differentially expressed in diseased phenotype.
2019-04-11 | E-MTAB-6690 | biostudies-arrayexpress
Project description:We present a meta-dataset comprising of a total of 663 samples including both primary tumors and tumor-free ovarian tissues from ten independent GEO datasets. To minimise inter-platform variation, only datasets generated from the GPL570 platform (Affymetrix Human Genome U133 Plus 2.0 Array) were processed to develop the meta-dataset. Using multiple open source R packages implemented in our previously developed bioinformatics pipeline, each dataset has been preprocessed with RMA normalisation, merged, and batch effect-corrected via Combat method. With increased sample size, the present meta-dataset serves an excellent 'discovery cohort' for discovering differentially expressed in diseased phenotype.
2019-04-11 | E-MTAB-6691 | biostudies-arrayexpress
Project description:We present a meta-dataset comprising of a total of 347 samples including both primary tumors and tumor-free renal tissues from six independent GEO datasets. To minimise inter-platform variation, only datasets generated from the GPL570 platform (Affymetrix Human Genome U133 Plus 2.0 Array) were processed to develop the meta-dataset. Using multiple open source R packages implemented in our previously developed bioinformatics pipeline, each dataset has been preprocessed with RMA normalisation, merged, and batch effect-corrected via Combat method. With increased sample size, the present meta-dataset serves an excellent 'discovery cohort' for discovering differentially expressed in diseased phenotype.
2019-04-11 | E-MTAB-6692 | biostudies-arrayexpress
Project description:We present a meta-dataset comprising of a total of 237 samples including both primary tumors and tumor-free prostate tissues from six independent GEO datasets. To minimise inter-platform variation, only datasets generated from the GPL570 platform (Affymetrix Human Genome U133 Plus 2.0 Array) were processed to develop the meta-dataset. Using multiple open source R packages implemented in our previously developed bioinformatics pipeline, each dataset has been preprocessed with RMA normalisation, merged, and batch effect-corrected via Combat method. With increased sample size, the present meta-dataset serves an excellent 'discovery cohort' for discovering differentially expressed in diseased phenotype.
2019-04-11 | E-MTAB-6694 | biostudies-arrayexpress
Project description:We present a meta-dataset comprising of a total of 212 samples including both primary tumors and tumor-free bladder tissues from four independent GEO datasets. To minimise inter-platform variation, only datasets generated from the GPL570 platform (Affymetrix Human Genome U133 Plus 2.0 Array) were processed to develop the meta-dataset. Using multiple open source R packages implemented in our previously developed bioinformatics pipeline, each dataset has been preprocessed with RMA normalisation, merged, and batch effect-corrected via Combat method. With increased sample size, the present meta-dataset serves an excellent 'discovery cohort' for discovering differentially expressed in diseased phenotype.
2019-04-11 | E-MTAB-6696 | biostudies-arrayexpress