Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcription profiling of rat neonatal ventricular myocytes

ABSTRACT: Title: Regulation of gene expression through mitogen-activated protein kinase cascades in cardiac myocytes.
Description: The aim of this study is to identify the changes in gene expression induced in rat neonatal
ventricular myocytes, a well-established cell culture model, by endothelin-1,
a known hypertrophic agonist, and to determine which of the changes are
mediated through the ERK cascade. This continues TKAC^Ys previous study of the
effects of oxidative stress, which induces cardiac myocyte apoptosis.

ORGANISM(S): Rattus norvegicus

SUBMITTER: unknown unknown

PROVIDER: E-MIMR-3 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Significance analysis of lexical bias in microarray data.

Kim Charles C CC Falkow Stanley S

BMC bioinformatics 20030403

<h4>Background</h4>Genes that are determined to be significantly differentially regulated in microarray analyses often appear to have functional commonalities, such as being components of the same biochemical pathway. This results in certain words being under- or overrepresented in the list of genes. Distinguishing between biologically meaningful trends and artifacts of annotation and analysis procedures is of the utmost importance, as only true biological trends are of interest for further expe ...[more]

PMID: 12697067

Similar Datasets

Project description:Epidemiological studies have revealed concurrence of specific cancers with other disease states such as metabolic syndrome, inflammatory disease and autoimmune disease. Patients with these chronic conditions have a higher incidence of various cancers, more aggressive tumors, and a higher mortality rate. It has been proposed that obesity, inflammation and chronic disease should be correlated with cancer at the molecular level, but common gene signatures or networks have yet to be described. Here, we identify genes regulated during the process of cellular transformation in both a breast epithelial cell line and a set of isogenic fibroblastic cell lines. The resulting gene signature strongly mimics those of many different cancer types, thereby validating these experimental systems as models of oncogenesis. Furthermore, it uncovers transcriptional factors and common gene regulatory networks linking cancer with other disease states such as atheroscelorsis, type II diabetes, obesity, lupus, and cardiomyopathy. We suggest that this common transcriptional program can contribute to the concurrence of different diseases, and that the interplay between this program and cell-type specific factors can give rise to a variety of human diseases. Two isogenic cell lines were used to model transformation. The first employed an inducible oncogene: src fused to the ligand binding domain of the estrogen receptor. ER-src and pBABE control cells were dosed with Tamoxifen or Etoh control across several time points to monitor gene expression during transformation. The other model consists of three isogenic cell lines derived from primary fibroblasts in a serial manner. The first is immortalized by overexpression of telomerase (hTERT), and exhibits normal fibroblast morphology. The second expresses hTERT along with both large and small T antigens of Simian virus 40, and it displays an altered morphology but is not transformed. The third cell line expresses hTERT, T antigens, and an oncogenic derivative of Ras (H-RasV12); it is morphologically transformed and has tumorigenic potential in soft agar and nude mice. Thus, three stages of transformation are represented by these cells.

Dataset Information

Transcription profiling of rat neonatal ventricular myocytes

Publications

Significance analysis of lexical bias in microarray data.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure