Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA186732 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:34 NSCLC cell lines were transcriptionally profiled against a reference mix of 45 NSCLC cell lines to look subtype specific differential gene expression 34 individual cell lines were compared to a reference mix consiting of 45 NSCLC cell lines
2013-01-18 | E-GEOD-43567 | biostudies-arrayexpress
Project description:34 NSCLC cell lines were transcriptionally profiled against a reference mix of 45 NSCLC cell lines to look subtype specific differential gene expression
2013-01-18 | GSE43567 | GEO
Project description:Illumina miRNA-seq method to uncover the expression profile of NSCLC in-vitro experimental models consisting of cell lines A549, H460 compared to healthy BEAS-2B cell line, and lung tissue (NSCLC and paired normal) from urethane treated 6-week-old FVB/NJ mice. We aimed to uncover the divergent epigenetic background of KRAS-mutant NSCLC in mouse and human cell lines, extensively used as biological models in relevant research. To that end, we have comprehensively mapped the functional miRNA and lncRNA landscape of human (A549 and H460) and mouse (experimentally developed LUAD) NSCLC models and correlated current results with LRF/ZBTB7A expression
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Project description:Eleven NSCLC cell lines with widely divergent gefitinib sensitivities were compared using gene expression. Genes associated with gefitinib response were used to classify additional NSCLC lines with unknown gefitnib sensitivity. A subset of the test set data was tested for gefitinib sensitivity, and results correlated strongly with the gene expression-based predictions; All eleven training set lines, and seven test set lines had both HGU133A and B chips done, while other test set lines had only HGU133As. Experiment Overall Design: Baseline (unstimulated) gene expression was measured in a large panel of NSCLC cell lines.
2007-11-01 | E-GEOD-4342 | biostudies-arrayexpress
Project description:RNA expression patterns of breast cell lines were compared with a breast cell line mixed reference. Gene expression profiles of 52 individual breast cell lines relative to a breast cell line reference mix containing equal amounts of 10 breast cell lines.
2013-02-22 | E-GEOD-44552 | biostudies-arrayexpress
Project description:Non-small cell lung cancer (NSCLC) cell lines are widely used model systems to study molecular aspects of lung cancer. Comparative and in-depth proteome expression data across many NSCLC cell lines has not been generated yet, but would be of utility for the investigation of candidate targets and markers in oncogenesis. We employed a SILAC reference approach to perform replicate proteome quantifications across 23 distinct NSCLC cell lines. On average, close to 4000 distinct proteins were identified and quantified per cell line. These included many known targets and diagnostic markers, indicating that our proteome expression data represents a useful resource for NSCLC pre-clinical research. To assess proteome diversity within the NSCLC cell line panel, we performed hierarchical clustering and principal component analysis of proteome expression data. Our results indicate that general proteome diversity among NSCLC cell lines supersedes potential effects common to K-Ras or epidermal growth factor receptor (EGFR) oncoprotein expression. However, we observed partial segregation of EGFR or KRAS mutant cell lines for certain principal components, which reflected biological differences according to gene ontology enrichment analyses. Moreover, statistical analysis revealed several proteins that were significantly overexpressed in KRAS or EGFR mutant cell lines. Biological significance Despite enormous progress in molecular characterization and targeted therapy NSCLC represents a major cause for cancer-related deaths. While pre-clinical models such as NSCLC cell lines have been studied on the genomic and transcriptional level, proteome composition is poorly characterized. We conducted quantitative profiling across 23 NSCLC cell lines and studied global proteome diversity in relation to the presence of oncogenic KRAS or EGFR mutations. Notably, in-depth bioinformatics analysis pointed to prominent biological processes as well as up-regulated proteins in KRAS and EGFR mutant cells, highlighting the utility of cancer cell proteomics to identify target or biomarker candidates in the context of specific oncogenic mechanisms.
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Project description:To provide useful data for development and validation of the PyMS Mass Spectrometry software, a test dataset was run at Metabolomics Australia. A biologically complex mix of a biological background material (foetal calf serum), spiked with 2-fold increasing amounts of a mix of metabolite standards. In addition, a single sample consisting of a simple mix of 45 metabolites representing a variety of chemical classes (sufars, organic acids, amino acids, sugar phosphates), was run through a standard Metabolomics Australia GC-MS analysis. The resulting data is a valuable tool in testing GC-MS data analysis software.
2012-03-29 | MTBLS6 | MetaboLights