Changes in global gene expression in lung cancer cell lines A549 (A) and HTB56 (H) [Affymetrix microarrays]
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE52143 | GEO | 2013/12/18
SECONDARY ACCESSION(S): PRJNA227471
REPOSITORIES: GEO
Similar Datasets
Project description:Here, we analyzed global gene expression changes that were associated with pro-metastatic phenotypes in non-small cell lung cancer using the Affymetrix microarray platform. Changes in global gene expression were determined with Affymetrix microarrays in lung cancer cell lines A549 (A) and HTB56 (H). We generated NSCLC lines with highly increased propensity to form tumor nodules in murine lungs after intravenous injections. In addition to the normal cell lines (0R) we analyzed gene expression of the the cell lines after three rounds of in vivo selection towards a highly metastatic phenotype (3R).
2013-12-18 | E-GEOD-52143 | biostudies-arrayexpress
Project description:Here, we analyzed global gene expression changes that were associated with pro-metastatic phenotypes in non-small cell lung cancer using the Affymetrix microarray platform. Changes in global gene expression were determined with Affymetrix microarrays in lung cancer cell lines A549 (A) and HTB56 (H). We generated NSCLC lines with highly increased propensity to form tumor nodules in murine lungs after intravenous injections. In addition to the normal cell lines (0R) we analyzed gene expression of the the cell lines after three rounds of in vivo selection towards a highly metastatic phenotype (3R).
| S-ECPF-GEOD-52143 | biostudies-other
Project description:Cancer cell phenotypes are partially determined by epigenetic specifications such as DNA methylation. Metastasis development is a late event in cancerogenesis and might be associated with epigenetic alterations. Here, we analyzed genome wide DNA methylation changes that were associated with pro-metastatic phenotypes in non-small cell lung cancer using the Illumina HumanMethylation27 BeadChip platform.
2013-12-18 | GSE52144 | GEO
Project description:Cancer cell phenotypes are partially determined by epigenetic specifications such as DNA methylation. Metastasis development is a late event in cancerogenesis and might be associated with epigenetic alterations. Here, we analyzed genome wide DNA methylation changes that were associated with pro-metastatic phenotypes in non-small cell lung cancer using the Illumina HumanMethylation27 BeadChip platform. We studied genome-wide methylation changes in lung cancer cell lines A549 (A) and HTB56 (H). We generated NSCLC lines with highly increased propensity to form tumor nodules in murine lungs after intravenous injections. In addition to the normal cell lines (0R) we analyzed the methylome of the the cell lines after three rounds of in vivo selection towards a highly metastatic phenotype (3R).
2013-12-18 | E-GEOD-52144 | biostudies-arrayexpress
Project description:PurposeThe present study was designed to compare the results obtained from two different microarray platforms: spotted cDNAs using a two-color system (Clontech, Atlas Glass Human 3.8) and the Affymetrix platform. We evaluated the internal consistency within each of the platforms, and compared the results across the two platforms.MethodsRNA was isolated from two retinal pigment epithelial (RPE) cell lines, D407 cells and ARPE19 cells. Each microarray system requires a specific RNA isolation and target preparation procedure. To compare the results between the two platforms, the intensity values for each platform were standardized and scaled. This allowed for a direct comparison of the data between two very different microarray platforms. Real-time RT-PCR was used as an independent conformation of expression levels for selected transcripts. The protein levels for some of these genes were determined using a quantitative immunoblot method.ResultsFirst, we compared the transcriptome of the D407 cell line to itself. Within each of the platforms there was a high degree of consistency. However, when the data from the Atlas Glass Human 3.8 microarray platform was compared to that of the Affymetrix platform there was a dramatic lack of agreement. The second step was to compare the mRNA profile of the ARPE19 cell line to the D407 cell line. Again there was good agreement within each platform. When the results of the Atlas Glass Human 3.8 platform were compared to the Affymetrix platform, there was a surprising lack of agreement between the two data sets. Real-time RT-PCR was used as independent means of defining RNA levels in the two cell lines. In general, the real-time RT-PCR results were in better agreement with the Affymetrix platform (85%) than the Atlas Glass platform (33%). In addition, we also examined the levels of 11 proteins in these two cell lines using a quantitative immunoblot method. The results from this protein analysis had a higher degree of concordance with the results from Affymetrix platform.ConclusionsIn both the Atlas Glass Human 3.8 system and the Affymetrix platform, there is a high degree of internal consistency. However, comparisons between the two platforms show a lack of agreement. In general, the real-time RT-PCR confirmed the results on the Affymetrix system more often than those from Atlas Glass arrays. However, in both cases, conformation by an independent method proves to be of considerable value.
| S-EPMC2819117 | biostudies-literature
Project description:Gene expression microarrays measure the levels of messenger ribonucleic acid (mRNA) in a sample using probe sequences that hybridize with transcribed regions. These probe sequences are designed using a reference genome for the relevant species. However, most model organisms and all humans have genomes that deviate from their reference. These variations, which include single nucleotide polymorphisms, insertions of additional nucleotides, and nucleotide deletions, can affect the microarray's performance. Genetic experiments comparing individuals bearing different population-associated single nucleotide polymorphisms that intersect microarray probes are therefore subject to systemic bias, as the reduction in binding efficiency due to a technical artifact is confounded with genetic differences between parental strains. This problem has been recognized for some time, and earlier methods of compensation have attempted to identify probes affected by genome variants using statistical models. These methods may require replicate microarray measurement of gene expression in the relevant tissue in inbred parental samples, which are not always available in model organisms and are never available in humans.By using sequence information for the genomes of organisms under investigation, potentially problematic probes can now be identified a priori. However, there is no published software tool that makes it easy to eliminate these probes from an annotation. I present equalizer, a software package that uses genome variant data to modify annotation files for the commonly used Affymetrix IVT and Gene/Exon platforms. These files can be used by any microarray normalization method for subsequent analysis. I demonstrate how use of equalizer on experiments mapping germline influence on gene expression in a genetic cross between two divergent mouse species and in human samples significantly reduces probe hybridization-induced bias, reducing false positive and false negative findings.The equalizer package reduces probe hybridization bias from experiments performed on the Affymetrix microarray platform, allowing accurate assessment of germline influence on gene expression.
| S-EPMC4518889 | biostudies-literature
Project description:BackgroundAffymetrix microarrays are used by many laboratories to generate gene expression profiles. Generally, only large differences (> 1.7-fold) between conditions have been reported. Computational methods to reduce inter-array variability might be of value when attempting to detect smaller differences. We examined whether inter-array variability could be reduced by using data based on the Affymetrix algorithm for pairwise comparisons between arrays (ratio method) rather than data based on the algorithm for analysis of individual arrays (signal method). Six HG-U95A arrays that probed mRNA from young (21-31 yr old) human muscle were compared with six arrays that probed mRNA from older (62-77 yr old) muscle.ResultsDifferences in mean expression levels of young and old subjects were small, rarely > 1.5-fold. The mean within-group coefficient of variation for 4629 mRNAs expressed in muscle was 20% according to the ratio method and 25% according to the signal method. The ratio method yielded more differences according to t-tests (124 vs. 98 differences at P < 0.01), rank sum tests (107 vs. 85 differences at P < 0.01), and the Significance Analysis of Microarrays method (124 vs. 56 differences with false detection rate < 20%; 20 vs. 0 differences with false detection rate < 5%). The ratio method also improved consistency between results of the initial scan and results of the antibody-enhanced scan.ConclusionThe ratio method reduces inter-array variance and thereby enhances statistical power.
| S-EPMC126253 | biostudies-literature
Project description:BackgroundThe development of large-scale gene expression profiling technologies is rapidly changing the norms of biological investigation. But the rapid pace of change itself presents challenges. Commercial microarrays are regularly modified to incorporate new genes and improved target sequences. Although the ability to compare datasets across generations is crucial for any long-term research project, to date no means to allow such comparisons have been developed. In this study the reproducibility of gene expression levels across two generations of Affymetrix GeneChips (HuGeneFL and HG-U95A) was measured.ResultsCorrelation coefficients were computed for gene expression values across chip generations based on different measures of similarity. Comparing the absolute calls assigned to the individual probe sets across the generations found them to be largely unchanged.ConclusionWe show that experimental replicates are highly reproducible, but that reproducibility across generations depends on the degree of similarity of the probe sets and the expression level of the corresponding transcript.
| S-EPMC165600 | biostudies-literature
Project description:Cancer cell phenotypes are partially determined by epigenetic specifications such as DNA methylation. Metastasis development is a late event in cancerogenesis and might be associated with epigenetic alterations. Here, we analyzed genome wide DNA methylation changes that were associated with pro-metastatic phenotypes in non-small cell lung cancer with Reduced Representation Bisulfite Sequencing. DNMT-inhibition by 5-Azacytidine at low concentrations reverted the pro-metastatic phenotype. 5-Azacytidine led to preferential loss of DNA methylation at sites that were DNA hypermethylated during the in vivo selection. Changes in DNA methylation persisted over time. Keywords: Methylation profiling by high throughput sequencing We studied genome-wide methylation changes in lung cancer cell lines A549 (A) and HTB56 (H). We generated NSCLC lines with highly increased propensity to form tumor nodules in murine lungs after intravenous injections. In addition to the normal cell lines (0R) we analyzed the methylome of the the cell lines after three rounds of in vivo selection towards a highly metastatic phenotype (3R). Next we studied changes in the methylome of highly metastatic cell lines after DNA Methyltransferase inhibition by 5-Azacytidine treatment at low concentrations (250 nM & 1000 nM) for 6 days. During treatment cells were supplemented with fresh medium every 48 hours. After 6 days of 5-Azacytidine exposure, cells were washed three times with PBS to wash out the drug. The cells were released for additional 7 days in regular medium. We followed up the DNA methylation changes at day 13 of the experiment.
2013-12-18 | E-GEOD-52140 | biostudies-arrayexpress
Project description:Non Small Cell Lung Cancer (NSCLC) causes the premature death of over 1 million people worldwide each year, but remains inadequately understood at the molecular level. To provide new insights for NSCLC treatment we performed a molecular characterisation of wild type and platinum drugs resistance in A549 cells. Transcriptome profiling revealed contrasting patterns of gene expression in sensitive and resistant cells and identified genes whose expression was highly correlated with the platinum drugs. Our results revealed a gene set of 15 transcripts whose expression was highly correlated with platinum-resistance in NSCLC A549 cell lines.
| S-ECPF-MEXP-3123 | biostudies-other