Gene expression profiling of FFPE breast cancer samples [Affymetrix platform]
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE51450 | GEO | 2015/02/25
SECONDARY ACCESSION(S): PRJNA223225
REPOSITORIES: GEO
Similar Datasets
Project description:The use of Affymetrix U133 2.0 Plus chips on FFPE samples when coupled with a qPCR-based sample pre-assessment step, yielded satisfactory results from the point of view of biological reliability. When compared with the Illumina DASL WG platform, specifically designed for degraded RNA, the data generated with the Affymetrix platform showed a wider interquartile range (1.32 vs 0.57, p<2.2x10-16) suggesting a superior discriminatory power within samples as indicated by the good agreement with the immunohistiochemically derived ER status. FFPE primary breast cancer samples profiled using Illumina DASL WG platform after RNA amplification with the Nugen WT-Ovation FFPE System
2015-02-25 | GSE51451 | GEO
Project description:The use of Affymetrix U133 2.0 Plus chips on FFPE samples when coupled with a qPCR-based sample pre-assessment step, yielded satisfactory results from the point of view of biological reliability. When compared with the Illumina DASL WG platform, specifically designed for degraded RNA, the data generated with the Affymetrix platform showed a wider interquartile range (IQR 1.32 vs 0.57, p<2.2x10-16) suggesting a superior discriminatory power within samples as indicated by the good agreement with the immunohistiochemically derived ER status. FFPE primary breast cancer samples profiled using Affymetrix HG-U133 Plus 2.0 microarray platform after RNA amplification with the Nugen WT-Ovation FFPE System The following criteria were considered for a direct comparison of 12 GEPs obtained from Affymetrix and DASL platforms: gene variability as defined by IQR, ESR1 expression in ER status subgroups defined by IHC, distribution of fold changes for predefined ER related genes when comparing ER positive and negative samples.
2015-02-25 | E-GEOD-51450 | biostudies-arrayexpress
Project description:The use of Affymetrix U133 2.0 Plus chips on FFPE samples when coupled with a qPCR-based sample pre-assessment step, yielded satisfactory results from the point of view of biological reliability. When compared with the Illumina DASL WG platform, specifically designed for degraded RNA, the data generated with the Affymetrix platform showed a wider interquartile range (1.32 vs 0.57, p<2.2x10-16) suggesting a superior discriminatory power within samples as indicated by the good agreement with the immunohistiochemically derived ER status. FFPE primary breast cancer samples profiled using Illumina DASL WG platform after RNA amplification with the Nugen WT-Ovation FFPE System The following criteria were considered for a direct comparison of 12 GEPs obtained from Affymetrix and DASL platforms: gene variability as defined by IQR, ESR1 expression in ER status subgroups defined by IHC, distribution of fold changes for predefined ER related genes when comparing ER positive and negative samples.
2015-02-25 | E-GEOD-51451 | biostudies-arrayexpress
Project description:Cross-platform comparison between WG-DASL and IVT-based assays
2010-01-13 | GSE17575 | GEO
Project description:This is a pilot study. We are trying to detect potential salivary biomarkers in mice with a pancreatic tumor. Global gene expression profiling has shown great promise in high-throughput biomarker discovery for early disease detection in body fluids such as saliva, which is accessible, cost-effective, and non-invasive. However, this goal has not been fully realized because saliva, like many clinical samples, contains partially fragmented and degraded RNAs that are difficult to amplify and detect with prevailing technologies. Here, using nanogram scale salivary RNA as a proof-of-principle example, we describe our progress with a novel poly-A tail independent mRNA amplification strategy combined with the Affymetrix GeneChip Exon arrays. We defined a Salivary Exon Core Transcriptome (SECT) with highly similar expression profiles in healthy individuals verified by quantitative PCR. Informatics analysis of SECT provided important mechanistic insight to their potential origin and function. Finally we demonstrated the diagnostic potential of true exon level expression profiling approach with salivary exon biomarkers that accurately discriminated gender in healthy individuals. Recent studies have demonstrated that discriminatory salivary biomarkers can be readily detected upon the development of systemic diseases such as pancreatic cancer, breast cancer, lung cancer and ovarian cancer. However, the utility of salivary biomarkers for the detection of systemic diseases has been undermined due to the absence of biological and mechanistic rationale why distal diseases from the oral cavity would lead to the development of discriminatory biomarkers in saliva. Here, we examine the hypothesis that pancreatic tumor-derived exosomes are mechanistically involved in the development of pancreatic cancer-discriminatory salivary transcriptomic biomarkers. We first developed a pancreatic cancer mouse model that yielded discriminatory salivary biomarkers by implanting the mouse pancreatic cancer cell line Pan02 into the pancreas of the syngeneic host C57BL/6. The role of pancreatic cancer-derived exosomes in the development of discriminatory salivary biomarkers was then tested by engineered a Pan02 cell line that is suppressed for exosome biogenesis, implanted into the C56BL/6 mouse and examine if the discriminatory salivary biomarker profile was ablated or disrupted. Suppression of exosome biogenesis results in the ablation of discriminatory salivary biomarker development. This study supports that tumor-derived exosomes provide a mechanism in the development of discriminatory biomarkers in saliva and distal systemic diseases. We analyzed saliva from 6 healthy mice and 6 mice with a pancreatic tumor using the Affymetrix Mouse Exon Genome 430 2.0 platform. Array data was processed by dChip. No techinical replicates were performed.
2013-06-12 | E-GEOD-47811 | biostudies-arrayexpress
Project description:Gene expression profiling of FFPE breast cancer samples [Illumina DASL WG platform]
| PRJNA223226 | ENA
Project description:ε-poly-L-lysine (ε-PL) is a high value, widely used natural antimicrobial peptide additive for foods and cosmetic products that is mainly produced by S. albulus. In previous work, we developed the high-yield industrial strain S. albulus WG-608 through successive rounds of engineering. Here, we use integrated physiological, transcriptomic, and proteomics association analysis to resolve the complex mechanisms underlying high ε-PL production by comparing WG-608 with the progenitor strain M-Z18. Our results show that key genes in the glycolysis, glyoxylate, and L-lysine biosynthesis pathways are differentially upregulated in WG-608, while genes in the biosynthetic pathways for fatty acids, various branched amino acids, and secondary metabolite by-products are downregulated. This regulatory pattern results in the introduction of more carbon atoms into L-lysine biosynthesis and ε-PL production. Furthermore, transcriptional and translational upregulation of genes involved in the tricarboxylic acid cycle, oxidative phosphorylation, and pentose phosphate pathway also increase the pools of available NADH, ATP, and NADPH. In addition, significant changes in the regulation of DNA replication, transcription, and translation, two component systems, and quorum sensing may facilitate the adaptability to environmental pressure, thus further regulating the ε-PL biosynthesis. This study enables comprehensive understanding of the biosynthetic mechanisms of ε-PL in S. albulus WG-608, while providing a theoretical foundation development of advanced Streptomycetaceae microbial cell factories.
2023-07-20 | PXD036099 | Pride
Project description:This is a pilot study. We are trying to detect potential salivary biomarkers in mice with a pancreatic tumor. Global gene expression profiling has shown great promise in high-throughput biomarker discovery for early disease detection in body fluids such as saliva, which is accessible, cost-effective, and non-invasive. However, this goal has not been fully realized because saliva, like many clinical samples, contains partially fragmented and degraded RNAs that are difficult to amplify and detect with prevailing technologies. Here, using nanogram scale salivary RNA as a proof-of-principle example, we describe our progress with a novel poly-A tail independent mRNA amplification strategy combined with the Affymetrix GeneChip Exon arrays. We defined a Salivary Exon Core Transcriptome (SECT) with highly similar expression profiles in healthy individuals verified by quantitative PCR. Informatics analysis of SECT provided important mechanistic insight to their potential origin and function. Finally we demonstrated the diagnostic potential of true exon level expression profiling approach with salivary exon biomarkers that accurately discriminated gender in healthy individuals. Recent studies have demonstrated that discriminatory salivary biomarkers can be readily detected upon the development of systemic diseases such as pancreatic cancer, breast cancer, lung cancer and ovarian cancer. However, the utility of salivary biomarkers for the detection of systemic diseases has been undermined due to the absence of biological and mechanistic rationale why distal diseases from the oral cavity would lead to the development of discriminatory biomarkers in saliva. Here, we examine the hypothesis that pancreatic tumor-derived exosomes are mechanistically involved in the development of pancreatic cancer-discriminatory salivary transcriptomic biomarkers. We first developed a pancreatic cancer mouse model that yielded discriminatory salivary biomarkers by implanting the mouse pancreatic cancer cell line Pan02 into the pancreas of the syngeneic host C57BL/6. The role of pancreatic cancer-derived exosomes in the development of discriminatory salivary biomarkers was then tested by engineered a Pan02 cell line that is suppressed for exosome biogenesis, implanted into the C56BL/6 mouse and examine if the discriminatory salivary biomarker profile was ablated or disrupted. Suppression of exosome biogenesis results in the ablation of discriminatory salivary biomarker development. This study supports that tumor-derived exosomes provide a mechanism in the development of discriminatory biomarkers in saliva and distal systemic diseases.
2013-06-12 | GSE47811 | GEO
Project description:This was a prospective observational cohort study involving a convenience sample of previously healthy children <2 years of age with acute RSV infection as well as healthy non-infected age matched controls. The study was conducted at Nationwide Children’s Hospital (NCH; Columbus, OH) during four respiratory seasons, from 2011 to 2015. Children were enrolled at the NCH urgent care clinics, the emergency department or in the inpatient ward or intensive care unit (PICU). For the inpatients enrolled at ward or PICU the median time from admission to sample collection was 21.3h (interquartile range [IQR] 16.7 -37.6h). The majority of children had a confirmatory RSV test (either rapid antigen testing or PCR based) at enrollment per standard of care. In addition, the presence of RSV was confirmed by quantitative real time (qRT)-PCR in all study subjects. Healthy age-matched controls were enrolled during well-child visits or minor elective surgical procedures not involving the respiratory tract as described [Mejias 2013]. Exclusion criteria were as follows: documented bacterial co-infections, premature birth (<36 weeks of gestation), chronic or congenital medical conditions, and immunodeficiency. For healthy controls, additional exclusion criteria included: presence of fever or symptoms of respiratory tract infection within two weeks of enrollment.
2020-04-22 | GSE105450 | GEO
Project description:Microarray expression profiling has become a valuable tool in the evaluation of the genetic consequences of metabolic disease. Although 3’-biased gene expression microarray platforms were the first generation to have widespread availability, newer platforms are gradually emerging that have more up-to-date content and/or higher cost efficiency. Deciphering the relative strengths and weaknesses of these various platforms for metabolic pathway level analyses can be daunting. We sought to determine the practical strengths and weaknesses of four leading commercially-available expression array platforms relative to biologic investigations, as well as assess the feasibility of cross-platform data integration for purposes of biochemical pathway analyses. METHODS: Liver RNA from B6.Alb/cre,Pdss2loxP/loxP mice having primary Coenzyme Q deficiency was extracted either at baseline or following treatment with an antioxidant/antihyperlipidemic agent, probucol. Target RNA samples were prepared and hybridized to Affymetrix 430 2.0, Affymetrix Gene 1.0 ST, Affymetrix Exon 1.0 ST, and Illumina Mouse WG-6 expression arrays. Probes on all platforms were re-mapped to coding sequences in the current version of the mouse genome. Data processing and statistical analysis were performed by R/Bioconductor functions, and pathway analyses were carried out by KEGG Atlas and GSEA. RESULTS: Expression measurements were generally consistent across platforms. However, intensive probe-level comparison suggested that differences in probe locations were a major source of inter-platform variance. In addition, genes expressed at low or intermediate levels had lower inter-platform reproducibility than highly expressed genes. All platforms showed similar patterns of differential expression between sample groups, with ‘steroid biosynthesis’ consistently identified as the most down-regulated metabolic pathway by probucol treatment. CONCLUSIONS: This work offers a timely guide for metabolic disease investigators to enable informed end-user decisions regarding choice of expression microarray platform best-suited to specific research project goals. Successful cross-platform integration of biochemical pathway expression data is also demonstrated, especially for well-annotated and highly-expressed genes. However, integration of gene-level expression data is limited by individual platform probe design and the expression level of target genes. Cross-platform analyses of biochemical pathway data will require additional data processing and novel computational bioinformatics tools to address unique statistical challenges.
2010-01-11 | GSE18677 | GEO