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pmid:29113243

Differential gene expression analysis in glioblastoma cells and normal human brain cells based on GEO database.

Anping Wang · Guibin Zhang

Oncology letters · 2017 doi:10.3892/ol.2017.6922

Paper

complete

Experiment

complete

Data

partial

Analysis

complete

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:29113243
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science-record
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https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json
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2026-11-01T15:40:29Z
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paper object · 10 fields
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title
Differential gene expression analysis in glioblastoma cells and normal human brain cells based on GEO database.
doi
10.3892/ol.2017.6922
pmid
29113243
authors array · 2 items
[0]
Anping Wang
[1]
Guibin Zhang
journal
Oncology letters
year
2017
abstract
The differentially expressed genes between glioblastoma (GBM) cells and normal human brain cells were investigated to performed pathway analysis and protein interaction network analysis for the differentially expressed genes. GSE12657 and GSE42656 gene chips, which contain gene expression profile of GBM were obtained from Gene Expression Omniub (GEO) database of National Center for Biotechnology Information (NCBI). The 'limma' data packet in 'R' software was used to analyze the differentially expressed genes in the two gene chips, and gene integration was performed using 'RobustRankAggreg' package. Finally, pheatmap software was used for heatmap analysis and Cytoscape, DAVID, STRING and KOBAS were used for protein-protein interaction, Gene Ontology (GO) and KEGG analyses. As results: i) 702 differentially expressed genes were identified in GSE12657, among those genes, 548 were significantly upregulated and 154 were significantly downregulated (p<0.01, fold-change >1), and 1,854 differentially expressed genes were identified in GSE42656, among the genes, 1,068 were significantly upregulated and 786 were significantly downregulated (p<0.01, fold-change >1). A total of 167 differentially expressed genes including 100 upregulated genes and 67 downregulated genes were identified after gene integration, and the genes showed significantly different expression levels in GBM compared with normal human brain cells (p<0.05). ii) Interactions between the protein products of 101 differentially expressed genes were identified using STRING and expression network was established. A key gene, called CALM3, was identified by Cytoscape software. iii) GO enrichment analysis showed that differentially expressed genes were mainly enriched in 'neurotransmitter:sodium symporter activity' and 'neurotransmitter transporter activity', which can affect the activity of neurotransmitter transportation. KEGG pathway analysis showed that the differentially expressed genes were mainly enriched in 'protein processing in endoplasmic reticulum', which can affect protein processing in endoplasmic reticulum. The results showed that: i) 167 differentially expressed genes were identified from two gene chips after integration; and ii) protein interaction network was established, and GO and KEGG pathway analyses were successfully performed to identify and annotate the key gene, which provide new insights for the studies on GBN at gene level.
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Microarray data analysis package (Linear Models for Microarray Data, Limma) in ‘R’ software was used to screen the differentially expressed genes from raw data of two gene chips.
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sections[4] "Gene expression profile data" paragraph 3
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Microarray data analysis package (Linear Models for Microarray Data, Limma) in ‘R’ software was used to screen the differentially expressed genes from raw data of two gene chips.
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sections[4] "Gene expression profile data" paragraph 2
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GSE12657 was from Neuropathology in the Department of Medicine at Imperial College London with 7 cases of GBM patients as experimental group and 5 cases of normal samples as a control group.
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The study used the limma R package to analyze differentially expressed genes from GSE12657 and GSE42656 obtained from the NCBI GEO database, identifying 167 integrated differentially expressed genes in glioblastoma versus normal human brain cells.
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A total of 167 differentially expressed genes including 100 upregulated genes and 67 downregulated genes were identified after gene integration, and the genes showed significantly different expression levels in GBM compared with normal human brain cells (p<0.05).
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The ‘limma’ data packet in ‘R’ software was used to analyze the differentially expressed genes in the two gene chips, and gene integration was performed using ‘RobustRankAggreg’ package.
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sections[0] "Abstract" paragraph 1
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GSE12657 and GSE42656 gene chips, which contain gene expression profile of GBM were obtained from Gene Expression Omniub (GEO) database of National Center for Biotechnology Information (NCBI).
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A total of 167 differentially expressed genes including 100 upregulated genes and 67 downregulated genes were identified after gene integration, and the genes showed significantly different expression levels in GBM compared with normal human brain cells (p<0.05).
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The study used the limma R package to analyze differentially expressed genes from GSE12657 and GSE42656 obtained from the NCBI GEO database, identifying 167 integrated differentially expressed genes in glioblastoma versus normal human brain cells.
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Expression data from human glioma samples
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Gene expression profiles for paediatric brain tumours
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Results of KEGG pathway analysis.
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Results of KEGG pathway analysis.
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Microarray data analysis package (Linear Models for Microarray Data, Limma) in ‘R’ software was used to screen the differentially expressed genes from raw data of two gene chips.
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differential_expression_fit
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source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
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Microarray data analysis package (Linear Models for Microarray Data, Limma) in ‘R’ software was used to screen the differentially expressed genes from raw data of two gene chips.
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Complete file
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GSE12657 and GSE42656 gene chips, which contain gene expression profile of GBM were obtained from Gene Expression Omniub (GEO) database of National Center for Biotechnology Information (NCBI). The 'limma' data packet in 'R' software was used to analyze the differentially expressed genes in the two gene chips, and gene integration was performed using 'RobustRankAggreg' package. Finally, pheatmap software was used for heatmap analysis and Cytoscape, DAVID, STRING and KOBAS were used for protein-protein interaction, Gene Ontology (GO) and KEGG analyses. As results: i) 702 differentially expressed genes were identified in GSE12657, among those genes, 548 were significantly upregulated and 154 were significantly downregulated (p<0.01, fold-change >1), and 1,854 differentially expressed genes were identified in GSE42656, among the genes, 1,068 were significantly upregulated and 786 were significantly downregulated (p<0.01, fold-change >1). A total of 167 differentially expressed genes including 100 upregulated genes and 67 downregulated genes were identified after gene integration, and the genes showed significantly different expression levels in GBM compared with normal human brain cells (p<0.05). ii) Interactions between the protein products of 101 differentially expressed genes were identified using STRING and expression network was established. A key gene, called CALM3, was identified by Cytoscape software. iii) GO enrichment analysis showed that differentially expressed genes were mainly enriched in 'neurotransmitter:sodium symporter activity' and 'neurotransmitter transporter activity', which can affect the activity of neurotransmitter transportation. KEGG pathway analysis showed that the differentially expressed genes were mainly enriched in 'protein processing in endoplasmic reticulum', which can affect protein processing in endoplasmic reticulum. The results showed that: i) 167 differentially expressed genes were identified from two gene chips after integration; and ii) protein interaction network was established, and GO and KEGG pathway analyses were successfully performed to identify and annotate the key gene, which provide new insights for the studies on GBN at gene level.", "claims": [{"id": "claim-method", "statement": "Microarray data analysis package (Linear Models for Microarray Data, Limma) in ‘R’ software was used to screen the differentially expressed genes from raw data of two gene chips.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:29113243", "locator": "sections[4] \"Gene expression profile data\" paragraph 3", "quote": "Microarray data analysis package (Linear Models for Microarray Data, Limma) in ‘R’ software was used to screen the differentially expressed genes from raw data of two gene chips."}], "state": "complete"}, {"id": "claim-data-access", "statement": "GSE12657 was from Neuropathology in the Department of Medicine at Imperial College London with 7 cases of GBM patients as experimental group and 5 cases of normal samples as a control group.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:29113243", "locator": "sections[4] \"Gene expression profile data\" paragraph 2", "quote": "GSE12657 was from Neuropathology in the Department of Medicine at Imperial College London with 7 cases of GBM patients as experimental group and 5 cases of normal samples as a control group."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study used the limma R package to analyze differentially expressed genes from GSE12657 and GSE42656 obtained from the NCBI GEO database, identifying 167 integrated differentially expressed genes in glioblastoma versus normal human brain cells.", "kind": "quantitative", "target": {"value": 0.05, "unit": "p-value", "tolerance": null, "source": "A total of 167 differentially expressed genes including 100 upregulated genes and 67 downregulated genes were identified after gene integration, and the genes showed significantly different expression levels in GBM compared with normal human brain cells (p<0.05)."}, "evidence": [{"asset": "source:pmid:29113243", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The ‘limma’ data packet in ‘R’ software was used to analyze the differentially expressed genes in the two gene chips, and gene integration was performed using ‘RobustRankAggreg’ package."}, {"asset": "source:pmid:29113243", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "GSE12657 and GSE42656 gene chips, which contain gene expression profile of GBM were obtained from Gene Expression Omniub (GEO) database of National Center for Biotechnology Information (NCBI)."}, {"asset": "source:pmid:29113243", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "A total of 167 differentially expressed genes including 100 upregulated genes and 67 downregulated genes were identified after gene integration, and the genes showed significantly different expression levels in GBM compared with normal human brain cells (p<0.05)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study used the limma R package to analyze differentially expressed genes from GSE12657 and GSE42656 obtained from the NCBI GEO database, identifying 167 integrated differentially expressed genes in glioblastoma versus normal human brain cells.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:29113243"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE12657"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE12657"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:29113243", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3892/ol.2017.6922", "sha256": 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