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pmid:28943905

Screening the key genes of hepatocellular adenoma via microarray analysis of DNA expression and methylation profiles.

Dan Liu · Pengfei Liu · Liye Cao · Quan Zhang · Yaqing Chen

Oncology letters · 2017 doi:10.3892/ol.2017.6673

Paper

complete

Experiment

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Data

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Analysis

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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title
Screening the key genes of hepatocellular adenoma via microarray analysis of DNA expression and methylation profiles.
doi
10.3892/ol.2017.6673
pmid
28943905
authors array · 5 items
[0]
Dan Liu
[1]
Pengfei Liu
[2]
Liye Cao
[3]
Quan Zhang
[4]
Yaqing Chen
journal
Oncology letters
year
2017
abstract
The aim of the present study was to identify the biomarkers involved in the development of hepatocellular adenoma (HCA) through integrated analysis of gene expression and methylation microarray. The microarray dataset GSE7473, containing HNF1α-mutated HCA and their corresponding non-tumor livers, 5 HNF1α-mutated HCA and 4 non-related non-tumor livers, was downloaded from the Gene Expression Omnibus (GEO) database. The DNA methylation profile GSE43091, consisting of 50 HCA and 4 normal liver tissues, was also downloaded from the GEO database. Differentially expressed genes (DEGs) were identified by the limma package of R. A t-test was conducted on the differentially methylated sites. Functional enrichment analysis of DEGs was performed through the Database for Annotation, Visualization and Integrated Analysis. The genes corresponding to the differentially methylated sites were obtained by the annotation files of methylation chip platform. A total of 182 DEGs and 3,902 differentially methylated sites were identified in HCA. In addition, 238 enriched GO terms, including organic acid metabolic process and carboxylic acid metabolic process, and 14 KEGG pathways, including chemical carcinogenesis, were identified. Furthermore, 12 DEGs were identified to contain differentially methylated sites, among which, 8 overlapped genes, including pregnancy zone protein and solute carrier family 22 member 1 (SLC22A1), exhibited inverse associations between gene expression levels and DNA methylation levels. The DNA methylation levels may be potential targets of HCA. The present study revealed that the 8 overlapped genes, including annexin A2, chitinase 3-like 1, fibroblast growth factor receptor 4, mal, T-cell differentiation protein like, palladin, cytoskeletal associated protein, plasmalemma vesicle associated protein and SLC22A1, may be potential therapeutic targets of HCA.
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DEGs were identified using the limma package of R with P<0.05 and |log2 (fold-change)|>1.
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The gene expression profile (GSE7473) contained 41 samples, including 8 HNF1α-mutated HCA and the corresponding non-tumor liver samples (each sample was assessed four times using 11K_VJF-ARRAY; GPL3282), and 5 HNF1α-mutated HCA and 4 non-related non-tumor liver samples (the 9 samples were assessed using GPL96 Affymetrix Human Genome U133A Array).
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sections[4] "Microarray data" paragraph 2
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The gene expression profile (GSE7473) contained 41 samples, including 8 HNF1α-mutated HCA and the corresponding non-tumor liver samples (each sample was assessed four times using 11K_VJF-ARRAY; GPL3282), and 5 HNF1α-mutated HCA and 4 non-related non-tumor liver samples (the 9 samples were assessed using GPL96 Affymetrix Human Genome U133A Array).
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The study used the limma package of R to identify DEGs and a t-test to identify differentially methylated sites using GEO datasets GSE7473 and GSE43091; the headline result was 182 DEGs, 3,902 differentially methylated sites, and eight genes showing inverse associations between gene expression and DNA methylation.
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The microarray dataset GSE7473, containing HNF1α-mutated HCA and their corresponding non-tumor livers, 5 HNF1α-mutated HCA and 4 non-related non-tumor livers, was downloaded from the Gene Expression Omnibus (GEO) database.
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The DNA methylation profile GSE43091, consisting of 50 HCA and 4 normal liver tissues, was also downloaded from the GEO database.
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Differentially expressed genes (DEGs) were identified by the limma package of R.
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sections[0] "Abstract" paragraph 1
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A t-test was conducted on the differentially methylated sites.
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sections[0] "Abstract" paragraph 1
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A total of 182 DEGs and 3,902 differentially methylated sites were identified in HCA.
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sections[0] "Abstract" paragraph 1
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Furthermore, 12 DEGs were identified to contain differentially methylated sites, among which, 8 overlapped genes, including pregnancy zone protein and solute carrier family 22 member 1 (SLC22A1), exhibited inverse associations between gene expression levels and DNA methylation levels.
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The study used the limma package of R to identify DEGs and a t-test to identify differentially methylated sites using GEO datasets GSE7473 and GSE43091; the headline result was 182 DEGs, 3,902 differentially methylated sites, and eight genes showing inverse associations between gene expression and DNA methylation.
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Genome-scale methylome profiling of hepatocellular adenomas.
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HNF1-alpha inactivation promotes lipogenesis in human hepatocellular adenoma independently of SREBP1 & ChREBP activation
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Top 20 enriched GO terms for differentially expressed genes.
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The gene expression profile (GSE7473) contained 41 samples, including 8 HNF1α-mutated HCA and the corresponding non-tumor liver samples (each sample was assessed four times using 11K_VJF-ARRAY; GPL3282), and 5 HNF1α-mutated HCA and 4 non-related non-tumor liver samples (the 9 samples were assessed using GPL96 Affymetrix Human Genome U133A Array).
basis
The paper names GSE7473, GSE43091 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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the key genes of hepatocellular adenoma via microarray analysis of DNA expression and methylation p
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analysis of gene expression and methylation microarray. The microarray dataset GSE7473, containing
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e expression and methylation microarray. The microarray dataset GSE7473, containing HNF1α-mutated HC
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Complete file
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The microarray dataset GSE7473, containing HNF1α-mutated HCA and their corresponding non-tumor livers, 5 HNF1α-mutated HCA and 4 non-related non-tumor livers, was downloaded from the Gene Expression Omnibus (GEO) database. The DNA methylation profile GSE43091, consisting of 50 HCA and 4 normal liver tissues, was also downloaded from the GEO database. Differentially expressed genes (DEGs) were identified by the limma package of R. A t-test was conducted on the differentially methylated sites. Functional enrichment analysis of DEGs was performed through the Database for Annotation, Visualization and Integrated Analysis. The genes corresponding to the differentially methylated sites were obtained by the annotation files of methylation chip platform. A total of 182 DEGs and 3,902 differentially methylated sites were identified in HCA. In addition, 238 enriched GO terms, including organic acid metabolic process and carboxylic acid metabolic process, and 14 KEGG pathways, including chemical carcinogenesis, were identified. Furthermore, 12 DEGs were identified to contain differentially methylated sites, among which, 8 overlapped genes, including pregnancy zone protein and solute carrier family 22 member 1 (SLC22A1), exhibited inverse associations between gene expression levels and DNA methylation levels. The DNA methylation levels may be potential targets of HCA. The present study revealed that the 8 overlapped genes, including annexin A2, chitinase 3-like 1, fibroblast growth factor receptor 4, mal, T-cell differentiation protein like, palladin, cytoskeletal associated protein, plasmalemma vesicle associated protein and SLC22A1, may be potential therapeutic targets of HCA.", "claims": [{"id": "claim-method", "statement": "DEGs were identified using the limma package of R with P<0.05 and |log2 (fold-change)|>1.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:28943905", "locator": "sections[6] \"Identification of differentially methylated sites and differentially expressed genes (DEGs)\" paragraph 2", "quote": "DEGs were identified using the limma package of R with P<0.05 and |log2 (fold-change)|>1."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The gene expression profile (GSE7473) contained 41 samples, including 8 HNF1α-mutated HCA and the corresponding non-tumor liver samples (each sample was assessed four times using 11K_VJF-ARRAY; GPL3282), and 5 HNF1α-mutated HCA and 4 non-related non-tumor liver samples (the 9 samples were assessed using GPL96 Affymetrix Human Genome U133A Array).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:28943905", "locator": "sections[4] \"Microarray data\" paragraph 2", "quote": "The gene expression profile (GSE7473) contained 41 samples, including 8 HNF1α-mutated HCA and the corresponding non-tumor liver samples (each sample was assessed four times using 11K_VJF-ARRAY; GPL3282), and 5 HNF1α-mutated HCA and 4 non-related non-tumor liver samples (the 9 samples were assessed using GPL96 Affymetrix Human Genome U133A Array)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study used the limma package of R to identify DEGs and a t-test to identify differentially methylated sites using GEO datasets GSE7473 and GSE43091; the headline result was 182 DEGs, 3,902 differentially methylated sites, and eight genes showing inverse associations between gene expression and DNA methylation.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:28943905", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The microarray dataset GSE7473, containing HNF1α-mutated HCA and their corresponding non-tumor livers, 5 HNF1α-mutated HCA and 4 non-related non-tumor livers, was downloaded from the Gene Expression Omnibus (GEO) database."}, {"asset": "source:pmid:28943905", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The DNA methylation profile GSE43091, consisting of 50 HCA and 4 normal liver tissues, was also downloaded from the GEO database."}, {"asset": "source:pmid:28943905", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Differentially expressed genes (DEGs) were identified by the limma package of R."}, {"asset": "source:pmid:28943905", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "A t-test was conducted on the differentially methylated sites."}, {"asset": "source:pmid:28943905", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "A total of 182 DEGs and 3,902 differentially methylated sites were identified in HCA."}, {"asset": "source:pmid:28943905", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Furthermore, 12 DEGs were identified to contain differentially methylated sites, among which, 8 overlapped genes, including pregnancy zone protein and solute carrier family 22 member 1 (SLC22A1), exhibited inverse associations between gene expression levels and DNA methylation levels."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study used the limma package of R to identify DEGs and a t-test to identify differentially methylated sites using GEO datasets GSE7473 and GSE43091; the headline result was 182 DEGs, 3,902 differentially methylated sites, and eight genes showing inverse associations between gene expression and DNA methylation.", "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:28943905"], "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. 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