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pmid:29257318

Identification of key pathways and genes in Barrett's esophagus using integrated bioinformatics methods.

Cong Zhang · Yujie Shen · Jiazheng Wang · Mingxia Zhou · Yingwei Chen

Molecular medicine reports · 2018 doi:10.3892/mmr.2017.8274

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:29257318
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science-record
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2026-11-01T15:40:30Z
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2026-11-01T22:43:12Z
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title
Identification of key pathways and genes in Barrett's esophagus using integrated bioinformatics methods.
doi
10.3892/mmr.2017.8274
pmid
29257318
authors array · 5 items
[0]
Cong Zhang
[1]
Yujie Shen
[2]
Jiazheng Wang
[3]
Mingxia Zhou
[4]
Yingwei Chen
journal
Molecular medicine reports
year
2018
abstract
Barrett's esophagus (BE) is a premalignant lesion of esophageal adenocarcinoma. The aim of the present study was to investigate the possible mechanisms and biomarkers of BE. To identify the differentially expressed microRNAs (DEmiRNAs) and genes (DEGs) in BE, the miRNA expression profile GSE20099 and the gene expression profiles GSE26886, GSE13083 and GSE34619 were obtained from the Gene Expression Omnibus (GEO) database. DEGs and DEmiRNAs were screened for using the GEO2R tool. Using DAVID, functional and pathway enrichment analysis was performed to explore the biological function of identified DEGs. The protein‑protein interaction (PPI) network was detected using STRING and constructed by Cytoscape software. Furthermore, targets of identified DEmiRNAs were predicted by the miRecords database, then integrated with the identified DEGs to obtain key genes involved in BE. In total, 311 DEGs were identified. These genes were significantly enriched in the pancreatic secretion, metabolic pathways and cytochrome P450 drug metabolism pathways. In the PPI network, 16 hub genes, including keratin 16, cystic fibrosis transmembrane conductance regulator, involucrin, protein kinase C α and cadherin 17 were identified. Following integration of the predicted target genes of DEmiRNAs with DEGs, three key BE genes were identified: PRKCA, CDH17 and epiregulin. In conclusion, a comprehensive bioinformatics analysis of identified DEGs and DEmiRNAs was performed to elucidate potential pathways and biomarkers involved in the development of BE.
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GEO2R (http://www.ncbi.nlm.nih.gov/geo/geo2r/) is an online tool that performs comparisons on GEO datasets based on the GEOquery and Limma R packages (9). The BE group and normal group were selected, and the GEO2R program was subsequently applied for differential expression analysis.
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sections[5] "Differential expression analysis" paragraph 2
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GEO2R (http://www.ncbi.nlm.nih.gov/geo/geo2r/) is an online tool that performs comparisons on GEO datasets based on the GEOquery and Limma R packages (9). The BE group and normal group were selected, and the GEO2R program was subsequently applied for differential expression analysis.
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mRNA expression profiles (GSE26886, GSE13083 and GSE34619) and the miRNA expression profile of GSE20099 were downloaded from the GEO data repository. The dataset of GSE26886 contains 20 BE samples and 19 normal esophageal samples.
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sections[4] "Data resources" paragraph 2
quote
mRNA expression profiles (GSE26886, GSE13083 and GSE34619) and the miRNA expression profile of GSE20099 were downloaded from the GEO data repository. The dataset of GSE26886 contains 20 BE samples and 19 normal esophageal samples.
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The paper used the GEO2R tool to analyze DEGs and DEmiRNAs, with source expression data obtained from the Gene Expression Omnibus (GEO) database using GSE20099 and GSE26886, GSE13083 and GSE34619.
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sections[0] "Abstract" paragraph 1
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To identify the differentially expressed microRNAs (DEmiRNAs) and genes (DEGs) in BE, the miRNA expression profile GSE20099 and the gene expression profiles GSE26886, GSE13083 and GSE34619 were obtained from the Gene Expression Omnibus (GEO) database.
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DEGs and DEmiRNAs were screened for using the GEO2R tool.
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The paper used the GEO2R tool to analyze DEGs and DEmiRNAs, with source expression data obtained from the Gene Expression Omnibus (GEO) database using GSE20099 and GSE26886, GSE13083 and GSE34619.
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mRNA expression profiles (GSE26886, GSE13083 and GSE34619) and the miRNA expression profile of GSE20099 were downloaded from the GEO data repository. The dataset of GSE26886 contains 20 BE samples and 19 normal esophageal samples.
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mRNA expression profiles (GSE26886, GSE13083 and GSE34619) and the miRNA expression profile of GSE20099 were downloaded from the GEO data repository. The dataset of GSE26886 contains 20 BE samples and 19 normal esophageal samples.
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Barrett's vs Normal esophagus vs small intestine comparison
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51
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null
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8871
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Homo sapiens; Mus musculus
title
microRNA/UCR expression profiling of human Barrett's carcinogenesis
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2026-11-01T15:39:54Z
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mRNA expression profiles (GSE26886, GSE13083 and GSE34619) and the miRNA expression profile of GSE20099 were downloaded from the GEO data repository. The dataset of GSE26886 contains 20 BE samples and 19 normal esophageal samples.
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mRNA expression profiles (GSE26886, GSE13083 and GSE34619) and the miRNA expression profile of GSE20099 were downloaded from the GEO data repository. The dataset of GSE26886 contains 20 BE samples and 19 normal esophageal samples.
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69
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null
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570
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Homo sapiens
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Gene expression profiling of Barrett's esophagus, adenocarcinoma, esophageal squamous epithelium and squamous cell carcinoma
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2026-11-01T15:39:54Z
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mRNA expression profiles (GSE26886, GSE13083 and GSE34619) and the miRNA expression profile of GSE20099 were downloaded from the GEO data repository. The dataset of GSE26886 contains 20 BE samples and 19 normal esophageal samples.
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6244
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Homo sapiens
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Gene expression profile in Barrett's esopahgus
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GEO2R (http://www.ncbi.nlm.nih.gov/geo/geo2r/) is an online tool that performs comparisons on GEO datasets based on the GEOquery and Limma R packages (9). The BE group and normal group were selected, and the GEO2R program was subsequently applied for differential expression analysis.
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mRNA expression profiles (GSE26886, GSE13083 and GSE34619) and the miRNA expression profile of GSE20099 were downloaded from the GEO data repository. The dataset of GSE26886 contains 20 BE samples and 19 normal esophageal samples.
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GEO GSE13083
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GEO2R (http://www.ncbi.nlm.nih.gov/geo/geo2r/) is an online tool that performs comparisons on GEO datasets based on the GEOquery and Limma R packages (9). The BE group and normal group were selected, and the GEO2R program was subsequently applied for differential expression analysis.
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To identify the differentially expressed microRNAs (DEmiRNAs) and genes (DEGs) in BE, the miRNA expression profile GSE20099 and the gene expression profiles GSE26886, GSE13083 and GSE34619 were obtained from the Gene Expression Omnibus (GEO) database. DEGs and DEmiRNAs were screened for using the GEO2R tool. Using DAVID, functional and pathway enrichment analysis was performed to explore the biological function of identified DEGs. The protein‑protein interaction (PPI) network was detected using STRING and constructed by Cytoscape software. Furthermore, targets of identified DEmiRNAs were predicted by the miRecords database, then integrated with the identified DEGs to obtain key genes involved in BE. In total, 311 DEGs were identified. These genes were significantly enriched in the pancreatic secretion, metabolic pathways and cytochrome P450 drug metabolism pathways. In the PPI network, 16 hub genes, including keratin 16, cystic fibrosis transmembrane conductance regulator, involucrin, protein kinase C α and cadherin 17 were identified. Following integration of the predicted target genes of DEmiRNAs with DEGs, three key BE genes were identified: PRKCA, CDH17 and epiregulin. In conclusion, a comprehensive bioinformatics analysis of identified DEGs and DEmiRNAs was performed to elucidate potential pathways and biomarkers involved in the development of BE.", "claims": [{"id": "claim-method", "statement": "GEO2R (http://www.ncbi.nlm.nih.gov/geo/geo2r/) is an online tool that performs comparisons on GEO datasets based on the GEOquery and Limma R packages (9). 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