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pmid:30100738

Identification of prognostic risk factors for esophageal adenocarcinoma using bioinformatics analysis.

Zhiyu Dong · Junwen Wang · Tingting Zhan · Shuchang Xu

OncoTargets and therapy · 2018 doi:10.2147/OTT.S156716

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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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pmid:30100738
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sha256:813922ec9c35a89528b96965e79f7e0a295147478926b5cb0357db802b91858c
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2026-11-01T15:40:36Z
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2026-11-01T21:59:59Z
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title
Identification of prognostic risk factors for esophageal adenocarcinoma using bioinformatics analysis.
doi
10.2147/OTT.S156716
pmid
30100738
authors array · 4 items
[0]
Zhiyu Dong
[1]
Junwen Wang
[2]
Tingting Zhan
[3]
Shuchang Xu
journal
OncoTargets and therapy
year
2018
abstract
PURPOSE: Esophageal adenocarcinoma (EAC) is the most common type of esophageal cancer in Western countries. It is usually detected at an advanced stage and has a poor prognosis. The aim of this study was to identify key genes and miRNAs in EAC. METHODS: The mRNA microarray data sets GSE1420, GSE26886, and GSE92396 and miRNA data set GSE16456 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were obtained using R software. Functional enrichment analysis was performed using the DAVID database. A protein-protein interaction (PPI) network and functional modules were established using the STRING database and visualized by Cytoscape. The targets of the DEMs were predicted using the miRecords database, and overlapping genes between DEGs and targets were identified. The prognosis-related overlapping genes were identified using Kaplan-Meier analysis and Cox proportional hazard analysis based on The Cancer Genome Atlas (TCGA) database. The differential expression of these prognosis-related genes was validated using the expression matrix in the TCGA database. RESULTS: Seven hundred and fifteen DEGs were obtained, consisting of 313 upregulated and 402 downregulated genes. The PPI network consisted of 281 nodes; 683 edges were constructed and 3 functional modules were established. Forty-four overlapping genes and 56 miRNA- mRNA pairs were identified. Five genes, FAM46A, RAB15, SLC20A1, IL1A, and ACSL1, were associated with overall survival or relapse-free survival. FAM46A and IL1A were found to be independent prognostic indicators for overall survival, and FAM46A, RAB15, and SLC20A1 were considered independent prognostic indicators for relapse-free survival. Among them, the overexpression of RAB15 and SLC20A1 and lower expression of ACSL1 were also identified in EAC tissues based on the expression matrix in the TCGA database. CONCLUSION: These prognosis-related genes and differentially expressed miRNA have provided potential biomarkers for EAC diagnosis and treatment.
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The mRNA transcript per million of 89 EAC tissue samples and corresponding clinical parameters and follow-up information for these patients were downloaded from UCSC Xena (https://xenabrowser.net/datapages/?host=https://tcga.xenahubs.net), an integrated online tool based on The Cancer Genome Atlas (TCGA) database.18 Kaplan–Meier analyses were performed in Survival package (https://CRAN.R-project.org/package=survival)19 in R software to explore the prognostic value of DEM-targeted DEGs based on overall survival and relapse-free survival.
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sections[9] "Kaplan–Meier analysis of DEM-targeted DEGs" paragraph 2
quote
The mRNA transcript per million of 89 EAC tissue samples and corresponding clinical parameters and follow-up information for these patients were downloaded from UCSC Xena (https://xenabrowser.net/datapages/?host=https://tcga.xenahubs.net), an integrated online tool based on The Cancer Genome Atlas (TCGA) database.18 Kaplan–Meier analyses were performed in Survival package (https://CRAN.R-project.org/package=survival)19 in R software to explore the prognostic value of DEM-targeted DEGs based on overall survival and relapse-free survival.
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The mRNA transcript per million of 89 EAC tissue samples and corresponding clinical parameters and follow-up information for these patients were downloaded from UCSC Xena (https://xenabrowser.net/datapages/?host=https://tcga.xenahubs.net), an integrated online tool based on The Cancer Genome Atlas (TCGA) database.
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sections[9] "Kaplan–Meier analysis of DEM-targeted DEGs" paragraph 2
quote
The mRNA transcript per million of 89 EAC tissue samples and corresponding clinical parameters and follow-up information for these patients were downloaded from UCSC Xena (https://xenabrowser.net/datapages/?host=https://tcga.xenahubs.net), an integrated online tool based on The Cancer Genome Atlas (TCGA) database.
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The paper obtained DEGs and DEMs using R software from three GEO mRNA microarray datasets and one GEO miRNA dataset, identifying five genes associated with overall or relapse-free survival in EAC.
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sections[0] "Abstract" paragraph 2
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The mRNA microarray data sets GSE1420, GSE26886, and GSE92396 and miRNA data set GSE16456 were downloaded from the Gene Expression Omnibus database.
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sections[0] "Abstract" paragraph 2
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Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were obtained using R software.
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sections[0] "Abstract" paragraph 3
quote
Five genes, FAM46A, RAB15, SLC20A1, IL1A, and ACSL1, were associated with overall survival or relapse-free survival.
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The paper obtained DEGs and DEMs using R software from three GEO mRNA microarray datasets and one GEO miRNA dataset, identifying five genes associated with overall or relapse-free survival in EAC.
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Univariate and multivariate analyses of overall survival in esophageal adenocarcinoma patients
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Cox proportional hazard analysis
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Univariate and multivariate analyses of overall survival in esophageal adenocarcinoma patients
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Univariate and multivariate analyses of recurrence-free survival in esophageal adenocarcinoma patients
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Significantly enriched GO biological process terms and KEGG pathways
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Functional enrichment analysis
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Significantly enriched GO biological process terms and KEGG pathways
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[3]
3.36×10−10
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[1]
ECM organization
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7.97×10−10
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ECM disassembly
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9.49×10−7
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Type I interferon signaling pathway
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1.96×10−5
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[3]
6.05×10−5
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[1]
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27
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2.14×10−4
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[1]
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[3]
8.00×10−3
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9.18×10−3
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[1]
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[2]
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[3]
4.89×10−11
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[1]
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[3]
1.70×10−5
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[3]
1.99×10−5
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[3]
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PPI network analysis
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Significantly enriched GO terms and KEGG pathways for modules
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9.86×10−12
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6
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Univariate and multivariate analyses of overall survival in esophageal adenocarcinoma patients
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Cox proportional hazard analysis
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Univariate and multivariate analyses of overall survival in esophageal adenocarcinoma patients
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caption
Univariate and multivariate analyses of recurrence-free survival in esophageal adenocarcinoma patients
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The mRNA transcript per million of 89 EAC tissue samples and corresponding clinical parameters and follow-up information for these patients were downloaded from UCSC Xena (https://xenabrowser.net/datapages/?host=https://tcga.xenahubs.net), an integrated online tool based on The Cancer Genome Atlas (TCGA) database.18 Kaplan–Meier analyses were performed in Survival package (https://CRAN.R-project.org/package=survival)19 in R software to explore the prognostic value of DEM-targeted DEGs based on overall survival and relapse-free survival.
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The aim of this study was to identify key genes and miRNAs in EAC.\nMETHODS: The mRNA microarray data sets GSE1420, GSE26886, and GSE92396 and miRNA data set GSE16456 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were obtained using R software. Functional enrichment analysis was performed using the DAVID database. A protein-protein interaction (PPI) network and functional modules were established using the STRING database and visualized by Cytoscape. The targets of the DEMs were predicted using the miRecords database, and overlapping genes between DEGs and targets were identified. The prognosis-related overlapping genes were identified using Kaplan-Meier analysis and Cox proportional hazard analysis based on The Cancer Genome Atlas (TCGA) database. The differential expression of these prognosis-related genes was validated using the expression matrix in the TCGA database.\nRESULTS: Seven hundred and fifteen DEGs were obtained, consisting of 313 upregulated and 402 downregulated genes. The PPI network consisted of 281 nodes; 683 edges were constructed and 3 functional modules were established. Forty-four overlapping genes and 56 miRNA- mRNA pairs were identified. Five genes, FAM46A, RAB15, SLC20A1, IL1A, and ACSL1, were associated with overall survival or relapse-free survival. FAM46A and IL1A were found to be independent prognostic indicators for overall survival, and FAM46A, RAB15, and SLC20A1 were considered independent prognostic indicators for relapse-free survival. Among them, the overexpression of RAB15 and SLC20A1 and lower expression of ACSL1 were also identified in EAC tissues based on the expression matrix in the TCGA database.\nCONCLUSION: These prognosis-related genes and differentially expressed miRNA have provided potential biomarkers for EAC diagnosis and treatment.", "claims": [{"id": "claim-method", "statement": "The mRNA transcript per million of 89 EAC tissue samples and corresponding clinical parameters and follow-up information for these patients were downloaded from UCSC Xena (https://xenabrowser.net/datapages/?host=https://tcga.xenahubs.net), an integrated online tool based on The Cancer Genome Atlas (TCGA) database.18 Kaplan–Meier analyses were performed in Survival package (https://CRAN.R-project.org/package=survival)19 in R software to explore the prognostic value of DEM-targeted DEGs based on overall survival and relapse-free survival.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:30100738", "locator": "sections[9] \"Kaplan–Meier analysis of DEM-targeted DEGs\" paragraph 2", "quote": "The mRNA transcript per million of 89 EAC tissue samples and corresponding clinical parameters and follow-up information for these patients were downloaded from UCSC Xena (https://xenabrowser.net/datapages/?host=https://tcga.xenahubs.net), an integrated online tool based on The Cancer Genome Atlas (TCGA) database.18 Kaplan–Meier analyses were performed in Survival package (https://CRAN.R-project.org/package=survival)19 in R software to explore the prognostic value of DEM-targeted DEGs based on overall survival and relapse-free survival."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The mRNA transcript per million of 89 EAC tissue samples and corresponding clinical parameters and follow-up information for these patients were downloaded from UCSC Xena (https://xenabrowser.net/datapages/?host=https://tcga.xenahubs.net), an integrated online tool based on The Cancer Genome Atlas (TCGA) database.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:30100738", "locator": "sections[9] \"Kaplan–Meier analysis of DEM-targeted DEGs\" paragraph 2", "quote": "The mRNA transcript per million of 89 EAC tissue samples and corresponding clinical parameters and follow-up information for these patients were downloaded from UCSC Xena (https://xenabrowser.net/datapages/?host=https://tcga.xenahubs.net), an integrated online tool based on The Cancer Genome Atlas (TCGA) database."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The paper obtained DEGs and DEMs using R software from three GEO mRNA microarray datasets and one GEO miRNA dataset, identifying five genes associated with overall or relapse-free survival in EAC.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:30100738", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The mRNA microarray data sets GSE1420, GSE26886, and GSE92396 and miRNA data set GSE16456 were downloaded from the Gene Expression Omnibus database."}, {"asset": "source:pmid:30100738", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were obtained using R software."}, {"asset": "source:pmid:30100738", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Five genes, FAM46A, RAB15, SLC20A1, IL1A, and ACSL1, were associated with overall survival or relapse-free survival."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "The paper obtained DEGs and DEMs using R software from three GEO mRNA microarray datasets and one GEO miRNA dataset, identifying five genes associated with overall or relapse-free survival in EAC.", "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:30100738"], "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": "blocked", "blocked_on": "data:accession_absent", "description": "The GEO series accession resolves and its sample accessions are listed. 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