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pmid:32714975

Identification of Differentially Expressed Genes and miRNAs Associated with Esophageal Squamous Cell Carcinoma by Integrated Analysis of Microarray Data.

Lemeng Zhang · Jianhua Chen · Tianli Cheng · Hua Yang · Changqie Pan · Haitao Li

BioMed research international · 2020 doi:10.1155/2020/1980921

Paper

complete

Experiment

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Data

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Analysis

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pmid:32714975
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title
Identification of Differentially Expressed Genes and miRNAs Associated with Esophageal Squamous Cell Carcinoma by Integrated Analysis of Microarray Data.
doi
10.1155/2020/1980921
pmid
32714975
authors array · 6 items
[0]
Lemeng Zhang
[1]
Jianhua Chen
[2]
Tianli Cheng
[3]
Hua Yang
[4]
Changqie Pan
[5]
Haitao Li
journal
BioMed research international
year
2020
abstract
To identify candidate key genes and miRNAs associated with esophageal squamous cell carcinoma (ESCC) development and prognosis, the gene expression profiles and miRNA microarray data including GSE20347, GSE38129, GSE23400, and GSE55856 were downloaded from the Gene Expression Omnibus (GEO) database. Clinical and survival data were retrieved from The Cancer Genome Atlas (TCGA). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of differentially expressed genes (DEGs) was analyzed via DAVID, while the DEG-associated protein-protein interaction network (PPI) was constructed using the STRING database. Additionally, the miRNA target gene regulatory network and miRNA coregulatory network were constructed, using the Cytoscape software. Survival analysis and prognostic model construction were performed via the survival (version 2.42-6) and rbsurv R packages, respectively. The results showed a total of 2575, 2111, and 1205 DEGs, and 226 differentially expressed miRNAs (DEMs) were identified. Pathway enrichment analyses revealed that DEGs were mainly enriched in 36 pathways, such as the proteasome, p53, and beta-alanine metabolism pathways. Furthermore, 448 nodes and 1144 interactions were identified in the PPI network, with MYC having the highest random walk score. In addition, 7 DEMs in the microarray data, including miR-196a, miR-21, miR-205, miR-194, miR-103, miR-223, and miR-375, were found in the regulatory network. Moreover, several reported disease-related miRNAs, including miR-198a, miR-103, miR-223, miR-21, miR-194, and miR-375, were found to have common target genes with other DEMs. Survival analysis revealed that 85 DEMs were related to prognosis, among which hsa-miR-1248, hsa-miR-1291, hsa-miR-421, and hsa-miR-7-5p were used for a prognostic survival model. Taken together, this study revealed the important roles of DEGs and DEMs in ESCC development, as well as DEMs in the prognosis of ESCC. This will provide potential therapeutic targets and prognostic predictors for ESCC.
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In order to integrate the DEGs that were combined in the three datasets, the MetaDE package of R (version: 1.0.5) was used [17].
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sections[5] "2.3. Prediction of DEGs Based on a Meta-analysis" paragraph 2
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In order to integrate the DEGs that were combined in the three datasets, the MetaDE package of R (version: 1.0.5) was used [17].
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sections[24] "Data Availability" paragraph 2
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The data used to support the findings of this study are included within the article.
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Analysis of gene expression in esophageal squamous cell carcinoma (ESCC)
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Global gene expression profiling and validation in esophageal squamous cell carcinoma (ESCC)
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216
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14613
taxon
synthetic construct; Homo sapiens
title
Comprehensive Analysis of Recurrence-Associated Small Non-Coding RNAs in Esophageal Cancer [Affymetrix]
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2026-11-01T15:39:54Z
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In order to integrate the DEGs that were combined in the three datasets, the MetaDE package of R (version: 1.0.5) was used [17].
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The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: hierarchical.
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[0]
The data used to support the findings of this study are included within the article.
basis
The paper names GSE20347, GSE38129, GSE23400, GSE55856 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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minimax
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GEO GSE20347
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[0]
ous Cell Carcinoma by Integrated Analysis of Microarray Data.
[1]
osis, the gene expression profiles and miRNA microarray data including GSE20347, GSE38129, GSE23400,
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andom walk score. In addition, 7 DEMs in the microarray data, including miR-196a, miR-21, miR-205, m
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32714975", "kind": "science-record", "revision": 7, "content_hash": "sha256:f10442135450fce4069e6b61a97534e40f4702986c96c2052ff8ccb703673f9d", "created_at": "2026-11-01T15:41:06Z", "updated_at": "2026-11-01T22:01:57Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Differentially Expressed Genes and miRNAs Associated with Esophageal Squamous Cell Carcinoma by Integrated Analysis of Microarray Data.", "doi": "10.1155/2020/1980921", "pmid": "32714975", "authors": ["Lemeng Zhang", "Jianhua Chen", "Tianli Cheng", "Hua Yang", "Changqie Pan", "Haitao Li"], "journal": "BioMed research international", "year": 2020, "abstract": "To identify candidate key genes and miRNAs associated with esophageal squamous cell carcinoma (ESCC) development and prognosis, the gene expression profiles and miRNA microarray data including GSE20347, GSE38129, GSE23400, and GSE55856 were downloaded from the Gene Expression Omnibus (GEO) database. Clinical and survival data were retrieved from The Cancer Genome Atlas (TCGA). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of differentially expressed genes (DEGs) was analyzed via DAVID, while the DEG-associated protein-protein interaction network (PPI) was constructed using the STRING database. Additionally, the miRNA target gene regulatory network and miRNA coregulatory network were constructed, using the Cytoscape software. Survival analysis and prognostic model construction were performed via the survival (version 2.42-6) and rbsurv R packages, respectively. The results showed a total of 2575, 2111, and 1205 DEGs, and 226 differentially expressed miRNAs (DEMs) were identified. Pathway enrichment analyses revealed that DEGs were mainly enriched in 36 pathways, such as the proteasome, p53, and beta-alanine metabolism pathways. Furthermore, 448 nodes and 1144 interactions were identified in the PPI network, with MYC having the highest random walk score. In addition, 7 DEMs in the microarray data, including miR-196a, miR-21, miR-205, miR-194, miR-103, miR-223, and miR-375, were found in the regulatory network. Moreover, several reported disease-related miRNAs, including miR-198a, miR-103, miR-223, miR-21, miR-194, and miR-375, were found to have common target genes with other DEMs. Survival analysis revealed that 85 DEMs were related to prognosis, among which hsa-miR-1248, hsa-miR-1291, hsa-miR-421, and hsa-miR-7-5p were used for a prognostic survival model. Taken together, this study revealed the important roles of DEGs and DEMs in ESCC development, as well as DEMs in the prognosis of ESCC. This will provide potential therapeutic targets and prognostic predictors for ESCC.", "claims": [{"id": "claim-method", "statement": "In order to integrate the DEGs that were combined in the three datasets, the MetaDE package of R (version: 1.0.5) was used [17].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32714975", "locator": "sections[5] \"2.3. 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This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE20347"], "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:GSE20347"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:32714975", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2020/1980921", "sha256": 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