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pmid:32606769

Identification of Potential Key Genes and Pathways for Inflammatory Breast Cancer Based on GEO and TCGA Databases.

Qing Lv · Yansong Liu · Hu Huang · Mingjie Zhu · Junqiang Wu · Dong Meng

OncoTargets and therapy · 2020 doi:10.2147/OTT.S255300

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title
Identification of Potential Key Genes and Pathways for Inflammatory Breast Cancer Based on GEO and TCGA Databases.
doi
10.2147/OTT.S255300
pmid
32606769
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Qing Lv
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Yansong Liu
[2]
Hu Huang
[3]
Mingjie Zhu
[4]
Junqiang Wu
[5]
Dong Meng
journal
OncoTargets and therapy
year
2020
abstract
INTRODUCTION: Inflammatory breast cancer (IBC) is a rare type of breast cancer with poor prognosis, and the pathogenesis of this life-threatening disease is yet to be fully elucidated. This study aims to identify key genes of IBC, which could be potential diagnostic or therapeutic targets. METHODS: Four datasets GSE5847, GSE22597, GSE23720, and GSE45581 were downloaded from the Gene Expression Omnibus (GEO) and differential expression analysis was performed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to understand the potential bio-functions of the differentially expressed genes (DEGs). Protein-protein interaction (PPI) network was constructed for functional modules analysis and hub genes identification, and TCGA survival analysis and qRT-PCR of clinical samples were used to further explore and validate the effect of hub genes on IBC. RESULTS: A total of 114 DEGs were identified from the GEO datasets. GO and KEGG analyses showed that the DEGs were mainly enriched in oncogenesis and cell adhesion. From the PPI network, we screened out five hub genes, including PTPRC, IL6, SELL, CD40, and SPN. Survival analysis and expression validation verified the robustness of the hub genes. DISCUSSION: The present study provides new insight into the understanding of IBC pathogenesis and the identified hub genes may serve as potential targets for diagnosis and treatment.
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9128;570
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Homo sapiens
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High-resolution comparative genomic hybridization of inflammatory breast cancer and identification of candidate genes
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2026-11-01T15:39:54Z
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title
Expression Analysis of Microdissected Inflammatory Breast Cancer
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Homo sapiens
title
Tumor and stroma from breast by LCM
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PPI Network Construction and Module Analysis
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KEGG Enrichment Analysis of Top 4 Modules Identified from PPI Network
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The R package, limma (https://www.bioconductor.org/packages/release/bioc/html/limma.html), was applied to analyze differential expression. Bayes tests were used to evaluate statistical significance.
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{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32606769", "kind": "science-record", "revision": 9, "content_hash": "sha256:33179e0209fd326c454e8c969ae94062237ef9a4f0adf1573d3562f474c6dae8", "created_at": "2026-11-01T15:41:05Z", "updated_at": "2026-11-01T22:45:01Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Potential Key Genes and Pathways for Inflammatory Breast Cancer Based on GEO and TCGA Databases.", "doi": "10.2147/OTT.S255300", "pmid": "32606769", "authors": ["Qing Lv", "Yansong Liu", "Hu Huang", "Mingjie Zhu", "Junqiang Wu", "Dong Meng"], "journal": "OncoTargets and therapy", "year": 2020, "abstract": "INTRODUCTION: Inflammatory breast cancer (IBC) is a rare type of breast cancer with poor prognosis, and the pathogenesis of this life-threatening disease is yet to be fully elucidated. This study aims to identify key genes of IBC, which could be potential diagnostic or therapeutic targets.\nMETHODS: Four datasets GSE5847, GSE22597, GSE23720, and GSE45581 were downloaded from the Gene Expression Omnibus (GEO) and differential expression analysis was performed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to understand the potential bio-functions of the differentially expressed genes (DEGs). Protein-protein interaction (PPI) network was constructed for functional modules analysis and hub genes identification, and TCGA survival analysis and qRT-PCR of clinical samples were used to further explore and validate the effect of hub genes on IBC.\nRESULTS: A total of 114 DEGs were identified from the GEO datasets. GO and KEGG analyses showed that the DEGs were mainly enriched in oncogenesis and cell adhesion. From the PPI network, we screened out five hub genes, including PTPRC, IL6, SELL, CD40, and SPN. Survival analysis and expression validation verified the robustness of the hub genes.\nDISCUSSION: The present study provides new insight into the understanding of IBC pathogenesis and the identified hub genes may serve as potential targets for diagnosis and treatment.", "claims": [{"id": "claim-method", "statement": "The R package, limma (https://www.bioconductor.org/packages/release/bioc/html/limma.html), was applied to analyze differential expression. Bayes tests were used to evaluate statistical significance.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32606769", "locator": "sections[4] \"Identification of DEGs\" paragraph 2", "quote": "The R package, limma (https://www.bioconductor.org/packages/release/bioc/html/limma.html), was applied to analyze differential expression. 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