ArticleMedical science monitor : international medical journal of experimental and clinical research2020
Identification of Hub Genes and Pathways in Gastric Adenocarcinoma Based on Bioinformatics Analysis.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 26 citations in OpenAlex.
- Prognostic value of RNA methylation-related genes in gastric adenocarcinoma based on bioinformatics.PeerJ · 2024Article
- Transcriptome sequencing and miRNA-mRNA network construction in exosome of macrophage M2 in stomach adenocarcinoma.World journal of surgical oncology · 2023Article
- Identification of miR-143-3p as a diagnostic biomarker in gastric cancer.BMC medical genomics · 2023Article
- Review
- Identification and verification of microRNA signature and key genes in the development of osteosarcoma with lung metastasis.Medicine · 2022Article
- A Deep Neural Network for Gastric Cancer Prognosis Prediction Based on Biological Information Pathways.Journal of oncology · 2022Article
- Association ofFrontiers in genetics · 2022Article
- An integrated analysis of prognostic mRNA signature in early- and progressive-stage gastric adenocarcinoma.Frontiers in molecular biosciences · 2022Article
- A tumour-resident Lgr5Nature cell biology · 2021Article
- Identification of Potential Biomarkers Associated with Prognosis in Gastric Cancer via Bioinformatics Analysis.Medical science monitor : international medical journal of experimental and clinical research · 2021Article
- Immunoexpression of E-cadherin, CD44 and Claudin 7 in gastric adenocarcinomas.Romanian journal of morphology and embryology = Revue roumaine de morphologie et embryologieArticle
- Silencing of SPP1 Suppresses Progression of Tongue Cancer by Mediating the PI3K/Akt Signaling Pathway.Technology in cancer research & treatmentArticle
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND Gastric adenocarcinoma accounts for 95% of all gastric malignant tumors. The purpose of this research was to identify differentially expressed genes (DEGs) of gastric adenocarcinoma by use of bioinformatics methods. MATERIAL AND METHODS The gene microarray datasets of GSE103236, GSE79973, and GSE29998 were imported from the GEO database, containing 70 gastric adenocarcinoma samples and 68 matched normal samples. Gene ontology (GO) and KEGG analysis were applied to screened DEGs; Cytoscape software was used for constructing protein-protein interaction (PPI) networks and to perform module analysis of the DEGs. UALCAN was used for prognostic analysis. RESULTS We identified 2909 upregulated DEGs (uDEGs) and 7106 downregulated DEGs (dDEGs) of gastric adenocarcinoma. The GO analysis showed uDEGs were enriched in skeletal system development, cell adhesion, and biological adhesion. KEGG pathway analysis showed uDEGs were enriched in ECM-receptor interaction, focal adhesion, and Cytokine-cytokine receptor interaction. The top 10 hub genes - COL1A1, COL3A1, COL1A2, BGN, COL5A2, THBS2, TIMP1, SPP1, PDGFRB, and COL4A1 - were distinguished from the PPI network. These 10 hub genes were shown to be significantly upregulated in gastric adenocarcinoma tissues in GEPIA. Prognostic analysis of the 10 hub genes via UALCAN showed that the upregulated expression of COL3A1, COL1A2, BGN, and THBS2 significantly reduced the survival time of gastric adenocarcinoma patients. Module analysis revealed that gastric adenocarcinoma was related to 2 pathways: including focal adhesion signaling and ECM-receptor interaction. CONCLUSIONS This research distinguished hub genes and relevant signal pathways, which contributes to our understanding of the molecular mechanisms, and could be used as diagnostic indicators and therapeutic biomarkers for gastric adenocarcinoma.
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