ArticleOncology letters2016
Identification of key genes associated with gastric cancer based on DNA microarray data.
Article in Oncology letters, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Gastric Cancer Associated Genes Identified by an Integrative Analysis of Gene Expression Data.BioMed research international · 2017Pooled it
- Collagen type I alpha 1 induces radio-resistance in hypoxic glioblastoma cells by promoting autophagy.Journal of neuro-oncology · 2025Article
- Identification of differentially expressed genes associated with the pathogenesis of gastric cancer by bioinformatics analysis.BMC medical genomics · 2023Article
- Liquid biopsy: an examination of platelet RNA obtained from head and neck squamous cell carcinoma patients for predictive molecular tumor markers.Exploration of targeted anti-tumor therapy · 2023Article
- Bioinformatics and pathway enrichment analysis identified hub genes and potential biomarker for gastric cancer prognosis.Frontiers in oncology · 2023Article
- Identification of significant genes associated with prognosis of gastric cancer by bioinformatics analysis.Journal of the Egyptian National Cancer Institute · 2022Article
- Identification of a Cancer Stem Cells Signature of Head and Neck Squamous Cell Carcinoma.Frontiers in genetics · 2022Article
- Role of the CXCR3‑mediated TLRs/MyD88 signaling pathway in promoting the development of hepatitis B into cirrhosis and liver cancer.Molecular medicine reports · 2021Article
- Collagen XI alpha 1 chain, a potential therapeutic target for cancer.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2021Review
- Observational
- RNA Sequencing of Early-Stage Gastric Adenocarcinoma Reveals Multiple Activated Pathways and Novel Long Non-Coding RNAs in Patient Tissue Samples.Reports of biochemistry & molecular biology · 2021Article
- High expression of TREM2 promotes EMT via the PI3K/AKT pathway in gastric cancer: bioinformatics analysis and experimental verification.Journal of Cancer · 2021Article
- Progressive and Prognostic Performance of an Extracellular Matrix-Receptor Interaction Signature in Gastric Cancer.Disease markers · 2020Article
- miR-133a-3p suppresses cell proliferation, migration, and invasion and promotes apoptosis in esophageal squamous cell carcinoma.Journal of cellular physiology · 2019Article
- An age-based, RNA expression paradigm for survival biomarker identification for pediatric neuroblastoma and acute lymphoblastic leukemia.Cancer cell international · 2019Article
- Novel prognostic biomarkers of gastric cancer based on gene expression microarray: COL12A1, GSTA3, FGA and FGG.Molecular medicine reports · 2018Article
- Regulatory network of circRNA-miRNA-mRNA contributes to the histological classification and disease progression in gastric cancer.Journal of translational medicine · 2018Article
- Genome-wide association pathway analysis to identify candidate single nucleotide polymorphisms and molecular pathways associated with TP53 expression status in HBV-related hepatocellular carcinoma.Cancer management and research · 2018Article
- Identification of Potential Key Genes Associated With the Pathogenesis and Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis.Frontiers in genetics · 2018Article
- P4HA3 is Epigenetically Activated by Slug in Gastric Cancer and its Deregulation is Associated With Enhanced Metastasis and Poor Survival.Technology in cancer research & treatment · 2018Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The present study aimed to identify genes with a differential pattern of expression in gastric cancer (GC), and to find novel molecular biomarkers for GC diagnosis and therapeutic treatment. The gene expression profile of GSE19826, including 12 GC samples and 15 normal controls, was downloaded from the Gene Expression Omnibus database. Differentially-expressed genes (DEGs) were screened in the GC samples compared with the normal controls. Two-way hierarchical clustering of DEGs was performed to distinguish the normal controls from the GC samples. The co-expression coefficient was analyzed among the DEGs using the data from COXPRESdb. The gene co-expression network was constructed based on the DEGs using Cytoscape software, and modules in the network were analyzed by ClusterOne and Bingo. Furthermore, enrichment analysis of the DEGs in the modules was performed using the Database for Annotation, Visualization and Integrated Discovery. In total, 596 DEGs in the GC samples and 57 co-expression gene pairs were identified. A total of 7 genes were enriched in the same module, for which the function was phosphate transport and which was annotated to participate in the extracellular matrix-receptor interaction pathway. These genes were collagen, type VI, α3 (COL6A3), COL1A2, COL1A1, COL5A2, thrombospondin 2, COL11A1 and COL5A1. Overall, the present study identified several biomarkers for GC using the gene expression profiling of human GC samples. The COL family is a promising prognostic marker for GC. Gene expression products represent candidate biomarkers endowed with great potential for the early screening and therapy of GC patients.
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