ArticleFrontiers in oncology2023
Bioinformatics and pathway enrichment analysis identified hub genes and potential biomarker for gastric cancer prognosis.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed, 23 citations in OpenAlex.
- Proteomic analysis of papillary thyroid carcinoma in the context of Hashimoto's thyroiditis.Scientific reports · 2026Article
- Caffeine enhances antitumor T-cell activity by suppressing kynurenine pathway in colorectal cancer.Nature communications · 2025Article
- Identification and validation of extracellular matrix-related genes in the progression of gastric cancer with intestinal metaplasia.World journal of gastrointestinal oncology · 2025Article
- Comprehensive analysis of intervention and control studies for the computational identification of dengue biomarker genes.PLoS neglected tropical diseases · 2025Article
- Article
- A Bioinformatics Investigation of Hub Genes Involved in Treg Migration and Its Synergistic Effects, Using Immune Checkpoint Inhibitors for Immunotherapies.International journal of molecular sciences · 2024Article
- Unravelling driver genes as potential therapeutic targets in ovarian cancer via integrated bioinformatics approach.Journal of ovarian research · 2024Article
- [Screening of differentially expressed genes in gastric cancer based on GEO database and function and pathway enrichment analysis].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2024Article
- Genetic characterization and selection of litter size traits of Guizhou Black goat and Meigu goat.PloS one · 2024Article
- Jian Yun Qing Hua Decoction inhibits malignant behaviors of gastric carcinoma cells via COL12A1 mediated ferroptosis signal pathway.Chinese medicine · 2023Article
- METTL3-Mediated m6A Modification of COL5A2 Inhibits Ferroptosis Through an IGF2BP3-dependent Mechanism in Gastric Cancer.Technology in cancer research & treatmentArticle
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Gastric cancer is one of the most common cancers in the world. This study aimed to identify genes, biomarkers, and metabolic pathways affecting gastric cancer using bioinformatic analysis and meta-analysis. Methods: Datasets containing gene expression profiles of tumor lesions and adjacent non-tumor mucosa samples were downloaded. Common differentially expressed genes between data sets were selected to identify hub genes and further analysis. Gene Expression Profiling and Interactive Analyses (GEPIA) and the Kaplan-Meier method were used to further validate the expression level of genes and plot the overall survivalcurve, respectively. Results and disscussion: KEGG pathway analysis showed that the most important pathway was enriched in ECM-receptor interaction. Hub genes includingCOL1A2, FN1, BGN, THBS2, COL5A2, COL6A3, SPARC and COL12A1 wereidentified. The top interactive miRNAs including miR-29a-3p, miR-101-3p,miR-183-5p, and miR-15a-5p targeted the most hub genes. The survival chart showed an increase in mortality in patients with gastric cancer, which shows the importance of the role of these genes in the development of the disease and can be considered candidate genes in the prevention and early diagnosis of gastric cancer.
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