ArticleCancer biomarkers : section A of Disease markers2021
Weighted correlation network analysis identifies FN1, COL1A1 and SERPINE1 associated with the progression and prognosis of gastric cancer.
Article in Cancer biomarkers : section A of Disease markers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed, 22 citations in OpenAlex.
- Shared molecular features and candidate pathways underlying gastric cancer-depression comorbidity: a systems biology analysis.Frontiers in bioinformatics · 2026Article
- The type I collagen paradox in PDAC progression: microenvironmental protector turned tumor accomplice.Journal of translational medicine · 2025Review
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- Prognostic development and validation of a prediction model based on major histocompatibility complex-related differentially expressed genes in stomach adenocarcinoma.Translational cancer research · 2025Article
- Elemene Injection Suppresses Pancreatic Cancer Progress through Regulating Cell Adhesion: A Research Based upon Network Pharmacology and Verification Test.Current medicinal chemistry · 2025Article
- ExpOmics: a comprehensive web platform empowering biologists with robust multi-omics data analysis capabilities.Bioinformatics (Oxford, England) · 2024Article
- miR-34b-3p-mediated regulation of STC2 and FN1 enhances chemosensitivity and inhibits proliferation in cervical cancer.Acta biochimica et biophysica Sinica · 2024Article
- Analysis of cancer-associated fibroblasts related genes identifies COL11A1 associated with lung adenocarcinoma prognosis.BMC medical genomics · 2024Article
- Construction of a prognostic model via WGCNA combined with the LASSO algorithm for stomach adenocarcinoma patients.Frontiers in genetics · 2024Article
- Identification of differentially expressed genes associated with the pathogenesis of gastric cancer by bioinformatics analysis.BMC medical genomics · 2023Article
- Identification and validation of key genes associated with pathogenesis and prognosis of gastric cancer.PeerJ · 2023Article
- The predictive effect of immune therapy and chemotherapy under T cell-related gene prognostic index for Gastric cancer.Frontiers in cell and developmental biology · 2023Article
- A prognostic model based on the COL1A1-network in gastric cancer.American journal of translational research · 2023Article
- Inflammation-Related Genes Serve as Prognostic Biomarkers and Involve in Immunosuppressive Microenvironment to Promote Gastric Cancer Progression.Frontiers in medicine · 2022Article
- Identification of Potential Diagnostic and Prognostic Biomarkers for Gastric Cancer Based on Bioinformatic Analysis.Frontiers in genetics · 2022Article
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGastric cancer (GC) is one of the most deadliest tumours worldwide, and its prognosis remains poor.
objectiveThis study aims to identify and validate hub genes associated with the progression and prognosis of GC by constructing a weighted correlation network.
methodsThe gene co-expression network was constructed by the WGCNA package based on GC samples and clinical data from the TCGA database. The module of interest that was highly related to clinical traits, including stage, grade and overall survival (OS), was identified. GO and KEGG pathway enrichment analyses were performed using the clusterprofiler package in R. Cytoscape software was used to identify the 10 hub genes. Differential expression and survival analyses were performed on GEPIA web resources and verified by four GEO datasets and our clinical gastric specimens. The receiver operating characteristic (ROC) curves of hub genes were plotted using the pROC package in R. The potential pathogenic mechanisms of hub genes were analysed using gene set enrichment analysis (GSEA) software.
resultsA total of ten modules were detected, and the magenta module was identified as highly related to OS, stage and grade. Enrichment analysis of magenta module indicated that ECM-receptor interaction, focal adhesion, PI3K-Akt pathway, proteoglycans in cancer were significantly enriched. The PPI network identified ten hub genes, namely COL1A1, COL1A2, FN1, POSTN, THBS2, COL11A1, SPP1, MMP13, COMP, and SERPINE1. Three hub genes (FN1, COL1A1 and SERPINE1) were finally identified to be associated with carcinogenicity and poor prognosis of GC, and all were independent risk factors for GC. The area under the curve (AUC) values of FN1, COL1A1 and SERPINE1 for the prediction of GC were 0.702, 0.917 and 0.812, respectively. GSEA showed that three hub genes share 15 common upregulated biological pathways, including hypoxia, epithelial mesenchymal transition, angiogenesis, and apoptosis.
conclusionWe identified FN1, COL1A1 and SERPINE1 as being associated with the progression and poor prognosis of GC.
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