ArticleFrontiers in immunology2025
Identification and validation of biomarkers in gastric cancer-associated membranous nephropathy: Insights from comprehensive bioinformatics analysis and machine learning.
Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Identification of replication factor C subunit 4 as a potential therapeutic target in esophageal squamous cell carcinoma based on bioinformatic analysis and machine learning.Discover oncology · 2026Article
- Artificial intelligence in membranous nephropathy: transforming clinical management toward precision medicine.Frontiers in medicine · 2026Review
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Authors and funding
6 authors.
Funding
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Abstract
Background: This study explores the genetic basis of membranous nephropathy (MN) in gastric adenocarcinoma (GC) through bioinformatics and machine learning analyses. Methods: Gene expression profiles from MN (GSE108109) and GC (GSE54129) datasets were obtained from the Gene Expression Omnibus. Common differentially expressed genes (DEGs) were identified using the limma R package. Biological functions were analyzed via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways with the Cluster Profiler package. LASSO regression and Random Forest algorithms were used to identify hub genes associated with GC-related MN. The area under the curve (AUC) of ROC analysis validated these genes for their diagnostic potential. Gene Set Enrichment Analysis (GSEA) and immune cell infiltration analysis were conducted, with hub genes validated through immunohistochemistry on renal and gastric cancer tissues. Results: We identified 40 common DEGs between GC and MN datasets. Using protein-protein interaction networks, 20 significant hub genes were selected, primarily involved in inflammatory and immune response regulation. Key hub genes identified were Conclusions: Our findings highlight the crucial roles of
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