ArticleTranslational cancer research2022
The prognostic role of fatty acid metabolism-related genes in patients with gastric cancer.
Article in Translational cancer research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 8 citations in OpenAlex.
- A Novel Telomere Maintenance Gene-Related Model for Prognosis Prediction in Gastric Cancer.Biochemical genetics · 2026Article
- Exploring and Validating Prognostic Biomarkers Related to Sphingolipid Metabolism in Gastric Cancer through Machine LearningEndocrine, metabolic & immune disorders drug targets · 2026Article
- Development and validation of a prognosis prediction model for overall survival in correlation between butyrate metabolism and gastric cancer prognosis: Mendelian randomization and transcriptomics analysis.Translational cancer research · 2025Article
- A prognostic model correlated with fatty acid metabolism in Ewing's sarcoma based on bioinformatics analysis.Open medicine (Warsaw, Poland) · 2025Article
- The influence of cancer on the reprogramming of lipid metabolism in healthy thyroid tissues of patients with papillary thyroid carcinoma.Endocrine · 2025Article
- Multimodal analysis of TAAD pathogenesis: SHAP-enhanced interpretable models and single-cell sequencing analysis reveal immune microenvironment alterations.Frontiers in immunology · 2025Article
- Article
- Expanding the Genetic Blueprint of Wilms Tumor: An Account of 71 Novel Variants across 16 Genes with Novel Implications for Wilms Tumor Pathogenesis.Journal of Indian Association of Pediatric SurgeonsArticle
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: With the deepening research on fatty acid metabolism, people have achieved a preliminary understanding of it in the development and prognosis of tumors. However, few studies are still on the expression pattern and prognostic value of fatty acid metabolism-related genes in gastric cancer (GC). Methods: We chose 93 genes relevant to fatty acid metabolism from the Gene Set Enrichment Analysis (GSEA) database. We analyzed differentially expressed genes (DEGs) in The Cancer Genome Atlas (TCGA) patients. Univariate Cox analysis and LASSO regression were used to select the genes most related to prognosis and therefore developed a prognosis model. In addition, a dataset of 76 samples from Gene Expression Omnibus (GEO) selected as a test set to aid in the development of a prognostic model. The prognostic relevance of this model was confirmed using Kaplan-Meier survival analysis, univariate/multivariate Cox analysis, and receiver operating characteristic (ROC) curve. Finally, enrichment analysis and protein-protein interaction (PPI) were used to analyze the functional differences of patients with different risk. Immune infiltration analysis based on CIBERSORT could check the infiltration degree and immune function changes of immune cell subtypes in patients with different risk groups. Results: Overexpression of Conclusions: Four fatty acid metabolism-related genes were discovered to be closely connected to the prognosis of individuals with GC. Through analysis and verification, we believed that this prognostic model was reliable and instructive in the prediction of the prognosis of GC.
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