ArticleJournal of inflammation research2022
Lipid Metabolic-Related Signature CYP19A1 is a Potential Biomarker for Prognosis and Immune Cell Infiltration in Gastric Cancer.
Article in Journal of inflammation research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 13 citations in OpenAlex.
- Article
- Development of an ADME gene signature for prognostic and therapeutic stratification in gastric cancer.Discover oncology · 2025Article
- Tracing the evolutionary pathway of SARS-CoV-2 through RNA sequencing analysis.Scientific reports · 2025Article
- DNMT1/MTTP axis promotes gastritis progression duringEpigenomics · 2025Article
- Editorial: From bench to bedside in gastric cancer: diagnosis, prognosis, and treatment, volume II.Frontiers in medicine · 2025Article
- CYP19A1 Silencing Inhibits Cell Proliferation and Endoplasmic Reticulum Stress in Stomach Adenocarcinoma.Oncology research · 2025Article
- Integrated analysis of single-cell and bulk RNA-sequencing reveals a novel signature based on NK cell marker genes to predict prognosis and immunotherapy response in gastric cancer.Scientific reports · 2024Article
- The expression of lnc-CCDC170-4:1, ESR1, lncRNA SRA, and CYP19A1 in cervical squamous cell carcinoma and their relationship with the clinical characteristics.Frontiers in oncology · 2024Article
- Progressions of the correlation between lipid metabolism and immune infiltration characteristics in gastric cancer and identification of BCHE as a potential biomarker.Frontiers in immunology · 2024Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Altered lipid metabolism is associated with gastric cancer (GC) progression. Comprehensive analysis to identify critical lipid metabolic drivers for predicting overall survival (OS) is not fully elucidated in GC. Our study aim to explore a novel lipid metabolism-related prognostic marker for GC. Methods: Transcriptional status and clinical features were obtained from the TCGA-STAD database. The differentially expressed lipid metabolic genes and the risk prognostic model were developed by using bioinformatics and Cox regression analyses. ROC and Kaplan-Meier analysis were established to assess the performance of the risk predictive score model. GSE84437 dataset was used for external validation. Immunochemistry (IHC) was used to examine the expression of CYP19A1 in GC patients. Gene Set Enrichment Analysis (GSEA) was conducted to elucidate the underlying enriched mechanisms. TIMER and CIBERSORT analysis were performed to explore the relationship between CYP19A1 and immune microenvironment. Results: A novel lipid metabolic gene signature (including M Conclusion: CYP19A1 could be an independent prognostic factor and a novel metabolic-targeted treatment strategy for gastric cancer.
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Registered trials
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