ArticlePeerJ2024
Prognostic value of RNA methylation-related genes in gastric adenocarcinoma based on bioinformatics.
Article in PeerJ, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Maternal causation of early-onset pre-eclampsia: excessive endometrial gland-derived apolipoprotein D induces placental ferroptosis and developmental abnormalities.Journal of biomedical science · 2025Article
- Development of a quantitative genomic instability scoring system and a related competing endogenous RNA network in head and neck squamous cell carcinoma.Translational cancer research · 2025Article
- Correlation between dyslipidaemia and gastric cancer: pathogenesis to prevention and treatment strategies.Lipids in health and disease · 2025Review
- Association of miR-338-3p with survival outcomes in gastric cancer patients who received peri-operative blood transfusion.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Article
- Comprehensive Bioinformatics Analyses and Experimental Validation of the Cell Cycle Related Protein SAPCD2 as a New Biomarker and Potential Therapeutic Target in Pancreatic Cancer.Journal of inflammation research · 2025Article
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Authors and funding
8 authors.
Funding
Abstract
Background: Gastric cancer (GC) is a malignant tumor that originates from the epithelium of the gastric mucosa and has a poor prognosis. Stomach adenocarcinoma (STAD) covers 95% of total gastric cancer. This study aimed to identify the prognostic value of RNA methylation-related genes in gastric cancer. Methods: In this study, The Cancer Genome Atlas (TCGA)-STAD and GSE84426 cohorts were downloaded from public databases. Patients were classified by consistent cluster analysis based on prognosis-related differentially expressed RNA methylation genes Prognostic genes were obtained by differential expression, univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses. The prognostic model was established and validated in the training set, test set and validation set respectively. Independent prognostic analysis was implemented. Finally, the expression of prognostic genes was affirmed by reverse transcription quantitative PCR (RT-qPCR). Results: In total, four prognostic genes ( Conclusion: Our study established a novel RNA methylation-related risk signature for STAD, which was of considerable significance for improving prognosis of STAD patients and offering theoretical support for clinical therapy.
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