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Identification and validation of a novel ferroptosis-related gene model for predicting the prognosis of gastric cancer patients
- Source :
- PLoS ONE, PLoS ONE, Vol 16, Iss 7, p e0254368 (2021)
- Publication Year :
- 2021
- Publisher :
- Public Library of Science (PLoS), 2021.
-
Abstract
- Background Ferroptosis is a novel form of regulated cell death that plays a critical role in tumorigenesis. The purpose of this study was to establish a ferroptosis-associated gene (FRG) signature and assess its clinical outcome in gastric cancer (GC). Methods Differentially expressed FRGs were identified using gene expression profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were performed to construct a prognostic signature. The model was validated using an independent GEO dataset, and a genomic-clinicopathologic nomogram integrating risk scores and clinicopathological features was established. Results An 8-FRG signature was constructed to calculate the risk score and classify GC patients into two risk groups (high- and low-risk) according to the median value of the risk score. The signature showed a robust predictive capacity in the stratification analysis. A high-risk score was associated with advanced clinicopathological features and an unfavorable prognosis. The predictive accuracy of the signature was confirmed using an independent GSE84437 dataset. Patients in the two groups showed different enrichment of immune cells and immune-related pathways. Finally, we established a genomic-clinicopathologic nomogram (based on risk score, age, and tumor stage) to predict the overall survival (OS) of GC patients. Conclusions The novel FRG signature may be a reliable tool for assisting clinicians in predicting the OS of GC patients and may facilitate personalized treatment.
- Subjects :
- Male
0301 basic medicine
Oncology
Cell signaling
Epidemiology
Gene Expression
Kaplan-Meier Estimate
Signal transduction
medicine.disease_cause
0302 clinical medicine
Lasso (statistics)
Medicine and Health Sciences
Multidisciplinary
Framingham Risk Score
Cancer Risk Factors
Signaling cascades
Regression analysis
Middle Aged
Prognosis
Gene Expression Regulation, Neoplastic
Nephrology
Renal Cancer
030220 oncology & carcinogenesis
Medicine
Female
Research Article
Cell biology
medicine.medical_specialty
MAPK signaling cascades
Science
03 medical and health sciences
Lymphocytes, Tumor-Infiltrating
Malignant Tumors
Stomach Neoplasms
Diagnostic Medicine
Internal medicine
Gastrointestinal Tumors
Genetics
medicine
Ferroptosis
Humans
Aged
Proportional Hazards Models
Models, Genetic
Biology and life sciences
business.industry
Proportional hazards model
Univariate
Reproducibility of Results
Cancers and Neoplasms
Cancer
Nomogram
medicine.disease
Gastric Cancer
Gene Ontology
030104 developmental biology
Medical Risk Factors
Multivariate Analysis
Transcriptome
business
Carcinogenesis
Subjects
Details
- ISSN :
- 19326203
- Volume :
- 16
- Database :
- OpenAIRE
- Journal :
- PLOS ONE
- Accession number :
- edsair.doi.dedup.....c81a0c5353d1a826db1d57b7dbdf0249