Development and validation of two redox-related genes associated with prognosis and immune microenvironment in endometrial carcinoma.
Math Biosci Eng
; 20(6): 10339-10357, 2023 03 31.
Article
in En
| MEDLINE
| ID: mdl-37322935
ABSTRACT
In recent studies, the tumourigenesis and development of endometrial carcinoma (EC) have been correlated significantly with redox. We aimed to develop and validate a redox-related prognostic model of patients with EC to predict the prognosis and the efficacy of immunotherapy. We downloaded gene expression profiles and clinical information of patients with EC from the Cancer Genome Atlas (TCGA) and the Gene Ontology (GO) dataset. We identified two key differentially expressed redox genes (CYBA and SMPD3) by univariate Cox regression and utilised them to calculate the risk score of all samples. Based on the median of risk scores, we composed low-and high-risk groups and performed correlation analysis with immune cell infiltration and immune checkpoints. Finally, we constructed a nomogram of the prognostic model based on clinical factors and the risk score. We verified the predictive performance using receiver operating characteristic (ROC) and calibration curves. CYBA and SMPD3 were significantly related to the prognosis of patients with EC and used to construct a risk model. There were significant differences in survival, immune cell infiltration and immune checkpoints between the low-and high-risk groups. The nomogram developed with clinical indicators and the risk scores was effective in predicting the prognosis of patients with EC. In this study, a prognostic model constructed based on two redox-related genes (CYBA and SMPD3) were proved to be independent prognostic factors of EC and associated with tumour immune microenvironment. The redox signature genes have the potential to predict the prognosis and the immunotherapy efficacy of patients with EC.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Endometrial Neoplasms
Type of study:
Prognostic_studies
/
Risk_factors_studies
Limits:
Female
/
Humans
Language:
En
Journal:
Math Biosci Eng
Year:
2023
Document type:
Article
Affiliation country: