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Updated: May 9, 2026

Imaging Approaches to Assessments of Toxicological Oxidative Stress Using Genetically-encoded Fluorogenic Sensors
Published on: February 7, 2018
An oxidative stress related gene signature predicts prognosis in cholangiocarcinoma
1Cadre Ward Two, General Hospital of Central Theater Command, Wuhan, 430030, Hubei, China.
Background:
Cholangiocarcinoma (CCA) is a malignancy with a poor prognosis and limited effective prognostic markers or therapeutic strategies. This study aims to construct and validate a prognostic risk model based on oxidative stress-related genes (OSRGs) to stratify patient risk and guide individualized treatment for CCA.
Methods:
Using data from 66 tumors and 36 control samples obtained from the TCGA and GEO databases, we identified 3,632 differentially expressed genes (DEGs). Intersection with oxidative stress-related genes revealed 122 OSRGs, from which 10 key prognostic genes were selected through univariate Cox and LASSO regression analyses. Model performance was assessed with Kaplan-Meier survival, ROC curve, PCA, and t-SNE analyses. Tumor microenvironment (TME) features, immune cell infiltration, and chemosensitivity to cisplatin and 5-fluorouracil were also evaluated.
Results:
The 10-gene model, including genes like RORA and GRIN2A, effectively distinguished between high- and low-risk groups, with high RORA and GRIN2A expression correlating with improved survival. High-risk groups displayed increased immune and ESTIMATE scores, with significant differences in immune cell infiltration. Chemosensitivity analysis indicated differential responses to various chemotherapeutics in high-risk patients.
Conclusion:
This OSRG-based model demonstrates strong prognostic potential, stratifying CCA patients by risk and survival outcomes. The model provides insights into personalized treatment strategies, potentially advancing therapeutic interventions for CCA.
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