Construction of a prognostic model for autophagy in Wilm's tumor
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In brief
In brief
This study develops a prognostic model for Wilms tumor using autophagy-related genes CXCR4 and ERBB2, identifying high-risk and low-risk patient groups with significantly different survival outcomes. The model combines genetic markers with clinical factors to predict prognosis and may guide future therapeutic targeting.
- CXCR4 and ERBB2 are critical autophagy-related genes with prognostic significance in Wilms tumor patients.
- A two-gene prognostic model successfully stratifies WT patients into high-risk and low-risk groups with distinct survival outcomes.
- The autophagy-based prognostic model incorporates race, age, and stage to predict Wilms tumor prognosis.
- Autophagy-related gene expression patterns may serve as novel biomarkers for risk stratification in pediatric kidney cancer.
- CXCR4 and ERBB2 represent potential therapeutic targets for improving outcomes in high-risk Wilms tumor cases.
Written by the GCMD Library team from the article.
Abstract
Background
Wilm's tumor (WT) is one of the most common childhood urological tumors, ranking second in the incidence of pediatric abdominal tumors. The development of WT is associated with various factors, and the correlation with autophagy is currently unclear.
Purpose
To develop a new prognostic model of autophagy-related genes (ATG) for WT.
Methods
Using the Therapeutically applicable research to generate effective treatments (TARGET) database to screen for differentially expressed ATGs in WT and normal tissues. ATGs were screened for prognostic relevance to WT using one-way and multifactorial Cox regression analyses and prognostic models were constructed. The risk score was calculated according to the model, and the predictive ability of the constructed model was analyzed using the ROC (receiver operating characteristic) curve to verify the significance of the model for the prognosis of WT.
Results
Sixty-eight differentially expressed ATGs were identified by univariate Cox regression analysis, and two critical prognostic ATGs (CXCR4 and ERBB2) were identified by multivariate Cox regression analysis. Patients were divided into high-risk and low-risk groups according to the differential expression of these two ATGs. Kaplan–Meier (KM) curves showed a significant difference in survival time between the two groups. The critical prognostic ATGs were combined with race, age, and stage in a multifactorial regression analysis, and the final prognostic model was produced as a line graph.
Conclusion
The prognostic model of autophagy-related genes composed of the CXCR4 gene and ERBB2 gene has a specific predictive value for the prognosis of WT, and the present study provides a clear basis for future research on biomarkers and therapeutic targets.