Development of a Multilayered Prognostic Model for Wilms' Tumor Based on Characteristic Lymphocyte Genes.

ABSTRACT:

Objective

To develop a prognostic nomogram for Wilms' tumor (WT) integrating genetic and clinical factors to improve evaluation accuracy and clinical utility.

Methods

RNA sequencing (RNA-seq) data from 125 WT patients and single-cell RNA (scRNA-seq) data from 2437 samples were analyzed using bioinformatics tools for data processing, including normalization and scaling with SCTransform, and cell clustering with Seurat. Principal component analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP) were utilized for data visualization. Differential gene expression analysis identified pivotal genes for the Genetic Feature Prognostic Model for WT (GPM-WT). Univariate Cox regression analysis refined this model by incorporating clinical prognostic indicators. Survival

SUBMITTER: Li Z 

PROVIDER: S-EPMC12721763 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature