Construction of a Wilms tumor risk model based on machine learning and identification of cuproptosis-related clusters.

ABSTRACT:

Background

Cuproptosis, a recently identified type of programmed cell death triggered by copper, has mechanisms in Wilms tumor (WT) that are not yet fully understood. This research focuses on examining the link between WT and Cuproptosis-related genes (CRGs), with the goal of developing a predictive model for WT.

Methods

Four gene expression datasets related to WT were sourced from the GEO database. Subsequently, expression profiles of CRGs were extracted for differential analysis and immune infiltration studies. Utilizing 105 WT samples, clusters related to Cuproptosis were identified. This involved analyzing associated immune cell infiltration and conducting functional enrichment analysis. Disease-characteristic genes were pinpointed using weighted gene co-expression netwo

SUBMITTER: Huang J 

PROVIDER: S-EPMC11536559 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature