An innovative glutamine metabolism-related gene signature for predicting prognosis and immune landscape in cervical cancer.

ABSTRACT:

Background

Cervical cancer (CC) is a major global malignancy affecting women. However, the precise mechanisms underlying glutamine's role in CC remain inadequately understood. This study systematically assessed the survival outcomes, immune landscape, and drug sensitivity profiles with CC patients by analyzing genes associated with glutamine metabolism.

Methods

Transcriptomic data for the samples were sourced from the TCGA, GTEx, and GEO databases. Prognostic genes were identified through univariate, multivariate, and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses. The predictive accuracy of the model was assessed through the analysis of receiver operating characteristic (ROC) curves. A comprehensive nomogram was developed and evaluated for accur

SUBMITTER: Fang HY 

PROVIDER: S-EPMC11926318 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature