Development and validation of prognostic models based on cell cycle-related signatures for predicting the prognosis of patients with lung adenocarcinoma.

ABSTRACT:

Background

Lung adenocarcinoma (LUAD) represents the most prevalent histological subtype within lung cancer. Nevertheless, the risk of postoperative metastasis and recurrence remains a substantial concern. We aimed to build the cell cycle-related competing endogenous RNA (ceRNA) networks and potential prognosis prediction models of LUAD, which might provide a valuable reference for studying the prognosis of LUAD.

Methods

The RNA sequencing data of LUAD were procured from The Cancer Genome Atlas (TCGA) database and the differentially expressed RNAs were identified from the Ensembl genome browser 96 database [P<0.05 and |log2 fold change (FC)| >1]. The gene expression profile data were acquired from the Gene Expression Omnibus (GEO) repository. A gene set variation analysis wa

SUBMITTER: Huang Y 

PROVIDER: S-EPMC12170059 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature