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ABSTRACT: Background
Glycolysis plays a major role in progression of idiopathic pulmonary fibrosis (IPF). Here, we aim to explore the predictive signature based on glycolysis-related genes for predicting the prognosis and identified a potential therapeutic target for IPF.Methods
Gene expression data of bronchoalveolar lavage (BAL) cells and clinical information were downloaded from the Gene Expression Omnibus database. Bioinformatic analysis was then performed to identify differentially expressed genes (DEGs). Lasso multivariate cox analysis and multivariate Cox regression were used to establish a gene signature. The prediction model was evaluated using the time-dependent receiver operating characteristic (ROC) curve and validated using an external independent dataset. The expression
SUBMITTER: Xia Y
PROVIDER: S-EPMC11662423 | biostudies-literature | 2024 Dec
REPOSITORIES: biostudies-literature