A prognostic model based on clusters of molecules related to epithelial–mesenchymal transition for idiopathic pulmonary fibrosis - Zhao, Jiarui; Wang, Can; Fan, Rui; Liu, Xiangyang; Zhang, Wei (Frontiers in Genetics, 2023)
Background: Most patients with idiopathic pulmonary fibrosis (IPF) have poor prognosis; effective predictive models for these patients are currently lacking. Epithelial–mesenchymal transition (EMT) often occurs during IPF development, and is closely related to multiple pathways and biological processes. It is thus necessary for clinicians to find prognostic biomarkers with high accuracy and specificity from the perspective of EMT. Methods: Data were obtained from the Gene Expression Omnibus database. Using consensus clustering, patients were grouped based on EMT-related genes. Next, functional enrichment analysis was performed on the results of consensus clustering using gene set variation analysis. The gene modules associated with EMT were obtained through weighted gene co-expression network analysis. Prognosis-related genes were screened via least absolute shrinkage and selection operator (LASSO) regression analysis. The model was then evaluated and validated using survival analysis and time-dependent receiver operating characteristic (ROC) analysis. Results: A total of 239 EMT-related genes were obtained from patients with IPF. Six genes with strong prognostic associations (C-X-C chemokine receptor type 7 [CXCR7], heparan sulfate-glucosamine 3-sulfotransferase 1 [HS3ST1], matrix metallopeptidase 25 [MMP25], murine retrovirus integration site 1 [MRVI1], transmembrane 4 L6 family member 1 [TM4SF1], and tyrosylprotein sulfotransferase 1 [TPST1]) were identified via LASSO and Cox regression analyses. A prognostic model was then constructed based on the selected genes. Survival analysis showed that patients with high-risk scores had worse prognosis based on the training set (hazard ratio [HR] = 7.31, P < 0.001) and validation set (HR = 2.85, P = 0.017). The time-dependent ROC analysis showed that the area under the curve (AUC) values in the training set were 0.872, 0.905, and 0.868 for 1-, 2-, and 3-year overall survival rates, respectively. Moreover, the AUC values in the validation set were 0.814, 0.814, and 0.808 for 1-, 2-, and 3-year overall survival rates, respectively. Conclusions: The independent prognostic model constructed from six EMT-related genes provides bioinformatics guidance to identify additional prognostic markers for IPF in the future.