Anoikis and SPP1 in idiopathic pulmonary fibrosis: integrating bioinformatics, cell, and animal studies to explore prognostic biomarkers and PI3K/AKT signaling regulation

Abstract

ABSTRACT Objective This study aims to explore the relevance of anoikis in idiopathic pulmonary fibrosis (IPF) and identify associated biomarkers and signaling pathways. Method Unsupervised consensus cluster analysis was employed to categorize IPF patients into subtypes. We utilized Weighted Gene Co-Expression Network Analysis (WGCNA) and Protein-Protein Interaction network construction to identify anoikis-related modules and key genes. A prognostic signature was developed using Lasso and multivariate Cox regression analysis. Single-cell sequencing assessed hub gene expression in various cell types, and both cell and animal experiments confirmed IPF-related pathways. Results We identified two distinct anoikis-associated subtypes with differing prognoses. WGCNA revealed essential hub genes, with SPP1 being prominent in the anoikis-related signature. The anoikis-related signature is effective in determining the prognosis of patients with IPF. Single-cell sequencing highlighted significant differences in SPP1 expression, notably elevated in fibroblasts derived from IPF patients. In vivo and in vitro experiments demonstrated that SPP1 enhances fibrosis in mouse lung fibroblasts by regulating p27 through the PI3K/Akt pathway. Conclusion Our research demonstrates a robust prognostic signature associated with anoikis and highlights SPP1 as a pivotal regulator of the PI3K/AKT signaling pathway in pulmonary fibrosis.