C39-11 Development of a Blood-derived M6a-associated Gene Signature for Prognostic Prediction in Idiopathic Pulmonary Fibrosis

Rationale Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal interstitial lung disease characterized by irreversible scarring of lung tissue and poor prognosis. Despite advances in diagnosis and therapy, accurate prognostic biomarkers for IPF remain limited. N6-methyladenosine (m6A) RNA methylation has emerged as a critical epitranscriptomic regulator of gene expression and tissue remodeling. Recent studies revealed dysregulated m6A modification patterns in IPF, suggesting a potential link between m6A signaling and disease progression. This study aimed to identify and validate a blood-derived m6A-associated gene signature that predicts survival in IPF patients. Methods A total of 200 m6A-associated genes were initially identified using the STRING database. Univariate Cox regression analysis was performed to screen for survival-related genes, identifying 65 candidates significantly associated with IPF prognosis. A gene co-expression network was constructed to determine hub genes, resulting in the identification of 17 key m6A-associated genes. These genes were incorporated into a multivariate Cox regression model to construct a prognostic risk score. Patients were divided into high- and low-risk groups based on median risk score values. The predictive performance of the signature was evaluated using Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curve analysis in both discovery and validation cohorts. Functional enrichment analysis was conducted to explore biological pathways associated with the identified hub genes. Results The constructed 17-gene m6A-associated signature demonstrated robust prognostic performance, effectively stratifying patients into high- and low-risk groups with significantly different overall survival outcomes. The risk model achieved strong predictive accuracy, with area under the ROC curve (AUC) values indicating high sensitivity and specificity in both discovery and validation cohorts. Functional enrichment analysis revealed that these 17 hub genes were primarily involved in RNA processing, mRNA stability, and cellular stress response pathways—key processes implicated in fibrogenesis. Comparative analyses showed that this signature outperformed 95% of randomized models, underscoring its reliability and biological relevance. Conclusions This study established a novel blood-derived 17-gene m6A-associated prognostic signature that reliably predicts survival in IPF patients. The findings highlight the potential of m6A-related pathways as key contributors to IPF pathogenesis and suggest that this gene signature could serve as an independent and clinically useful biomarker for risk stratification and therapeutic decision-making in IPF. This abstract is funded by: NIH