Construction and Validation of a Novel Prognostic Signature of Idiopathic Pulmonary Fibrosis by Identifying Subtypes Based on Genes Related to 7-Methylguanosine Modification

Background: Idiopathic pulmonary fibrosis (IPF) is the interstitial lung disease with the highest incidence and mortality. The lack of specific markers results in limited treatment methods for IPF patients. Numerous prognostic signatures represented effective indexes in predicting the survival of patients in various diseases; however, little is investigated on their application in IPF. Methods: This study attempted to explore the clinical markers suitable for IPF by constructing a prognostic signature from the perspective of 7-methylguanosine (m7G). An m7G-related prognostic signature (m7GPS) was established based on the discovery cohort with the LASSO algorithm and was verified by internal and external validation cohorts. The area under the curve (AUC) values were utilized to assess the accuracy of m7GPS in predicting the prognosis of IPF patients and the ability of m7GPS in screening IPF patients. Kaplan-Meier curves and Cox regression analyses were used to identify the relationship of m7GPS with the prognosis of IPF individuals. Enrichment analyses, CIBERSORT algorithm, and weighted gene co-expression network analysis were applied to explore the underlying mechanisms and correlation of m7GPS in IPF. Results: The two m7G regulatory genes can divide IPF into subtypes 1 and 2, and subtype 2 demonstrated a poor prognosis for IPF patients (p < 0.05). For the first time in this field, the m7GPS was constructed. m7GPS made it feasible to predict the 1–5 years survival status of IPF patients (AUC = 0.730–0.971), and it was an independent prognostic risk factor for IPF patients (hazard ratio > 1, p < 0.05). The conspicuous ability of m7GPS to screen IPF patients from the healthy was also revealed by an AUC value of 0.960. The roles of m7GPS in IPF may link to inflammation, immune response, and immune cell levels. Seven genes (CYR61, etc.) were identified as hub genes of m7GPS in IPF. Three drugs (ZM447439-1050, AZD1332-1463, and Ribociclib-1632) were considered sensitive to patients with high m7GPS risk scores. Conclusion: This study developed a novel m7GPS, which is a reliable indicator for predicting the survival status of IPF patients and is identified as an effective marker for prognosis and screening of IPF patients.