Bioinformatic analyses and integrated machine learning reveal the role of lactate, a metabolic driver of the immune landscape, serves in idiopathic pulmonary fibrosis

Abstract

Abstract Background: The development and progression of idiopathic pulmonary fibrosis (IPF) are significantly influenced by altered lactate metabolism. However, the exact mechanism has not been elucidated. This study attempted to find novel lactate metabolism-related gene signatures that could be used to predict the diagnosis, prognosis, and immune environment of IPF patients. Methods: Transcriptome data of PBMC samples with IPF and lactate metabolism-related genes were obtained from GEO database and freely accessible data sources, respectively. DEGs analysis and integrated machine learning (LASSO regression, Random Forest, and SVM) were used to identify key genes. On the screened genes, GO analysis, KEGG pathway enrichment analysis, GSEA, and PPI network were carried out. ROC curves and Kaplan–Meier survival analysis were performed to evaluate the diagnostic performance and prognostic value of key genes. The ssGSEA analysis was used for estimating the characteristics of immune cell infiltration. In addition, we predicted the transcription factors and miRNAs upstream of the identified key genes. Results: 50 differentially expressed lactate metabolism-related genes (DELMRGs) were identified, with 30 genes upregulated and 20 genes downregulated; 6 key DELMRGs (CA5A, COQ2, SCO2, NDUFAF4, PC, and SLC25A10) were found by additional screening using integrated machine learning. Multiple enriched terms associated with mitochondrial function and energy metabolism were found using GO and KEGG functional enrichment analysis. Diagnostic efficacy and survival analysis showed that all 6 key DELMRGs could potentially be used as diagnostic biomarkers for IPF; among them, CA5A, COQ2, and SCO2 were negatively associated with prognosis while NDUFAF4 was positively associated with prognosis in IPF. The ssGSEA and correlation analysis showed that the percentage of MDSCs, macrophages, neutrophils, gamma delta T cells, and regulatory T cells was increased in IPF; their infiltration levels were closely correlated with the expression profiles of 6 key DELMRGs. Conclusions: Altered lactate metabolism presents in IPF and correlates with immuneresponse. We screened 6 key DELMRGs to predict the diagnosis, prognosis, and features of immune landscape with IPF. This study provides a new viewpoint to comprehend the roles of lactate metabolism and metabolic regulation of immune response serve in IPF.