Construction of prediction model of inflammation related genes in idiopathic pulmonary fibrosis and its correlation with immune microenvironment

Abstract

BackgroundThe role of inflammation in the formation of idiopathic pulmonary fibrosis (IPF) has gained a lot of attention recently. However, the involvement of genes related to inflammation and immune exchange environment status in the prognosis of IPF remains to be further clarified. The objective of this research is to establish a new model for the prediction of the overall survival (OS) rate of inflammation-related IPF.MethodsGene Expression Omnibus (GEO) was employed to obtain the three expression microarrays of IPF, including two from alveolar lavage fluid cells and one from peripheral blood mononuclear cells. To construct the risk assessment model of inflammation-linked genes, least absolute shrinkage and selection operator (lasso), univariate cox and multivariate stepwise regression, and random forest method were used. The proportion of immune cell infiltration was evaluated by single sample Gene Set Enrichment Analysis (ssGSEA) algorithm.ResultsThe value of genes linked with inflammation in the prognosis of IPF was analyzed, and a four-genes risk model was constructed, including tpbg, Myc, ffar2, and CCL2. It was highlighted by Kaplan Meier (K-M) survival analysis that patients with high-risk scores had worse overall survival time in all training and validation sets, and univariate and multivariate analysis highlighted that it has the potential to act as an independent risk indicator for poor prognosis. ROC analysis showed that the prediction efficiency of 1-, 3-, and 5-year OS time in the training set reached 0.784, 0.835, and 0.921, respectively. Immune infiltration analysis showed that Myeloid-Derived Suppressor Cells (MDSC), macrophages, regulatory T cells, cd4+ t cells, neutrophils, and dendritic cells were more infiltrated in the high-risk group than in the low-risk group.ConclusionInflammation-related genes can be well used to evaluate the IPF prognosis and impart a new idea for the treatment and follow-up management of IPF patients.

A novel model for predicting prognosis in patients with idiopathic pulmonary fibrosis based on endoplasmic reticulum stress‐related genes

“…Increasing evidence indicated that immune cells were associated with IPF (Dai et al, 2022; Moss et al, 2022; Yin et al, 2022). In addition, monocyte count had been found to be a prognostic biomarker for patients with IPF (Kreuter et al, 2021).…”

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

“…Furthermore, given the immune system is central to the maintenance of normal, physiological deposition of ECM [12] , immunology has been the hot research topic in the eld of IPF. Numerous research has revealed the difference in immune cell in ltration between IPF patients and healthy controls [13][14] and immune response involved in in ammation response and brosis process in IPF [12,15] . Although several studies have demonstrated the interaction between lactate metabolism and immune response; however, such studies have mainly focused on oncology, viral infection, and sepsis [16][17][18] , while the clear characterizations and mechanisms of the underlying lactate metabolism-immunity in IPF remain poorly understood.…”