AUTHOR=Zheng Jiafeng , Dong Hanquan , Zhang Tongqiang , Ning Jing , Xu Yongsheng , Cai Chunquan TITLE=Development and Validation of a Novel Gene Signature for Predicting the Prognosis of Idiopathic Pulmonary Fibrosis Based on Three Epithelial-Mesenchymal Transition and Immune-Related Genes JOURNAL=Frontiers in Genetics VOLUME=Volume 13 - 2022 YEAR=2022 URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.865052 DOI=10.3389/fgene.2022.865052 ISSN=1664-8021 ABSTRACT=Background: Increasing evidence has revealed that epithelial-mesenchymal transition (EMT) and immune play key roles in idiopathic pulmonary fibrosis (IPF). Methods: Two microarray expression profiling datasets (GSE70866 and GSE28221) were downloaded from the Gene Expression Omnibus (GEO) database. EMT and immune-related genes were identified by gene set variation analysis (GSVA) and Estimation of Stromal and Immune cells in MAlignant Tumours using Expression data (ESTIMATE) algorithm. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to investigate the functions of theses EMT and immune-related genes. Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were used to screen prognostic genes and establish a gene signature. Gene Set Enrichment Analysis (GSEA) and Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) were used to investigate the function of the EMT and immune-related signature and correlation between the EMT and immune-related signature and immune cell infiltration. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to investigate the mRNA expression of genes in the EMT and immune-related signature. Results: Moreover, a EMT and immune-related signature was constructed based on three EMT and immune-related genes (IL1R2, S100A12, and CCL8), and K-M and ROC curves presented that the signature could affect the prognosis of IPF patients and could predict the 1-, 2-, and 3-year survival well. Furthermore, a nomogram was developed based on the expression of IL1R2, S100A12, and CCL8,. Finally, we further found that immune-related pathways were activated in the high-risk group of patients and the EMT and immune-related signature was associated with NK cells activated, macrophages M0, dendritic cells resting, mast cells resting, mast cells activated. QRT-PCR suggested that the mRNA expression of IL1R2, S100A12, and CCL8 was up-regulated in whole blood of IPF patients compared with normal samples. Conclusion: IL1R2, S100A12,and CCL8 might play key roles in IPF through regulating immune response and could be used as the prognostic biomarkers of IPF.