Identification of LPCAT1 as a key biomarker for Crohn's disease based on bioinformatics and machine learnings and experimental verification

Gene. 2024 May 3:920:148519. doi: 10.1016/j.gene.2024.148519. Online ahead of print.

Abstract

Epithelial-mesenchymal transition (EMT) plays a crucial role in regulating inflammatory responses and fibrosis formation. This study aims to explore the molecular mechanisms of EMT-related genes in Crohn's disease (CD) through bioinformatics methods and identify potential key biomarkers. In our research, we identified differentially expressed genes (DEGs) related to EMT based on the GSE52746 dataset and the gene set in the GeneCards database. Key genes were identified through Lasso-cox and Random Forest and validated using the external dataset GSE10616. Immune infiltration analysis showed that Lysophosphatidylcholine acyltransferase 1 (LPCAT1) was positively correlated with Neutrophils and Macrophages M1. The Gene Set Enrichment Analysis (GSEA) results for LPCAT1 showed associations with celladhesionmolecules and ECM receptor interaction. Additionally, a lncRNA-miRNA-mRNA ceRNA network was constructed. Finally, we validated that knocking down LPCAT1 could inhibit the release of inflammatory factors, EMT, and the elevation of fibrosis indices as well as the activation of NF-κB signaling pathway in LPS-induced HT-29 cells. LPCAT1 plays an important role in the occurrence and development of CD and may become a new biomarker.

Keywords: Bioinformatics; Biomarker; Crohn's disease; EMT; LPCAT1; Machine learnings.