A no-Wnt situation for alveolar macrophage self-renewal

Integrating cellular experiments, single-cell sequencing, and machine learning to identify endoplasmic reticulum stress biomarkers in idiopathic pulmonary fibrosis

BACKGROUND

Idiopathic Pulmonary Fibrosis (IPF) presents a severe respiratory challenge with a poor prognosis due to the lack of reliable biomarkers. Recent evidence suggests that Endoplasmic Reticulum Stress (ERS) may be associated with IPF pathogenesis. This study focuses on uncovering ERS-associated biomarkers for IPF.

METHODS

Sequencing data from diverse datasets were analyzed, utilizing differential gene expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA). Endoplasmic Reticulum Stress (ERS)-related genes were extracted from the GeneCards database. Hub genes were identified through Protein-Protein Interaction (PPI) analysis. Diagnostic and prognostic models were developed using machine learning algorithms and validated across both training and validation sets. Additionally, techniques such as Cell-type Identification by Estimating Relative Subsets of RNA Transcripts and single-cell RNA sequencing were employed to identify potential IPF-related cells. These findings were further investigated to elucidate their underlying mechanisms through in vitro experiments.

RESULTS

Differentially expressed genes, WGCNA-identified blue module genes, and ERS-related genes extracted from the GeneCards database were intersected, and the resulting genes were used to construct diagnostic and prognostic models. Validation using multiple datasets indicated that both the diagnostic and prognostic models possess strong predictive capabilities. PPI analysis highlighted SPP1 as a potential hub gene in IPF. Moreover, M2 macrophages were found in higher quantities in the lung tissue of IPF patients, with a significant increase in SPP1-expressing M2 macrophages compared to the control group. In vitro experiments demonstrated that exogenous SPP1 inhibited the proliferation and migration of M2 macrophages and promoted apoptosis within a certain concentration range.

CONCLUSION

This study identifies ERS-related biomarkers in IPF, highlighting SPP1 and M2 macrophages. The resulting diagnostic and prognostic models offer strong predictive capabilities, unveiling new therapeutic avenues.

Silicon dioxide-induced endoplasmic reticulum stress of alveolar macrophages and its role on the formation of silicosis fibrosis: a review article

Silicosis is a chronic lung inflammatory disease induced by long-term inhalation of high concentrations of silicon dioxide (SiO2), characterized by pulmonary fibrosis. Inhalation of silica invades alveolar macrophages (AMs) and changes the micro-environment of the cell, resulting in abnormal morphology and dysfunction of the endoplasmic reticulum (ER). Once beyond the range of cell regulation, the endoplasmic reticulum stress (ERS) will occur, which will lead to cell damage, necrosis, and apoptosis, eventually causing silicosis fibrosis through various mechanisms. This is a complex and delicate process accompanied by various macrophage-derived cytokines. Unfortunately, the details have not been systematically summarized yet. In this review, we systematically introduce the basic two processes: the process of inducing ERS by inhaling SiO2 and the process of inducing pulmonary fibrosis by ERS. Moreover, the underlying mechanism of the above two sequential events is also be discussed. We conclude that the ERS of alveolar macrophages caused by silica dust are involved deeply in the pathogenesis of silicosis. Therefore, changing the states of SiO2-induced ERS of macrophage may be an attractive therapeutic target for silicosis fibrosis.