Decline in Mast Cell Density During Diffuse Alveolar Damage in Idiopathic Pulmonary Fibrosis

FcεRI deficiency alleviates silica-induced pulmonary inflammation and fibrosis

Silicosis is one of the most important occupational diseases worldwide, caused by inhalation of silica particles or free crystalline silicon dioxide. As a disease with high mortality, it has no effective treatment and new therapeutic targets are urgently needed. Recent studies have identified FCER1A, encoding α-subunit of the immunoglobulin E (IgE) receptor FcεRI, as a candidate gene involved in the biological pathways leading to respiratory symptoms. FcεRI is known to be important in allergic asthma, but its role in silicosis remains unclear. In this study, serum IgE concentrations and FcεRI expression were assessed in pneumoconiosis patients and silica-exposed mice. The role of FcεRI was explored in a silica-induced mouse model using wild-type and FcεRI-deficient mice. The results showed that serum IgE concentrations were significantly elevated in both pneumoconiosis patients and mice exposed to silica compared with controls. The mRNA and protein expression of FcεRI were also significantly increased in the lung tissue of patients and silica-exposed mice. FcεRI deficiency significantly attenuated the changes in lung function caused by silica exposure. Silica-induced elevations of IL-1β, IL-6, and TNF-α were significantly attenuated in the lung tissue and bronchoalveolar lavage fluid (BALF) of FcεRI-deficient mice compared with wild-type controls. Additionally, FcεRI-deficient mice showed a significantly lower score of pulmonary fibrosis than wild-type mice following exposure to silica, with significantly lower hydroxyproline content and expression of fibrotic genes Col1a1 and Fn1. Immunofluorescent staining suggested FcεRI mainly on mast cells. Mast cell degranulation took place after silica exposure, as shown by increased serum histamine levels and β-hexosaminidase activity, which were significantly reduced in FcεRI-deficient mice compared with wild-type controls. Together, these data showed that FcεRI deficiency had a significant protective effect against silica-induced pulmonary inflammation and fibrosis. Our findings provide new insights into the pathophysiological mechanisms of silica-induced pulmonary fibrosis and a potential target for the treatment of silicosis.

A novel gene signature based on the hub genes of COVID-19 predicts the prognosis of idiopathic pulmonary fibrosis

Background: Increasing evidence has demonstrated that there was a strong correlation between COVID-19 and idiopathic pulmonary fibrosis (IPF). However, the studies are limited, and the real biological mechanisms behind the IPF progression were still uncleared.

Methods: GSE70866 and GSE 157103 datasets were downloaded. The weight gene co-expression network analysis (WGCNA) algorithms were conducted to identify the most correlated gene module with COVID-19. Then the genes were extracted to construct a risk signature in IPF patients by performing Univariate and Lasso Cox Regression analysis. Univariate and Multivariate Cox Regression analyses were used to identify the independent value for predicting the prognosis of IPF patients. What’s more, the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and gene set enrichment analysis (GSEA) were conducted to unveil the potential biological pathways. CIBERSORT algorithms were performed to calculate the correlation between the risk score and immune cells infiltrating levels.

Results: Two hundred thirty three differentially expressed genes were calculated as the hub genes in COVID-19. Fourteen of these genes were identified as the prognostic differentially expressed genes in IPF. Three (MET, UCHL1, and IGF1) of the fourteen genes were chosen to construct the risk signature. The risk signature can greatly predict the prognosis of high-risk and low-risk groups based on the calculated risk score. The functional pathway enrichment analysis and immune infiltrating analysis showed that the risk signature may regulate the immune-related pathways and immune cells.

Conclusion: We identified prognostic differentially expressed hub genes related to COVID-19 in IPF. A risk signature was constructed based on those genes and showed great value for predicting the prognosis in IPF patients. What’s more, three genes in the risk signature may be clinically valuable as potential targets for treating IPF patients and IPF patients with COVID-19.

NHLRC2 expression is increased in idiopathic pulmonary fibrosis

BACKGROUND

Variants of NHL repeat-containing protein 2 (NHLRC2) have been associated with severe fibrotic interstitial lung disease in early childhood and NHLRC2 has been listed as a differentially expressed gene between rapidly and slowly progressing idiopathic pulmonary fibrosis (IPF) patients. However, its cell type-specific localization in human lung tissue is unknown. The aim of this study was to evaluate NHLRC2 mRNA and protein expression in different cell types of lung tissue samples and to investigate the effect of transforming growth factor (TGF)-β1 exposure on NHLRC2 expression in vitro.

METHODS

The NHLRC2 expression in lung tissue samples was studied by immunohistochemistry (50 IPF, 10 controls) and mRNA in situ hybridization (8 IPF, 3 controls). The immunohistochemical NHLRC2 expression was quantified with image analysis software and associated with the clinical and smoking data of the patients. NHLRC2 expression levels in primary stromal and small airway epithelial cell lines after exposure to TGF-β1 was measured by quantitative reverse transcription polymerase chain reaction and Western blot analysis.

RESULTS

NHLRC2 expression was detected especially in bronchiolar epithelial cells, type II pneumocytes and macrophages in normal lung. In the lungs of IPF patients, NHLRC2 was mainly expressed in hyperplastic alveolar epithelial cells lining fibroblast foci and honeycombs. NHLRC2 expression assessed by image analysis was higher in IPF compared to controls (p < 0.001). Ever-smokers had more prominent NHLRC2 staining than non-smokers (p = 0.037) among IPF patients. TGF-β1 exposure did not influence NHLRC2 levels in lung cell lines.

CONCLUSIONS

NHLRC2 expression was higher in IPF compared to controls being widely expressed in type II pneumocytes, macrophages, bronchiolar epithelium, and hyperplastic alveolar epithelium. Additionally, its expression was not regulated by the exposure to TGF-β1 in vitro. Further studies are needed to clarify the role of NHLRC2 in IPF.

Construction and Validation of a Novel Prognostic Signature of Idiopathic Pulmonary Fibrosis by Identifying Subtypes Based on Genes Related to 7-Methylguanosine Modification

Background: Idiopathic pulmonary fibrosis (IPF) is the interstitial lung disease with the highest incidence and mortality. The lack of specific markers results in limited treatment methods for IPF patients. Numerous prognostic signatures represented effective indexes in predicting the survival of patients in various diseases; however, little is investigated on their application in IPF.

Methods: This study attempted to explore the clinical markers suitable for IPF by constructing a prognostic signature from the perspective of 7-methylguanosine (m7G). An m7G-related prognostic signature (m7GPS) was established based on the discovery cohort with the LASSO algorithm and was verified by internal and external validation cohorts. The area under the curve (AUC) values were utilized to assess the accuracy of m7GPS in predicting the prognosis of IPF patients and the ability of m7GPS in screening IPF patients. Kaplan-Meier curves and Cox regression analyses were used to identify the relationship of m7GPS with the prognosis of IPF individuals. Enrichment analyses, CIBERSORT algorithm, and weighted gene co-expression network analysis were applied to explore the underlying mechanisms and correlation of m7GPS in IPF.

Results: The two m7G regulatory genes can divide IPF into subtypes 1 and 2, and subtype 2 demonstrated a poor prognosis for IPF patients (p < 0.05). For the first time in this field, the m7GPS was constructed. m7GPS made it feasible to predict the 1–5 years survival status of IPF patients (AUC = 0.730–0.971), and it was an independent prognostic risk factor for IPF patients (hazard ratio > 1, p < 0.05). The conspicuous ability of m7GPS to screen IPF patients from the healthy was also revealed by an AUC value of 0.960. The roles of m7GPS in IPF may link to inflammation, immune response, and immune cell levels. Seven genes (CYR61, etc.) were identified as hub genes of m7GPS in IPF. Three drugs (ZM447439-1050, AZD1332-1463, and Ribociclib-1632) were considered sensitive to patients with high m7GPS risk scores.

Conclusion: This study developed a novel m7GPS, which is a reliable indicator for predicting the survival status of IPF patients and is identified as an effective marker for prognosis and screening of IPF patients.