Blood Transcriptomics Predicts Progression of Pulmonary Fibrosis and Associated Natural Killer Cells

Comparison of Pirfenidone and Nintedanib: Post Hoc Analysis of the CleanUP-IPF Study

BACKGROUND

Antifibrotics are effective in slowing FVC decline in idiopathic pulmonary fibrosis (IPF). However, whether antifibrotic type is differentially associated with FVC decline remains inconclusive.

RESEARCH QUESTION

Are there significant differences in 12-month FVC decline between pirfenidone and nintedanib?

STUDY DESIGN AND METHODS

A post hoc analysis was performed using the Clinical Efficacy of Antimicrobial Therapy Strategy Using Pragmatic Design in IPF (CleanUP-IPF) trial (No. NCT02759120). Participants who reported using pirfenidone or nintedanib on enrollment into the trial were in the primary analysis. Spirometry was scheduled at baseline and the 12- and 24-month study visits. Linear mixed-effects models with random intercept and slope were used to examine changes in FVC over time. Models were adjusted for age, sex, smoking history, coronary artery disease history, baseline FVC, and 12-month spline term. Survival and nonelective respiratory hospitalization by antifibrotic type were determined using Cox regression models with adjustment for age, sex, smoking history, coronary artery disease history, and baseline FVC and diffusing capacity for carbon monoxide.

RESULTS

Out of the 513 participants with IPF randomized in the CleanUP-IPF trial, 407 reported using pirfenidone (n = 264, 65%) or nintedanib (n = 143, 35%). The pirfenidone group had more participants with a history of coronary artery disease than the nintedanib group (34.1% vs 20.3%, respectively). Patients treated with nintedanib had a higher 12-month visit FVC than patients treated with pirfenidone (mean difference, 106 mL; 95% CI, 34-178). This difference was attenuated at the 24-month study visit. There were no significant differences in overall survival and nonelective respiratory hospitalization between the pirfenidone- and nintedanib-treated groups.

INTERPRETATION

Patients with IPF who used nintedanib had a slower 12-month FVC decline than pirfenidone in a post hoc analysis of a clinical trial.

Pyroptosis-related signatures predict immune characteristics and prognosis in IPF

The purpose of this work was to use integrated bioinformatics analysis to screen for pyroptosis-related genes (PRGs) and possible immunological phenotypes linked to the development and course of IPF. Transcriptome sequencing datasets GSE70866, GSE47460 and GSE150910 were obtained from GEO database. From the GSE70866 database, 34 PRGs with differential expression were found in IPF as compared to healthy controls. In addition, a diagnostic model containing 4 genes PRGs (CAMP, MKI67, TCEA3 and USP24) was constructed based on LASSO logistic regression. The diagnostic model showed good predictive ability to differentiate between IPF and healthy, with ROC-AUC ranging from 0.910 to 0.997 in GSE70866 and GSE150910 datasets. Moreover, based on a combined cohort of the Freiburg and the Siena cohorts from GSE70866 dataset, we identified ten PRGs that might predict prognosis for IPF. We constructed a prognostic model that included eight PRGs (CLEC5A, TREM2, MMP1, IRF2, SEZ6L2, ADORA3, NOS2, USP24) by LASSO Cox regression and validated it in the Leuven cohort. The risk model divided IPF patients from the combined cohort into high-risk and low-risk subgroups. There were significant differences between the two subgroups in terms of IPF survival and GAP stage. There is a close correlation between leukocyte migration, plasma membrane junction, and poor prognosis in a high-risk subgroup. Furthermore, a high-risk score was associated with more plasma cells, activated NK cells, monocytes, and activated mast cells. Additionally, we identified HDAC inhibitors in the cMAP database that might be therapeutic for IPF. To summarize, pyroptosis and its underlying immunological features are to blame for the onset and progression of IPF. PRG-based predictive models and drugs may offer new treatment options for IPF.

Machine learning identified MDK score has prognostic value for idiopathic pulmonary fibrosis based on integrated bulk and single cell expression data

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease that poses a significant challenge to medical professionals due to its increasing incidence and prevalence coupled with the limited understanding of its underlying molecular mechanisms. In this study, we employed a novel approach by integrating five expression datasets from bulk tissue with single-cell datasets; they underwent pseudotime trajectory analysis, switch gene selection, and cell communication analysis. Utilizing the prognostic information derived from the GSE47460 dataset, we identified 22 differentially expressed switch genes that were correlated with clinical indicators as important genes. Among these genes, we found that the midkine (MDK) gene has the potential to serve as a marker of Idiopathic pulmonary fibrosis because its cellular communicating genes are differentially expressed in the epithelial cells. We then utilized midkine and its cellular communication-related genes to calculate the midkine score. Machine learning models were further constructed through midkine and related genes to predict Idiopathic pulmonary fibrosis disease through the bulk gene expression datasets. The midkine score demonstrated a correlation with clinical indexes, and the machine learning model achieved an AUC of 0.94 and 0.86 in the Idiopathic pulmonary fibrosis classification task based on lung tissue samples and peripheral blood mononuclear cell samples, respectively. Our findings offer valuable insights into the pathogenesis of Idiopathic pulmonary fibrosis, providing new therapeutic directions and target genes for further investigation.

A comprehensive cuproptosis score and associated gene signatures reveal prognostic and immunological features of idiopathic pulmonary fibrosis

Background

Cuproptosis, the most recently identified and regulated cell death, depends on copper ions in vivo. Copper regulates the pathogenesis of Idiopathic pulmonary fibrosis (IPF), but the mechanism of action underlying cuproptosis in IPF remains unclear.

Methods

We identified three cuproptosis patterns based on ten cuproptosis-related genes using unsupervised consensus clustering. We quantified these patterns using a PCA algorithm to construct a cuproptosis score. ssGSEA and the Cibersort algorithm assessed the immune profile of IPF patients. GSEA and GSVA were used to analyze the functional differences in different molecular patterns. Drug susceptibility prediction based on cuproptosis scores and meaningful gene markers was eventually screened in combination with external public data sets,in vitro experiments and our cases.

Results

Of the three types of cuproptosis-related clusters identified in the study, patients in the clusterA, geneclusterB, and score-high groups showed improved prognoses. Moreover, each cluster exhibited differential immune characteristics, with the subtype showing a poorer prognosis associated with an immune overreaction. Cuproptosis score can be an independent risk factor for predicting the prognosis of IPF patients. GSEA showed a significant functional correlation between the score and cuproptosis. The genes AKAP9, ANK3, C6orf106, LYRM7, and MBNL1, were identified as prognostic-related signatures in IPF patients. The functional role of immune regulation in IPF was further explored by correlating essential genes with immune factors. Also, the nomogram constructed by cumulative information from gene markers and cuproptosis score showed reliable clinical application.

Conclusions

Cuproptosis patterns differ significantly in the prognosis and immune characteristics of IPF patients. The cuproptosis score and five gene signatures can provide a reliable reference in the prognosis and diagnosis of IPF.

Combination of BAL and Computed Tomography Differentiates Progressive and Non-progressive Fibrotic Lung Diseases

Rationale: Identifying patients with pulmonary fibrosis (PF) at risk of progression can guide management. Objectives: To explore the utility of combining baseline BAL and computed tomography (CT) in differentiating progressive and nonprogressive PF. Methods: The derivation cohort consisted of incident cases of PF for which BAL was performed as part of a diagnostic workup. A validation cohort was prospectively recruited with identical inclusion criteria. Baseline thoracic CT scans were scored for the extent of fibrosis and usual interstitial pneumonia (UIP) pattern. The BAL lymphocyte proportion was recorded. Annualized FVC decrease of >10% or death within 1 year was used to define disease progression. Multivariable logistic regression identified the determinants of the outcome. The optimum binary thresholds (maximal Wilcoxon rank statistic) at which the extent of fibrosis on CT and the BAL lymphocyte proportion could distinguish disease progression were identified. Measurements and Main Results: BAL lymphocyte proportion, UIP pattern, and fibrosis extent were significantly and independently associated with disease progression in the derivation cohort (n = 240). Binary thresholds for increased BAL lymphocyte proportion and extensive fibrosis were identified as 25% and 20%, respectively. An increased BAL lymphocyte proportion was rare in patients with a UIP pattern (8 of 135; 5.9%) or with extensive fibrosis (7 of 144; 4.9%). In the validation cohort (n = 290), an increased BAL lymphocyte proportion was associated with a significantly lower probability of disease progression in patients with nonextensive fibrosis or a non-UIP pattern. Conclusions: BAL lymphocytosis is rare in patients with extensive fibrosis or a UIP pattern on CT. In patients without a UIP pattern or with limited fibrosis, a BAL lymphocyte proportion of ⩾25% was associated with a lower likelihood of progression.

PCSK6 and Survival in Idiopathic Pulmonary Fibrosis

Rationale: Idiopathic pulmonary fibrosis (IPF) is a devastating disease characterized by limited treatment options and high mortality. A better understanding of the molecular drivers of IPF progression is needed. Objectives: To identify and validate molecular determinants of IPF survival. Methods: A staged genome-wide association study was performed using paired genomic and survival data. Stage I cases were drawn from centers across the United States and Europe and stage II cases from Vanderbilt University. Cox proportional hazards regression was used to identify gene variants associated with differential transplantation-free survival (TFS). Stage I variants with nominal significance (P < 5 × 10-5) were advanced for stage II testing and meta-analyzed to identify those reaching genome-wide significance (P < 5 × 10-8). Downstream analyses were performed for genes and proteins associated with variants reaching genome-wide significance. Measurements and Main Results: After quality controls, 1,481 stage I cases and 397 stage II cases were included in the analysis. After filtering, 9,075,629 variants were tested in stage I, with 158 meeting advancement criteria. Four variants associated with TFS with consistent effect direction were identified in stage II, including one in an intron of PCSK6 (proprotein convertase subtilisin/kexin type 6) reaching genome-wide significance (hazard ratio, 4.11 [95% confidence interval, 2.54-6.67]; P = 9.45 × 10-9). PCSK6 protein was highly expressed in IPF lung parenchyma. PCSK6 lung staining intensity, peripheral blood gene expression, and plasma concentration were associated with reduced TFS. Conclusions: We identified four novel variants associated with IPF survival, including one in PCSK6 that reached genome-wide significance. Downstream analyses suggested that PCSK6 protein plays a potentially important role in IPF progression.

IL-8 concurrently promotes idiopathic pulmonary fibrosis mesenchymal progenitor cell senescence and PD-L1 expression enabling escape from immune cell surveillance

Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic lung disease. We discovered fibrogenic mesenchymal progenitor cells (MPCs) in the lungs of IPF patients that display cell-autonomous fibrogenicity and drive fibrotic progression. In a study of the IPF MPC nuclear proteome, we identified DNA damage as one of the most altered functions in IPF MPCs. In prior work we found that IL-8 drives IPF MPC self-renewal. IL-8 can promote replicative stress and DNA damage and induce senescence through the CXCR2 receptor. We hypothesized that IL-8 promotes DNA damage-mediated senescence in IPF MPCs. We show that IL-8 induces DNA damage and promotes IPF MPC senescence. We discovered that IL-8 concurrently promotes senescence and upregulation of the programmed death ligand 1 (PD-L1) in a CXCR2-dependent manner. Disruption of programmed cell death protein-1 (PD-1)-PD-L1 interaction promotes natural killer (NK) cell killing of IPF MPCs in vitro and arrests IPF MPC-mediated experimental lung fibrosis in vivo. Immunohistochemical (IHC) analysis of IPF lung tissue identified PD-L1-expressing IPF MPCs codistributing with NK cells and β-galactosidase-positive cells. Our data indicate that IL-8 simultaneously promotes IPF MPC DNA damage-induced senescence and high PD-L1 expression, enabling IPF MPCs to elude immune cell-targeted removal. Disruption of PD-1-PD-L1 interaction may limit IPF MPC-mediated fibrotic progression.NEW & NOTEWORTHY Here we show that IL-8 concurrently promotes senescence and upregulation of PD-L1 in IPF MPCs. IHC analysis identifies the presence of senescent IPF MPCs intermingled with NK cells in the fibroblastic focus, suggesting that senescent MPCs elude immune cell surveillance. We demonstrate that disruption of PD-1/PD-L1 interaction promotes NK cell killing of IPF MPCs and arrests IPF MPC-mediated experimental lung fibrosis. Disruption of PD-1/PD-L1 interaction may be one means to limit fibrotic progression.

Integrative multi-omics analysis reveals novel idiopathic pulmonary fibrosis endotypes associated with disease progression

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is characterized by the accumulation of extracellular matrix in the pulmonary interstitium and progressive functional decline. We hypothesized that integration of multi-omics data would identify clinically meaningful molecular endotypes of IPF.

METHODS

The IPF-PRO Registry is a prospective registry of patients with IPF. Proteomic and transcriptomic (including total RNA [toRNA] and microRNA [miRNA]) analyses were performed using blood collected at enrollment. Molecular data were integrated using Similarity Network Fusion, followed by unsupervised spectral clustering to identify molecular subtypes. Cox proportional hazards models tested the relationship between these subtypes and progression-free and transplant-free survival. The molecular subtypes were compared to risk groups based on a previously described 52-gene (toRNA expression) signature. Biological characteristics of the molecular subtypes were evaluated via linear regression differential expression and canonical pathways (Ingenuity Pathway Analysis [IPA]) over-representation analyses.

RESULTS

Among 232 subjects, two molecular subtypes were identified. Subtype 1 (n = 105, 45.3%) and Subtype 2 (n = 127, 54.7%) had similar distributions of age (70.1 +/- 8.1 vs. 69.3 +/- 7.6 years; p = 0.31) and sex (79.1% vs. 70.1% males, p = 0.16). Subtype 1 had more severe disease based on composite physiologic index (CPI) (55.8 vs. 51.2; p = 0.002). After adjusting for CPI and antifibrotic treatment at enrollment, subtype 1 experienced shorter progression-free survival (HR 1.79, 95% CI 1.28,2.56; p = 0.0008) and similar transplant-free survival (HR 1.30, 95% CI 0.87,1.96; p = 0.20) as subtype 2. There was little agreement in the distribution of subjects to the molecular subtypes and the risk groups based on 52-gene signature (kappa = 0.04, 95% CI= -0.08, 0.17), and the 52-gene signature risk groups were associated with differences in transplant-free but not progression-free survival. Based on heatmaps and differential expression analyses, proteins and miRNAs (but not toRNA) contributed to classification of subjects to the molecular subtypes. The IPA showed enrichment in pulmonary fibrosis-relevant pathways, including mTOR, VEGF, PDGF, and B-cell receptor signaling.

CONCLUSIONS

Integration of transcriptomic and proteomic data from blood enabled identification of clinically meaningful molecular endotypes of IPF. If validated, these endotypes could facilitate identification of individuals likely to experience disease progression and enrichment of clinical trials.

TRIAL REGISTRATION

NCT01915511.

Potential of resveratrol in the treatment of interstitial lung disease

Interstitial lung disease (ILD) is a heterogeneous group of diseases characterized by lung injury caused by lung fibroblast proliferation, interstitial inflammation, and fibrosis. Different cell signal transduction pathways are activated in response to various proinflammatory or fibrotic cytokines, such as IL-6, and these cytokines are increased in different ILDs. The overexpressed cytokines and growth factors in ILD can activate TGF-β/Smad2/3/4, NF-κB, and JAK/STAT signal transduction pathways, promote the activation of immune cells, increase the release of pro-inflammatory and pro-fibrotic factors, differentiate fibroblasts into myofibroblasts, and promote the occurrence and development of ILD. This finding suggests the importance of signal transduction pathways in patients with ILD. Recent evidence suggests that resveratrol (RSV) attenuates excessive inflammation and pulmonary fibrosis by inhibiting the TGF-β/Smad2/3/4, NF-κB, and JAK/STAT signal transduction pathways and overactivation of immune cells. In this review, advances in lung protection and the underlying mechanisms of RSV are summarized, and the potential efficacy of RSV as a promising treatment option for ILD is highlighted.

The Effects of Interstitial Lung Diseases on Alveolar Extracellular Vesicles Profile: A Multicenter Study

Diagnosis of interstitial lung diseases (ILD) is difficult to perform. Extracellular vesicles (EVs) facilitate cell-to-cell communication, and they are released by a variety of cells. Our goal aimed to investigate EV markers in bronchoalveolar lavage (BAL) from idiopathic pulmonary fibrosis (IPF), sarcoidosis and hypersensitivity pneumonitis (HP) cohorts. ILD patients followed at Siena, Barcelona and Foggia University Hospitals were enrolled. BAL supernatants were used to isolate the EVs. They were characterized by flow cytometry assay through MACSPlex Exsome KIT. The majority of alveolar EV markers were related to the fibrotic damage. CD56, CD105, CD142, CD31 and CD49e were exclusively expressed by alveolar samples from IPF patients, while HP showed only CD86 and CD24. Some EV markers were common between HP and sarcoidosis (CD11c, CD1c, CD209, CD4, CD40, CD44, CD8). Principal component analysis distinguished the three groups based on EV markers with total variance of 60.08%. This study has demonstrated the validity of the flow cytometric method to phenotype and characterize EV surface markers in BAL samples. The two granulomatous diseases, sarcoidosis and HP, cohorts shared alveolar EV markers not revealed in IPF patients. Our findings demonstrated the viability of the alveolar compartment allowing identification of lung-specific markers for IPF and HP.

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.

Spatially resolved deconvolution of the fibrotic niche in lung fibrosis

A defining pathological feature of human lung fibrosis is localized tissue heterogeneity, which challenges the interpretation of transcriptomic studies that typically lose spatial information. Here we investigate spatial gene expression in diagnostic tissue using digital profiling technology. We identify distinct, region-specific gene expression signatures as well as shared gene signatures. By integration with single-cell data, we spatially map the cellular composition within and distant from the fibrotic niche, demonstrating discrete changes in homeostatic and pathologic cell populations even in morphologically preserved lung, while through ligand-receptor analysis, we investigate cellular cross-talk within the fibrotic niche. We confirm findings through bioinformatic, tissue, and in vitro analyses, identifying that loss of NFKB inhibitor zeta in alveolar epithelial cells dysregulates the TGFβ/IL-6 signaling axis, which may impair homeostatic responses to environmental stress. Thus, spatially resolved deconvolution advances understanding of cell composition and microenvironment in human lung fibrogenesis.

Blood gene expression risk profiles and interstitial lung abnormalities: COPDGene and ECLIPSE cohort studies

BACKGROUND

Interstitial lung abnormalities (ILA) are radiologic findings that may progress to idiopathic pulmonary fibrosis (IPF). Blood gene expression profiles can predict IPF mortality, but whether these same genes associate with ILA and ILA outcomes is unknown. This study evaluated if a previously described blood gene expression profile associated with IPF mortality is associated with ILA and all-cause mortality.

METHODS

In COPDGene and ECLIPSE study participants with visual scoring of ILA and gene expression data, we evaluated the association of a previously described IPF mortality score with ILA and mortality. We also trained a new ILA score, derived using genes from the IPF score, in a subset of COPDGene. We tested the association with ILA and mortality on the remainder of COPDGene and ECLIPSE.

RESULTS

In 1469 COPDGene (training n = 734; testing n = 735) and 571 ECLIPSE participants, the IPF score was not associated with ILA or mortality. However, an ILA score derived from IPF score genes was associated with ILA (meta-analysis of test datasets OR 1.4 [95% CI: 1.2-1.6]) and mortality (HR 1.25 [95% CI: 1.12-1.41]). Six of the 11 genes in the ILA score had discordant directions of effects compared to the IPF score. The ILA score partially mediated the effects of age on mortality (11.8% proportion mediated).

CONCLUSIONS

An ILA gene expression score, derived from IPF mortality-associated genes, identified genes with concordant and discordant effects on IPF mortality and ILA. These results suggest shared, and unique biologic processes, amongst those with ILA, IPF, aging, and death.

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

Background: Increasing evidence has revealed that epithelial–mesenchymal transition (EMT) and immunity play key roles in idiopathic pulmonary fibrosis (IPF). However, correlation between EMT and immune response and the prognostic significance of EMT in IPF remains unclear.

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 the Estimation of STromal and Immune cells in MAlignant Tumors 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 these 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 signatures and correlation between the EMT- and immune-related signatures 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 signatures.

Results: Functional enrichment analysis suggested that these genes were mainly involved in immune response. Moreover, the EMT- and immune-related signatures were constructed based on three EMT- and immune-related genes (IL1R2, S100A12, and CCL8), and the 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, and the calibration curve showed that the nomogram could visually and accurately predict the 1-, 2-, 3-year survival of IPF patients. Finally, we further found that immune-related pathways were activated in the high-risk group of patients, and the EMT- and immune-related signatures were associated with NK cells activated, macrophages M0, dendritic cells resting, mast cells resting, and mast cells activated. qRT-PCR suggested that the mRNA expression of IL1R2, S100A12, and CCL8 was upregulated in whole blood of IPF patients compared with normal samples.

Conclusion: IL1R2, S100A12, and CCL8 might play key roles in IPF by regulating immune response and could be used as prognostic biomarkers of IPF.

Anti-Inflammatory and Anti-Fibrotic Effect of Immortalized Mesenchymal-Stem-Cell-Derived Conditioned Medium on Human Lung Myofibroblasts and Epithelial Cells

Idiopathic pulmonary fibrosis (IPF) is caused by progressive lung tissue impairment due to extended chronic fibrosis, and it has no known effective treatment. The use of conditioned media (CM) from an immortalized human adipose mesenchymal stem cell line could be a promising therapeutic strategy, as it can reduce both fibrotic and inflammatory responses. We aimed to investigate the anti-inflammatory and anti-fibrotic effect of CM on human pulmonary subepithelial myofibroblasts (hPSM) and on A549 pulmonary epithelial cells, treated with pro-inflammatory or pro-fibrotic mediators. CM inhibited the proinflammatory cytokine-induced mRNA and protein production of various chemokines in both hPSMs and A549 cells. It also downregulated the mRNA expression of IL-1α, but upregulated IL-1β and IL-6 mRNA production in both cell types. CM downregulated the pro-fibrotic-induced mRNA expression of collagen Type III and the migration rate of hPSMs, but upregulated fibronectin mRNA production and the total protein collagen secretion. CM's direct effect on the chemotaxis and cell recruitment of immune-associated cells, and its indirect effect on fibrosis through the significant decrease in the migration capacity of hPSMs, makes it a plausible candidate for further development towards a therapeutic treatment for IPF.

S100A12 as Biomarker of Disease Severity and Prognosis in Patients With Idiopathic Pulmonary Fibrosis

Background

Idiopathic pulmonary fibrosis (IPF) is one of interstitial lung diseases (ILDs) with poor prognosis. S100 calcium binding protein A12 (S100A12) has been reported as a prognostic serum biomarker in the IPF, but its correlation with IPF remains unclear in the lung tissue and bronchoalveolar lavage fluids (BALF).

Methods

Datasets were collected from the Gene Expression Omnibus (GEO) database. Person correlation coefficient, Kaplan–Meier analysis, Cox regression analysis, functional enrichment analysis and so on were used. And single cell RNA-sequencing (scRNA-seq) analysis was also used to explore the role of S100A12 and related genes in the IPF.

Results

S100A12 was mainly and highly expressed in the monocytes, and its expression was downregulated in the lung of patients with IPF according to scRNA-seq and the transcriptome analysis. However, S100A12 expression was upregulated both in blood and BALF of patients with IPF. In addition, 10 genes were found to interact with S100A12 according to protein–protein interaction (PPI) network, and the first four transcription factors (TF) targeted these genes were found according to hTFtarget database. Two most significant co-expression genes of S100A12 were S100A8 and S100A9. The 3 genes were significantly negatively associated with lung function and positively associated with the St. George’s Respiratory Questionnaire (SGRQ) scores in the lung of patients with IPF. And, high expression of the 3 genes was associated with higher mortality in the BALF, and shorter transplant-free survival (TFS) and progression-free survival (PFS) time in the blood. Prognostic predictive value of S100A12 was more superior to S100A8 and S100A9 in patients with IPF, and the composited variable [S100A12 + GAP index (gender, age, and physiological index)] may be a more effective predictive index.

Conclusion

These results imply that S100A12 might be an efficient disease severity and prognostic biomarker in patients with IPF.

CD247, a Potential T Cell-Derived Disease Severity and Prognostic Biomarker in Patients With Idiopathic Pulmonary Fibrosis

Background

Idiopathic pulmonary fibrosis (IPF) has high mortality worldwide. The CD247 molecule (CD247, as known as T-cell surface glycoprotein CD3 zeta chain) has been reported as a susceptibility locus in systemic sclerosis, but its correlation with IPF remains unclear.

Methods

Datasets were acquired by researching the Gene Expression Omnibus (GEO). CD247 was identified as the hub gene associated with percent predicted diffusion capacity of the lung for carbon monoxide (Dlco% predicted) and prognosis according to Pearson correlation, logistic regression, and survival analysis.

Results

CD247 is significantly downregulated in patients with IPF compared with controls in both blood and lung tissue samples. Moreover, CD247 is significantly positively associated with Dlco% predicted in blood and lung tissue samples. Patients with low-expression CD247 had shorter transplant-free survival (TFS) time and more composite end-point events (CEP, death, or decline in FVC >10% over a 6-month period) compared with patients with high-expression CD247 (blood). Moreover, in the follow-up 1st, 3rd, 6th, and 12th months, low expression of CD247 was still the risk factor of CEP in the GSE93606 dataset (blood). Thirteen genes were found to interact with CD247 according to the protein-protein interaction network, and the 14 genes including CD247 were associated with the functions of T cells and natural killer (NK) cells such as PD-L1 expression and PD-1 checkpoint pathway and NK cell-mediated cytotoxicity. Furthermore, we also found that a low expression of CD247 might be associated with a lower activity of TIL (tumor-infiltrating lymphocytes), checkpoint, and cytolytic activity and a higher activity of macrophages and neutrophils.

Conclusion

These results imply that CD247 may be a potential T cell-derived disease severity and prognostic biomarker for IPF.

Prognostic role of NK cell percentages in bronchoalveolar lavage from patients with different fibrotic interstitial lung diseases

BAL cellularity and lymphocyte immunophenotyping offer insights into lung inflammatory status. Natural killer (NK) cells are efficient effector cells, producing pro-inflammatory cytokines. A better understanding of the biology of NK cells in BAL in the lungs is necessary to improve the pathogenesis of fibrotic ILD and develop prospective targeted treatments. Our aim was to analyse NK and NKT-like cell percentages in BAL from 159 patients with different ILD: f-HP, f-NSIP, IPF and CTD-ILD, to evaluate their potential diagnostic/prognostic role. BAL NK cell percentages showed significantly higher values in IPF than in f-HP and f-NSIP, while BAL NKT-like cells showed significantly lower values in the f-NSIP than the f-HP and IPF. A cut-off of 4%NK cells in BAL of IPF showed a significant difference in survival rate. It suggests a possible new marker of survival and raises the possibility of new targeted approach in treatment and management of IPF.