Bayesian probit regression model for the diagnosis of pulmonary fibrosis: proof-of-principle

Plausible role of INPP4A dysregulation in idiopathic pulmonary fibrosis

INPP4A has been shown to be involved in the regulation of cell proliferation and apoptosis of multiple cell types including fibroblasts. Previous reports from our group have demonstrated the role of inositol polyphosphate 4-phosphatase Type I A (INPP4A) in these functions. Though existing evidences suggest a critical role for INPP4A in the maintenance of lung homeostasis, its role in chronic lung diseases is relatively under explored. In the current study, we made an attempt to understand the regulation of INPP4A in idiopathic pulmonary fibrosis (IPF). Through integration of relevant INPP4A gene expression data from public repositories with our results from in vitro experiments and mouse models, we show that INPP4A is altered in IPF. Interestingly, the direction of the change is dependent both on the disease stage and the region of the lung used. INPP4A was found to be upregulated when analyzed in lung sample representative of the whole lung, but was downregulated in the fibrotic regions of the lung. Similarly, INPP4A was found to be high, compared to controls, only in the early stage of the disease. Though the observed increase in INPP4A was found to be negatively correlated to physiological indices, FVC, and DLCO, of lung function, treatment with anti-INPP4A antibody worsened the condition in bleomycin treated mice. These contrasting results taken together are suggestive of a nuanced regulation of INPP4A in IPF which is dependent on the disease stage, cellular state and extent of fibrosis in the lung region being analyzed.

Bioinformatics-based dynamics of cuproptosis -related indicators in experimental silicosis

Pneumoconiosis is one of the most serious occupational diseases worldwide. Silicosis due to prolonged inhalation of free silica dust during occupational activities is one of the main types. Cuproptosis is a newly discovered mode of programmed cell death characterized by the accumulation of free copper in the cell, which ultimately leads to cell death. Increased copper in the serum of silicosis patients, suggests that the development of silicosis is accompanied by changes in copper metabolism, but whether cuproptosis is involved in the progression of silicosis is actually to be determined. To test this hypothesis, we screened the genetic changes in patients with idiopathic fibrosis by bioinformatics methods and predicted and functionally annotated the cuproptosis-related genes among them. Subsequently, we established a mouse silicosis model and detected the concentration of copper ions and the activity of ceruloplasmin (CP) in serum, as well as changes of the concentration of copper and cuproptosis related genes in mouse lung tissues. We identified 9 cuproptosis-related genes among the differential genes in patients with IPF at different times and the tissue-specific expression levels of ferredoxin 1 (FDX1) and Lipoyl synthase (LIAS) proteins. Furthermore, serum CP activity and copper ion levels in silicosis mice were elevated on days 7th and 56th after silica exposure. The expression of CP in mouse lung tissue elevated at all stages after silica exposure. The mRNA level of FDX1 decreased on days 7th and 56th, and the protein level remained in accordance with the mRNA level on day 56th. LIAS and Dihydrolipoamide dehydrogenase (DLD) levels were downregulated at all times after silica exposure. In addition, Heatshockprotein70 (HSP70) expression was increased on day 56. In brief, our results demonstrate that there may be cellular cuproptosis during the development of experimental silicosis in mice and show synchronization with enhanced copper loading in mice.

Drug Repurposing: A Leading Strategy for New Threats and Targets

Less than 6% of rare illnesses have an appropriate treatment option. Repurposed medications for new indications are a cost-effective and time-saving strategy that results in excellent success rates, which may significantly lower the risk associated with therapeutic development for rare illnesses. It is becoming a realistic alternative to repurposing "conventional" medications to treat joint and rare diseases considering the significant failure rates, high expenses, and sluggish stride of innovative medication advancement. This is due to delisted compounds, cheaper research fees, and faster development time frames. Repurposed drug competitors have been developed using strategic decisions based on data analysis, interpretation, and investigational approaches, but technical and regulatory restrictions must also be considered. Combining experimental and computational methodologies generates innovative new medicinal applications. It is a one-of-a-kind strategy for repurposing human-safe pharmaceuticals to treat uncommon and difficult-to-treat ailments. It is a very effective method for discovering and creating novel medications. Several pharmaceutical firms have developed novel therapies by repositioning old medications. Repurposing drugs is practical, cost-effective, and speedy and generally involves lower risks when compared to developing a new drug from the beginning.

SLC15A3 plays a crucial role in pulmonary fibrosis by regulating macrophage oxidative stress

Idiopathic pulmonary fibrosis (IPF) is a fatal and irreversible disease with few effective treatments. Alveolar macrophages (AMs) are involved in the development of IPF from the initial stages due to direct exposure to air and respond to external oxidative damage (a major inducement of pulmonary fibrosis). Oxidative stress in AMs plays an indispensable role in promoting fibrosis development. The oligopeptide histidine transporter SLC15A3, mainly expressed on the lysosomal membrane of macrophages and highly expressed in the lung, has proved to be involved in innate immune and antiviral signaling pathways. In this study, we demonstrated that during bleomycin (BLM)- or radiation-induced pulmonary fibrosis, the recruitment of macrophages induced an increase of SLC15A3 in the lung, and the deficiency of SLC15A3 protected mice from pulmonary fibrosis and maintained the homeostasis of the pulmonary microenvironment. Mechanistically, deficiency of SLC15A3 resisted oxidative stress in macrophages, and SLC15A3 interacted with the scaffold protein p62 to regulate its expression and phosphorylation activation, thereby regulating p62-nuclear factor erythroid 2-related factor 2 (NRF2) antioxidant stress pathway protein, which is related to the production of reactive oxygen species (ROS). Overall, our data provided a novel mechanism for targeting SLC15A3 to regulate oxidative stress in macrophages, supporting the therapeutic potential of inhibiting or silencing SLC15A3 for the precautions and treatment of pulmonary fibrosis.

Identification of Hub Genes and Prediction of Targeted Drugs for Rheumatoid Arthritis and Idiopathic Pulmonary Fibrosis

There is a potential link between rheumatoid arthritis (RA) and idiopathic pulmonary fibrosis (IPF). The aim of this study is to investigate the molecular processes that underlie the development of these two conditions by bioinformatics methods. The gene expression samples for RA (GSE77298) and IPF (GSE24206) were retrieved from the Gene Expression Omnibus (GEO) database. After identifying the overlapping differentially expressed genes (DEGs) for RA and IPF, we conducted functional annotation, protein-protein interaction (PPI) network analysis, and hub gene identification. Finally, we used the hub genes to predict potential medications for the treatment of both disorders. We identified 74 common DEGs for further analysis. Functional analysis demonstrated that cellular components, biological processes, and molecular functions all played a role in the emergence and progression of RA and IPF. Using the cytoHubba plugin, we identified 7 important hub genes, namely COL3A1, SDC1, CCL5, CXCL13, MMP1, THY1, and BDNF. As diagnostic indicators for RA, SDC1, CCL5, CXCL13, MMP1, and THY1 showed favorable values. For IPF, COL3A1, SDC1, CCL5, CXCL13, THY1, and BDNF were favorable diagnostic markers. Furthermore, we predicted 61 Chinese and 69 Western medications using the hub genes. Our research findings demonstrate a shared pathophysiology between RA and IPF, which may provide new insights for more mechanistic research and more effective treatments. These common pathways and hub genes identified in our study offer potential opportunities for developing more targeted therapies that can address both disorders.

Comprehensive analysis of an endoplasmic reticulum stress-related gene prediction model and immune infiltration in idiopathic pulmonary fibrosis

Background

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive interstitial lung disease. This study aimed to investigate the involvement of endoplasmic reticulum stress (ERS) in IPF and explore its correlation with immune infiltration.

Methods

ERS-related differentially expressed genes (ERSRDEGs) were identified by intersecting differentially expressed genes (DEGs) from three Gene Expression Omnibus datasets with ERS-related gene sets. Gene Set Variation Analysis and Gene Ontology were used to explore the potential biological mechanisms underlying ERS. A nomogram was developed using the risk signature derived from the ERSRDEGs to perform risk assessment. The diagnostic value of the risk signature was evaluated using receiver operating characteristics, calibration, and decision curve analyses. The ERS score of patients with IPF was measured using a single-sample Gene Set Enrichment Analysis (ssGSEA) algorithm. Subsequently, a prognostic model based on the ERS scores was established. The proportion of immune cell infiltration was assessed using the ssGSEA and CIBERSORT algorithms. Finally, the expression of ERSRDEGs was validated in vivo and in vitro via RT-qPCR.

Results

This study developed an 8-ERSRDEGs signature. Based on the expression of these genes, we constructed a diagnostic nomogram model in which agouti-related neuropeptide had a significantly greater impact on the model. The area under the curve values for the predictive value of the ERSRDEGs signature were 0.975 and 1.000 for GSE70866 and GSE110147, respectively. We developed a prognostic model based on the ERS scores of patients with IPF. Furthermore, we classified patients with IPF into two subtypes based on their signatures. The RT-qPCR validation results supported the reliability of most of our conclusions.

Conclusion

We developed and verified a risk model using eight ERSRDEGs. These eight genes can potentially affect the progression of IPF by regulating ERS and immune responses.

Hydrogen sulfide inhibits alveolar type II cell senescence and limits pulmonary fibrosis via promoting MDM2-mediated p53 degradation

AIM

Senescence of alveolar type II (AT2) cells is an important driver of pulmonary fibrosis. This study aimed to investigate whether and how dysregulation of hydrogen sulfide (H2 S) production affected AT2 cell senescence, and then explored the effect of H2 S on the communication between AT2 and fibroblasts.

METHODS

ICR mice were intratracheally administered with bleomycin (3 mg/kg). Sodium hydrosulfide (NaHS, 28 μmol/kg/d) was intraperitoneally injected for 2 weeks. The H2 S-generating enzyme cystathionine-β-synthase (CBS) knockout heterozygous (CBS+/- ) mice were used as a low H2 S production model.

RESULTS

Analysis of microarray datasets revealed downregulation of H2 S-generating enzymes in lung tissues of patients with pulmonary fibrosis. Decreased H2 S production was correlated with higher levels of cell senescence markers p53 and p21 in bleomycin-induced lung fibrosis. CBS+/- mice exhibited increased levels of p53 and p21. The numbers of AT2 cells positive for p53 and p21 were increased in CBS+/- mice as compared to control mice. H2 S donor NaHS attenuated bleomycin-induced AT2 cell senescence both in vivo and in vitro. H2 S donor suppressed bleomycin-induced senescence-associated secretory phenotype (SASP) of AT2 cells via inhibiting p53/p21 pathway, consequently suppressing proliferation and myofibroblast transdifferentiation of fibroblasts. Mechanically, H2 S suppressed p53 expression by enhancing the mouse double-minute 2 homologue (MDM2)-mediated ubiquitination and degradation of p53.

CONCLUSION

H2 S inactivated p53-p21 pathway, consequently suppressing AT2 cell senescence as well as cell communication between senescent AT2 cells and fibroblasts. Aberrant H2 S synthesis may contribute to the development of pulmonary fibrosis through promoting the activation loop involving senescent AT2 cells and activated fibroblasts.

PTK2-associated gene signature could predict the prognosis of IPF

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease with a poor prognosis. Current/available clinical prediction tools have limited sensitivity and accuracy when evaluating clinical outcomes of IPF. Research has shown that focal adhesion kinase (FAK), produced by the protein tyrosine kinase 2 (PTK2) gene, is crucial in IPF development. FAK activation is a characteristic of lesional fibroblasts; Thus, FAK may be a valuable therapeutic target or prognostic biomarker for IPF. This study aimed to create a gene signature based on PTK2-associated genes and microarray data from blood cells to predict disease prognosis in patients with IPF. PTK2 levels were found to be higher in lung tissues of IPF patients compared to healthy controls, and PTK2 inhibitor Defactinib was found to reduce TGFβ-induced FAK activation and increase α-smooth muscle actin. Although the blood PTK2 levels were higher in IPF patients, blood PTK level alone could not predict IPF prognosis. From 196 PTK2-associated genes, 11 genes were prioritized to create a gene signature (PTK2 molecular signature) and a risk score system using univariate and multivariate Cox regression analysis. Patients were divided into high-risk and low-risk groups using PTK2 molecular signature. Patients in the high-risk group experienced decreased survival rates compared to patients in the low-risk group across all discovery and validation cohorts. Further functional enrichment and immune cell proportion analyses revealed that the PTK2 molecular signature strongly reflected the activation levels of immune pathways and immune cells. These findings suggested that PTK2 is a molecular target of IPF and the PTK2 molecular signature is an effective IPF prognostic biomarker.

Combining single-cell RNA sequencing data and transcriptomic data to unravel potential mechanisms and signature genes of the progression of idiopathic pulmonary fibrosis to lung adenocarcinoma and predict therapeutic agents

Patients with idiopathic pulmonary fibrosis (IPF) have a significantly higher prevalence of lung adenocarcinoma (LUAD) than normal subjects, although the underlying association is unclear. The raw data involved were obtained from the Gene Expression Omnibus (GEO) database. Differential expression analysis and weighted gene co-expression network analysis were used to screen for differentially expressed genes (DEGs) and modular signature genes (MSGs). Genes intersecting DEGs and MSGs were considered hub genes for IPF and LUAD. Machine learning algorithms were applied to capture epithelial cell-derived signature genes (EDSGs) shared. External cohort data were exploited to validate the robustness of EDSGs. Immunohistochemical staining and K-M plots were used to denote the prognostic value of EDSGs in LUAD. Based on EDSGs, we constructed a TF-gene-miRNA regulatory network. Molecular docking can validate the strength of action between candidate drugs and EDSGs. Epithelial cells, 650 DEGs, and 1773 MSGs were shared by IPF and LUAD. As for 379 hub genes, we performed pathway and functional enrichment analysis. By analyzing sc-RNA seq data, we identified 1234 marker genes of IPF epithelial cell-derived and 1481 of LUAD. And these genes shared 8 items with 379 hub genes. Through the machine learning algorithms, we further fished TRIM2, S100A14, CYP4B1, LMO7, and SFN. The ROC curves emphasized the significance of EDSGs in predicting the onset of LUAD and IPF. The TF-gene-miRNA network revealed regulatory relationships behind EDSGs. Finally, we predicted appropriate therapeutic agents. Our study preliminarily identified potential mechanisms between IPF and LUAD, which will inform subsequent studies.

Precise identification of cell states altered in disease using healthy single-cell references

Joint analysis of single-cell genomics data from diseased tissues and a healthy reference can reveal altered cell states. We investigate whether integrated collections of data from healthy individuals (cell atlases) are suitable references for disease-state identification and whether matched control samples are needed to minimize false discoveries. We demonstrate that using a reference atlas for latent space learning followed by differential analysis against matched controls leads to improved identification of disease-associated cells, especially with multiple perturbed cell types. Additionally, when an atlas is available, reducing control sample numbers does not increase false discovery rates. Jointly analyzing data from a COVID-19 cohort and a blood cell atlas, we improve detection of infection-related cell states linked to distinct clinical severities. Similarly, we studied disease states in pulmonary fibrosis using a healthy lung atlas, characterizing two distinct aberrant basal states. Our analysis provides guidelines for designing disease cohort studies and optimizing cell atlas use.

Identification of Hub Genes in Idiopathic Pulmonary Fibrosis and Their Association with Lung Cancer by Bioinformatics Analysis

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, and irreversible disease with a high mortality rate worldwide. However, the etiology and pathogenesis of IPF have not yet been fully described. Moreover, lung cancer is a significant complication of IPF and is associated with increased mortality. Nevertheless, identifying common genes involved in developing IPF and its progression to lung cancer remains an unmet need. The present study aimed to identify hub genes related to the development of IPF by meta-analysis. In addition, we analyzed their expression and their relationship with patients' progression in lung cancer.

METHOD

Microarray datasets GSE24206, GSE21369, GSE110147, GSE72073, and GSE32539 were downloaded from Gene Expression Omnibus (GEO). Next, we conducted a series of bioinformatics analysis to explore possible hub genes in IPF and evaluated the expression of hub genes in lung cancer and their relationship with the progression of different stages of cancer.

RESULTS

A total of 1888 differentially expressed genes (DEGs) were identified, including 1105 upregulated and 783 downregulated genes. The 10 hub genes that exhibited a high degree of connectivity from the PPI network were identified. Analysis of the KEGG pathways showed that hub genes correlate with pathways such as the ECM-receptor interaction. Finally, we found that these hub genes are expressed in lung cancer and are associated with the progression of different stages of lung cancer.

CONCLUSIONS

Based on the integration of GEO microarray datasets, the present study identified DEGs and hub genes that could play an essential role in the pathogenesis of IPF and its association with the development of lung cancer in these patients, which could be considered potential diagnostic biomarkers or therapeutic targets for the disease.

Time-course transcriptome analysis of a double challenge bleomycin-induced lung fibrosis rat model uncovers ECM homoeostasis-related translationally relevant genes

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is an irreversible disorder with a poor prognosis. The incomplete understanding of IPF pathogenesis and the lack of accurate animal models is limiting the development of effective treatments. Thus, the selection of clinically relevant animal models endowed with similarities with the human disease in terms of lung anatomy, cell biology, pathways involved and genetics is essential. The bleomycin (BLM) intratracheal murine model is the most commonly used preclinical assay to evaluate new potential therapies for IPF. Here, we present the findings derived from an integrated histomorphometric and transcriptomic analysis to investigate the development of lung fibrosis in a time-course study in a BLM rat model and to evaluate its translational value in relation to IPF.

METHODS

Rats were intratracheally injected with a double dose of BLM (days 0-4) and sacrificed at days 7, 14, 21, 28 and 56. Histomorphometric analysis of lung fibrosis was performed on left lung sections. Transcriptome profiling by RNAseq was performed on the right lung lobes and results were compared with nine independent human gene-expression IPF studies.

RESULTS

The histomorphometric and transcriptomic analyses provided a detailed overview in terms of temporal gene-expression regulation during the establishment and repair of the fibrotic lesions. Moreover, the transcriptomic analysis identified three clusters of differentially coregulated genes whose expression was modulated in a time-dependent manner in response to BLM. One of these clusters, centred on extracellular matrix (ECM)-related process, was significantly correlated with histological parameters and gene sets derived from human IPF studies.

CONCLUSIONS

The model of lung fibrosis presented in this study lends itself as a valuable tool for preclinical efficacy evaluation of new potential drug candidates. The main finding was the identification of a group of persistently dysregulated genes, mostly related to ECM homoeostasis, which are shared with human IPF.

Loss of cytochrome P450 (CYP)1B1 mitigates hyperoxia response in adult mouse lung by reprogramming metabolism and translation

Oxygen supplementation is life saving for premature infants and for COVID-19 patients but can induce long-term pulmonary injury by triggering inflammation, with xenobiotic-metabolizing CYP enzymes playing a critical role. Murine studies showed that CYP1B1 enhances, while CYP1A1 and CYP1A2 protect from, hyperoxic lung injury. In this study we tested the hypothesis that Cyp1b1-null mice would revert hyperoxia-induced transcriptomic changes observed in WT mice at the transcript and pathway level. Wild type (WT) C57BL/6J and Cyp1b1-null mice aged 8-10 weeks were maintained in room air (21% O2) or exposed to hyperoxia (>95% O2) for 48h. Transcriptomic profiling was conducted using the Illumina microarray platform. Hyperoxia exposure led to robust changes in gene expression and in the same direction in WT, Cyp1a1-, Cyp1a2-, and Cyp1b1-null mice, but to different extents for each mouse genotype. At the transcriptome level, all Cyp1-null murine models reversed hyperoxia effects. Gene Set Enrichment Analysis identified 118 hyperoxia-affected pathways mitigated only in Cyp1b1-null mice, including lipid, glutamate, and amino acid metabolism. Cell cycle genes Cdkn1a and Ccnd1 were induced by hyperoxia in both WT and Cyp1b1-null mice but mitigated in Cyp1b1-null O2 compared to WT O2 mice. Hyperoxia gene signatures associated positively with bronchopulmonary dysplasia (BPD), which occurs in premature infants (with supplemental oxygen being one of the risk factors), but only in the Cyp1b1-null mice did the gene profile after hyperoxia exposure show a partial rescue of BPD-associated transcriptome. Our study suggests that CYP1B1 plays a pro-oxidant role in hyperoxia-induced lung injury.

Single-cell transcriptome sequencing-based analysis: probing the mechanisms of glycoprotein NMB regulation of epithelial cells involved in silicosis

Chronic exposure to silica can lead to silicosis, one of the most serious occupational lung diseases worldwide, for which there is a lack of effective therapeutic drugs and tools. Epithelial mesenchymal transition plays an important role in several diseases; however, data on the specific mechanisms in silicosis models are scarce. We elucidated the pathogenesis of pulmonary fibrosis via single-cell transcriptome sequencing and constructed an experimental silicosis mouse model to explore the specific molecular mechanisms affecting epithelial mesenchymal transition at the single-cell level. Notably, as silicosis progressed, glycoprotein non-metastatic melanoma protein B (GPNMB) exerted a sustained amplification effect on alveolar type II epithelial cells, inducing epithelial-to-mesenchymal transition by accelerating cell proliferation and migration and increasing mesenchymal markers, ultimately leading to persistent pulmonary pathological changes. GPNMB participates in the epithelial-mesenchymal transition in distant lung epithelial cells by releasing extracellular vesicles to accelerate silicosis. These vesicles are involved in abnormal changes in the composition of the extracellular matrix and collagen structure. Our results suggest that GPNMB is a potential target for fibrosis prevention.

Identification of potential biomarkers for idiopathic pulmonary fibrosis and validation of TDO2 as a potential therapeutic target

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease with a high mortality rate. On this basis, exploring potential therapeutic targets to meet the unmet needs of IPF patients is important.

AIM

To explore novel hub genes for IPF therapy.

METHODS

Here, we used public datasets to identify differentially expressed genes between IPF patients and healthy donors. Potential targets were considered based on multiple bioinformatics analyses, especially the correlation between hub genes and carbon monoxide diffusing capacity of carbon monoxide, forced vital capacity, and patient survival rate. The mRNA levels of the hub genes were determined through quantitative real-time polymerase chain reaction.

RESULTS

We found that TDO2 was upregulated in IPF patients and predicted poor prognosis. Surprisingly, single-cell RNA sequencing data analysis revealed significant enrichment of TDO2 in alveolar fibroblasts, indicating that TDO2 may participate in the regulation of proliferation and survival. Therefore, we verified the upregulated expression of TDO2 in an experimental mouse model of transforming growth factor-β (TGF-β)-induced pulmonary fibrosis. Furthermore, the results showed that a TDO2 inhibitor effectively suppressed TGF-β-induced fibroblast activation. These findings suggest that TDO2 may be a potential target for IPF treatment. Based on transcription factors-microRNA prediction and scRNA-seq analysis, elevated TDO2 promoted the IPF proliferation of fibroblasts and may be involved in the P53 pathway and aggravate ageing and persistent pulmonary fibrosis.

CONCLUSION

We provided new target genes prediction and proposed blocking TGF-β production as a potential treatment for IPF.

Transcriptomic and proteomic profiling of young and old mice in the bleomycin model reveals high similarity

The most common preclinical, in vivo model to study lung fibrosis is the bleomycin-induced lung fibrosis model in 2- to 3-mo-old mice. Although this model resembles key aspects of idiopathic pulmonary fibrosis (IPF), there are limitations in its predictability for the human disease. One of the main differences is the juvenile age of animals that are commonly used in experiments, resembling humans of around 20 yr. Because IPF patients are usually older than 60 yr, aging appears to play an important role in the pathogenesis of lung fibrosis. Therefore, we compared young (3 months) and old mice (21 months) 21 days after intratracheal bleomycin instillation. Analyzing lung transcriptomics (mRNAs and miRNAs) and proteomics, we found most pathways to be similarly regulated in young and old mice. However, old mice show imbalanced protein homeostasis as well as an increased inflammatory state in the fibrotic phase compared to young mice. Comparisons with published human transcriptomic data sets (GSE47460, GSE32537, and GSE24206) revealed that the gene signature of old animals correlates significantly better with IPF patients, and it also turned human healthy individuals better into "IPF patients" using an approach based on predictive disease modeling. Both young and old animals show similar molecular hallmarks of IPF in the bleomycin-induced lung fibrosis model, although old mice more closely resemble several features associated with IPF in comparison to young animals.

Machine learning-based prediction of candidate gene biomarkers correlated with immune infiltration in patients with idiopathic pulmonary fibrosis

Objective

This study aimed to identify candidate gene biomarkers associated with immune infiltration in idiopathic pulmonary fibrosis (IPF) based on machine learning algorithms.

Methods

Microarray datasets of IPF were extracted from the Gene Expression Omnibus (GEO) database to screen for differentially expressed genes (DEGs). The DEGs were subjected to enrichment analysis, and two machine learning algorithms were used to identify candidate genes associated with IPF. These genes were verified in a validation cohort from the GEO database. Receiver operating characteristic (ROC) curves were plotted to assess the predictive value of the IPF-associated genes. The cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm was used to evaluate the proportion of immune cells in IPF and normal tissues. Additionally, the correlation between the expression of IPF-associated genes and the infiltration levels of immune cells was examined.

Results

A total of 302 upregulated and 192 downregulated genes were identified. Functional annotation, pathway enrichment, Disease Ontology and gene set enrichment analyses revealed that the DEGs were related to the extracellular matrix and immune responses. COL3A1, CDH3, CEBPD, and GPIHBP1 were identified as candidate biomarkers using machine learning algorithms, and their predictive value was verified in a validation cohort. Additionally, ROC analysis revealed that the four genes had high predictive accuracy. The infiltration levels of plasma cells, M0 macrophages and resting dendritic cells were higher and those of resting natural killer (NK) cells, M1 macrophages and eosinophils were lower in the lung tissues of patients with IPF than in those of healthy individuals. The expression of the abovementioned genes was correlated with the infiltration levels of plasma cells, M0 macrophages and eosinophils.

Conclusion

COL3A1, CDH3, CEBPD, and GPIHBP1 are candidate biomarkers of IPF. Plasma cells, M0 macrophages and eosinophils may be involved in the development of IPF and may serve as immunotherapeutic targets in IPF.

Saracatinib, a Selective Src Kinase Inhibitor, Blocks Fibrotic Responses in Preclinical Models of Pulmonary Fibrosis

Rationale: Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, and often fatal disorder. Two U.S. Food and Drug Administration-approved antifibrotic drugs, nintedanib and pirfenidone, slow the rate of decline in lung function, but responses are variable and side effects are common. Objectives: Using an in silico data-driven approach, we identified a robust connection between the transcriptomic perturbations in IPF disease and those induced by saracatinib, a selective Src kinase inhibitor originally developed for oncological indications. Based on these observations, we hypothesized that saracatinib would be effective at attenuating pulmonary fibrosis. Methods: We investigated the antifibrotic efficacy of saracatinib relative to nintedanib and pirfenidone in three preclinical models: 1) in vitro in normal human lung fibroblasts; 2) in vivo in bleomycin and recombinant Ad-TGF-β (adenovirus transforming growth factor-β) murine models of pulmonary fibrosis; and 3) ex vivo in mice and human precision-cut lung slices from these two murine models as well as patients with IPF and healthy donors. Measurements and Main Results: In each model, the effectiveness of saracatinib in blocking fibrogenic responses was equal or superior to nintedanib and pirfenidone. Transcriptomic analyses of TGF-β-stimulated normal human lung fibroblasts identified specific gene sets associated with fibrosis, including epithelial-mesenchymal transition, TGF-β, and WNT signaling that was uniquely altered by saracatinib. Transcriptomic analysis of whole-lung extracts from the two animal models of pulmonary fibrosis revealed that saracatinib reverted many fibrogenic pathways, including epithelial-mesenchymal transition, immune responses, and extracellular matrix organization. Amelioration of fibrosis and inflammatory cascades in human precision-cut lung slices confirmed the potential therapeutic efficacy of saracatinib in human lung fibrosis. Conclusions: These studies identify novel Src-dependent fibrogenic pathways and support the study of the therapeutic effectiveness of saracatinib in IPF treatment.

Mitochondrial uncoupling protein-2 reprograms metabolism to induce oxidative stress and myofibroblast senescence in age-associated lung fibrosis

Mitochondrial dysfunction has been associated with age-related diseases, including idiopathic pulmonary fibrosis (IPF). We provide evidence that implicates chronic elevation of the mitochondrial anion carrier protein, uncoupling protein-2 (UCP2), in increased generation of reactive oxygen species, altered redox state and cellular bioenergetics, impaired fatty acid oxidation, and induction of myofibroblast senescence. This pro-oxidant senescence reprogramming occurs in concert with conventional actions of UCP2 as an uncoupler of oxidative phosphorylation with dissipation of the mitochondrial membrane potential. UCP2 is highly expressed in human IPF lung myofibroblasts and in aged fibroblasts. In an aging murine model of lung fibrosis, the in vivo silencing of UCP2 induces fibrosis regression. These studies indicate a pro-fibrotic function of UCP2 in chronic lung disease and support its therapeutic targeting in age-related diseases associated with impaired tissue regeneration and organ fibrosis.

COVID-19 lung disease shares driver AT2 cytopathic features with Idiopathic pulmonary fibrosis

BACKGROUND

In the aftermath of Covid-19, some patients develop a fibrotic lung disease, i.e., post-COVID-19 lung disease (PCLD), for which we currently lack insights into pathogenesis, disease models, or treatment options.

METHODS

Using an AI-guided approach, we analyzed > 1000 human lung transcriptomic datasets associated with various lung conditions using two viral pandemic signatures (ViP and sViP) and one covid lung-derived signature. Upon identifying similarities between COVID-19 and idiopathic pulmonary fibrosis (IPF), we subsequently dissected the basis for such similarity from molecular, cytopathic, and immunologic perspectives using a panel of IPF-specific gene signatures, alongside signatures of alveolar type II (AT2) cytopathies and of prognostic monocyte-driven processes that are known drivers of IPF. Transcriptome-derived findings were used to construct protein-protein interaction (PPI) network to identify the major triggers of AT2 dysfunction. Key findings were validated in hamster and human adult lung organoid (ALO) pre-clinical models of COVID-19 using immunohistochemistry and qPCR.

FINDINGS

COVID-19 resembles IPF at a fundamental level; it recapitulates the gene expression patterns (ViP and IPF signatures), cytokine storm (IL15-centric), and the AT2 cytopathic changes, e.g., injury, DNA damage, arrest in a transient, damage-induced progenitor state, and senescence-associated secretory phenotype (SASP). These immunocytopathic features were induced in pre-clinical COVID models (ALO and hamster) and reversed with effective anti-CoV-2 therapeutics in hamsters. PPI-network analyses pinpointed ER stress as one of the shared early triggers of both diseases, and IHC studies validated the same in the lungs of deceased subjects with COVID-19 and SARS-CoV-2-challenged hamster lungs. Lungs from tg-mice, in which ER stress is induced specifically in the AT2 cells, faithfully recapitulate the host immune response and alveolar cytopathic changes that are induced by SARS-CoV-2.

INTERPRETATION

Like IPF, COVID-19 may be driven by injury-induced ER stress that culminates into progenitor state arrest and SASP in AT2 cells. The ViP signatures in monocytes may be key determinants of prognosis. The insights, signatures, disease models identified here are likely to spur the development of therapies for patients with IPF and other fibrotic interstitial lung diseases.

FUNDING

This work was supported by the National Institutes for Health grants R01- GM138385 and AI155696 and funding from the Tobacco-Related disease Research Program (R01RG3780).

Biological interacting units identified in human protein networks reveal tissue-functional diversification and its impact on disease

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Biological processes are exerted by groups of physically interacting proteins.

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Proteins display variable biological roles depending on tissue-interactomic context.

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Tissue-specific protein-protein interaction networks reveal functional diversification.

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Most disease associated genes/proteins display tissue-specific phenotypes.

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Protein interaction network analysis is a valuable resource to identify disease genes.

Protein-protein interactions (PPI) play an essential role in the biological processes that occur in the cell. Therefore, the dissection of PPI networks becomes decisive to model functional coordination and predict pathological de-regulation. Cellular networks are dynamic and proteins display varying roles depending on the tissue-interactomic context. Thus, the use of centrality measures in individual proteins fall short to dissect the functional properties of the cell. For this reason, there is a need for more comprehensive, relational, and context-specific ways to analyze the multiple actions of proteins in different cells and identify specific functional assemblies within global biomolecular networks. Under this framework, we define Biological Interacting units (BioInt-U) as groups of proteins that interact physically and are enriched in a common Gene Ontology. A search strategy was applied on 33 tissue-specific (TS) PPI networks to generate BioInt libraries associated with each particular human tissue. The cross-tissue comparison showed that housekeeping assemblies incorporate different proteins and exhibit distinct network properties depending on the tissue. Furthermore, disease genes (DGs) of tissue-associated pathologies preferentially accumulate in units in the expected tissues, which in turn were more central in the TS networks. Overall, the study reveals a tissue-specific functional diversification based on the identification of specific protein units and suggests vulnerabilities specific of each tissue network, which can be applied to refine protein-disease association methods.

COVID-19 lung disease shares driver AT2 cytopathic features with Idiopathic pulmonary fibrosis

Background

In the aftermath of Covid-19, some patients develop a fibrotic lung disease, i.e., p ost- C OVID-19 l ung d isease (PCLD), for which we currently lack insights into pathogenesis, disease models, or treatment options.

Method

Using an AI-guided approach, we analyzed > 1000 human lung transcriptomic datasets associated with various lung conditions using two viral pandemic signatures (ViP and sViP) and one covid lung-derived signature. Upon identifying similarities between COVID-19 and idiopathic pulmonary fibrosis (IPF), we subsequently dissected the basis for such similarity from molecular, cytopathic, and immunologic perspectives using a panel of IPF-specific gene signatures, alongside signatures of alveolar type II (AT2) cytopathies and of prognostic monocyte-driven processes that are known drivers of IPF. Transcriptome-derived findings were used to construct protein-protein interaction (PPI) network to identify the major triggers of AT2 dysfunction. Key findings were validated in hamster and human adult lung organoid (ALO) pre-clinical models of COVID-19 using immunohistochemistry and qPCR.

Findings

COVID-19 resembles IPF at a fundamental level; it recapitulates the gene expression patterns (ViP and IPF signatures), cytokine storm (IL15-centric), and the AT2 cytopathic changes, e.g., injury, DNA damage, arrest in a transient, damage-induced progenitor state, and senescence-associated secretory phenotype (SASP). These immunocytopathic features were induced in pre-clinical COVID models (ALO and hamster) and reversed with effective anti-CoV-2 therapeutics in hamsters. PPI-network analyses pinpointed ER stress as one of the shared early triggers of both diseases, and IHC studies validated the same in the lungs of deceased subjects with COVID-19 and SARS-CoV-2-challenged hamster lungs. Lungs from tg - mice, in which ER stress is induced specifically in the AT2 cells, faithfully recapitulate the host immune response and alveolar cytopathic changes that are induced by SARS-CoV-2.

Interpretation

Like IPF, COVID-19 may be driven by injury-induced ER stress that culminates into progenitor state arrest and SASP in AT2 cells. The ViP signatures in monocytes may be key determinants of prognosis. The insights, signatures, disease models identified here are likely to spur the development of therapies for patients with IPF and other fibrotic interstitial lung diseases.

Funding

This work was supported by the National Institutes for Health grants R01-GM138385 and AI155696 and funding from the Tobacco-Related disease Research Program (R01RG3780).

One Sentence Summary

Severe COVID-19 triggers cellular processes seen in fibrosing Interstitial Lung Disease.

RESEARCH IN CONTEXT

Evidence before this study: In its aftermath, the COVID-19 pandemic has left many survivors, almost a third of those who recovered, with a mysterious long-haul form of the disease which culminates in a fibrotic form of interstitial lung disease (post-COVID-19 ILD). Post-COVID-19 ILD remains a largely unknown entity. Currently, we lack insights into the core cytopathic features that drive this condition.Added value of this study: Using an AI-guided approach, which involves the use of sets of gene signatures, protein-protein network analysis, and a hamster model of COVID-19, we have revealed here that COVID-19 -lung fibrosis resembles IPF, the most common form of ILD, at a fundamental levelâ€"showing similar gene expression patterns in the lungs and blood, and dysfunctional AT2 processes (ER stress, telomere instability, progenitor cell arrest, and senescence). These findings are insightful because AT2 cells are known to contain an elegant quality control network to respond to intrinsic or extrinsic stress; a failure of such quality control results in diverse cellular phenotypes, of which ER stress appears to be a point of convergence, which appears to be sufficient to drive downstream fibrotic remodeling in the lung.Implications of all the available evidence: Because unbiased computational methods identified the shared fundamental aspects of gene expression and cellular processes between COVID-19 and IPF, the impact of our findings is likely to go beyond COVID-19 or any viral pandemic. The insights, tools (disease models, gene signatures, and biomarkers), and mechanisms identified here are likely to spur the development of therapies for patients with IPF and, other fibrotic interstitial lung diseases, all of whom have limited or no treatment options. To dissect the validated prognostic biomarkers to assess and track the risk of pulmonary fibrosis and develop therapeutics to halt fibrogenic progression.

Consensus Gene Co-Expression Network Analysis Identifies Novel Genes Associated with Severity of Fibrotic Lung Disease

Idiopathic pulmonary fibrosis (IPF) is a severe fibrotic lung disease characterized by irreversible scarring of the lung parenchyma leading to dyspnea, progressive decline in lung function, and respiratory failure. We analyzed lung transcriptomic data from independent IPF cohorts using weighted gene co-expression network analysis (WGCNA) to identify gene modules based on their preservation status in these cohorts. The consensus gene modules were characterized by leveraging existing clinical and molecular data such as lung function, biological processes, pathways, and lung cell types. From a total of 32 consensus gene modules identified, two modules were found to be significantly correlated with the disease, lung function, and preserved in other IPF datasets. The upregulated gene module was enriched for extracellular matrix, collagen metabolic process, and BMP signaling while the downregulated module consisted of genes associated with tube morphogenesis, blood vessel development, and cell migration. Using a combination of connectivity-based and trait-based significance measures, we identified and prioritized 103 "hub" genes (including 25 secretory candidate biomarkers) by their similarity to known IPF genetic markers. Our validation studies demonstrate the dysregulated expression of CRABP2, a retinol-binding protein, in multiple lung cells of IPF, and its correlation with the decline in lung function.

Asthma and Post-Asthmatic Fibrosis: A Search for New Promising Molecular Markers of Transition from Acute Inflammation to Pulmonary Fibrosis

Asthma is a heterogeneous pulmonary disorder, the progression and chronization of which leads to airway remodeling and fibrogenesis. To understand the molecular mechanisms of pulmonary fibrosis development, key genes forming the asthma-specific regulome and involved in lung fibrosis formation were revealed using a comprehensive bioinformatics analysis. The bioinformatics data were validated using a murine model of ovalbumin (OVA)-induced asthma and post-asthmatic fibrosis. The performed analysis revealed a range of well-known pro-fibrotic markers (Cat, Ccl2, Ccl4, Ccr2, Col1a1, Cxcl12, Igf1, Muc5ac/Muc5b, Spp1, Timp1) and a set of novel genes (C3, C3ar1, Col4a1, Col4a2, Cyp2e1, Fn1, Thbs1, Tyrobp) mediating fibrotic changes in lungs already at the stage of acute/subacute asthma-driven inflammation. The validation of genes related to non-allergic bleomycin-induced pulmonary fibrosis on asthmatic/fibrotic lungs allowed us to identify new universal genes (Col4a1 and Col4a2) associated with the development of lung fibrosis regardless of its etiology. The similarities revealed in the expression profiles of nodal fibrotic genes between asthma-driven fibrosis in mice and nascent idiopathic pulmonary fibrosis in humans suggest a tight association of identified genes with the early stages of airway remodeling and can be considered as promising predictors and early markers of pulmonary fibrosis.

The MIR100HG/miR-29a-3p/Tab1 axis modulates TGF-β1-induced fibrotic changes in type II alveolar epithelial cells BLM-caused lung fibrogenesis in mice

Transforming growth factor (TGF)-β1-induced fibrotic changes in alveolar epithelium is a critical event in pulmonary fibrosis. Herein, we recognized that lncRNA mir-100-let-7a-2-mir-125b-1 cluster host gene (MIR100HG) was abnormally upregulated within human idiopathic pulmonary fibrosis (IPF) lung tissue, bleomycin (BLM)-caused pulmonary fibrotic model mice and TGF-β1-stimulated mice type II alveolar epithelial cells. In vivo, MIR100HG knockdown attenuated BLM-caused lung fibrogenesis in mice; in vitro, MIR100HG knockdown attenuated TGF-β1-induced fibrotic changes in mice type II alveolar epithelial cells. Through direct binding, MIR100HG knockdown upregulated microRNA-29a-3p (miR-29a-3p) expression; through serving as competing endogenous RNA for miR-29a-3p, MIR100HG knockdown downregulated TGF-beta activated kinase 1/MAP3K7 binding protein 1 (Tab1) expression. Finally, under TGF-β1 stimulation, Tab1 knockdown attenuated TGF-β1-induced fibrotic changes and partially attenuated the effects of miR-29a-3p inhibition. In conclusion, we demonstrated the aberrant upregulation of lncRNA MIR100HG in BLM-caused lung fibrogenesis and TGF-β1-stimulated MLE 12 cells. The MIR100HG/miR-29a-3p/Tab1 axis could modulate TGF-β1-induced fibrotic changes in type II alveolar epithelial cells and, thus, might be promising targets for pulmonary fibrosis therapy.

Identification and Validation of Aging-Related Genes in Idiopathic Pulmonary Fibrosis

Aging plays a significant role in the occurrence and development of idiopathic pulmonary fibrosis (IPF). In this study, we aimed to identify and verify potential aging-associated genes involved in IPF using bioinformatic analysis. The mRNA expression profile dataset GSE150910 available in the Gene Expression Omnibus (GEO) database and R software were used to identify the differentially expressed aging-related genes involved in IPF. Hub gene expression was validated by other GEO datasets. Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on differentially expressed aging-related genes. Subsequently, aging-related genes were further screened using three techniques (least absolute shrinkage and selection operator (LASSO) regression, support vector machine, and random forest), and the receiver operating characteristic curves were plotted based on screening results. Finally, real-time quantitative polymerase chain reaction (qRT-PCR) was performed to verify the RNA expression of the six differentially expressed aging-related genes using the blood samples of patients with IPF and healthy individuals. Sixteen differentially expressed aging-related genes were detected, of which the expression of 12 were upregulated and four were downregulated. GO and KEGG enrichment analyses indicated the presence of several enriched terms related to senescence and apoptotic mitochondrial changes. Further screening by LASSO regression, support vector machine, and random forest identified six genes (IGF1, RET, IGFBP2, CDKN2A, JUN, and TFAP2A) that could serve as potential diagnostic biomarkers for IPF. Furthermore, qRT-PCR analysis indicated that among the above-mentioned six aging-related genes, only the expression levels of IGF1, RET, and IGFBP2 in patients with IPF and healthy individuals were consistent with the results of bioinformatic analysis. In conclusion, bioinformatics analysis identified 16 potential aging-related genes associated with IPF, and clinical sample validation suggested that among these, IGF1, RET, and IGFBP2 might play a role in the incidence and prognosis of IPF. Our findings may help understand the pathogenesis of IPF.

Identification of hub genes associated with COVID-19 and idiopathic pulmonary fibrosis by integrated bioinformatics analysis

INTRODUCTION

The coronavirus disease 2019 (COVID-19), emerged in late 2019, was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The risk factors for idiopathic pulmonary fibrosis (IPF) and COVID-19 are reported to be common. This study aimed to determine the potential role of differentially expressed genes (DEGs) common in IPF and COVID-19.

MATERIALS AND METHODS

Based on GEO database, we obtained DEGs from one SARS-CoV-2 dataset and five IPF datasets. A series of enrichment analysis were performed to identify the function of upregulated and downregulated DEGs, respectively. Two plugins in Cytoscape, Cytohubba and MCODE, were utilized to identify hub genes after a protein-protein interaction (PPI) network. Finally, candidate drugs were predicted to target the upregulated DEGs.

RESULTS

A total of 188 DEGs were found between COVID-19 and IPF, out of which 117 were upregulated and 71 were downregulated. The upregulated DEGs were involved in cytokine function, while downregulated DEGs were associated with extracellular matrix disassembly. Twenty-two hub genes were upregulated in COVID-19 and IPF, for which 155 candidate drugs were predicted (adj.P.value < 0.01).

CONCLUSION

Identifying the hub genes aberrantly regulated in both COVID-19 and IPF may enable development of molecules, encoded by those genes, as therapeutic targets for preventing IPF progression and SARS-CoV-2 infections.

Identification of Genetic Signature Associated With Aging in Pulmonary Fibrosis

Background: Aging is a strong risk factor and an independent prognostic factor in idiopathic pulmonary fibrosis (IPF). In this study, we aimed to conduct a comprehensive analysis based on gene expression profiles for the role of aging in pulmonary fibrosis.

Method: Four datasets (GSE21411, GSE24206, GSE47460, and GSE101286) for patients with clinical IPF and one dataset for bleomycin (BLM)-induced pulmonary fibrosis (BIPF) mouse model (GSE123293) were obtained from Gene Expression Omnibus (GEO). According to different age ranges, both patients with IPF and BIPF mice were divided into young and aged groups. The differently expressed genes (DEGs) were systemically analyzed using Gene Ontology (GO) functional, Kyoto Encyclopedia of Genes and Genomes (KEGG), and hub genes analysis. Finally, we verified the role of age and core genes associated with age in vivo.

Results:Via the expression profile comparisons of aged and young patients with IPF, we identified 108 aging-associated DEGs, with 21 upregulated and 87 downregulated. The DEGs were associated with “response to glucocorticoid,” “response to corticosteroid,” and “rhythmic process” in GO biological process (BP). For KEGG analysis, the top three significantly enriched KEGG pathways of the DEGs included “IL-17 signaling pathway,” “Mineral absorption,” and “HIF-1-signaling pathway.” Through the comparisons of aged and young BIPF mice, a total number of 778 aging-associated DEGs were identified, with 453 genes increased and 325 genes decreased. For GO and KEGG analysis, the DEGs were enriched in extracellular matrix (ECM) and collagen metabolism. The common DEGs of patients with IPF and BIPF mice were enriched in the BP category, including “induction of bacterial agglutination,” “hyaluronan biosynthetic process,” and “positive regulation of heterotypic cell-cell adhesion.” We confirmed that aged BIPF mice developed more serious pulmonary fibrosis. Finally, the four aging-associated core genes (Slc2a3, Fga, Hp, and Thbs1) were verified in vivo.

Conclusion: This study provides new insights into the impact of aging on pulmonary fibrosis. We also identified four aging-associated core genes (Slc2a3, Fga, Hp, and Thbs1) related to the development of pulmonary fibrosis.

A Markov random field model for network-based differential expression analysis of single-cell RNA-seq data

BACKGROUND

Recent development of single cell sequencing technologies has made it possible to identify genes with different expression (DE) levels at the cell type level between different groups of samples. In this article, we propose to borrow information through known biological networks to increase statistical power to identify differentially expressed genes (DEGs).

RESULTS

We develop MRFscRNAseq, which is based on a Markov random field (MRF) model to appropriately accommodate gene network information as well as dependencies among cell types to identify cell-type specific DEGs. We implement an Expectation-Maximization (EM) algorithm with mean field-like approximation to estimate model parameters and a Gibbs sampler to infer DE status. Simulation study shows that our method has better power to detect cell-type specific DEGs than conventional methods while appropriately controlling type I error rate. The usefulness of our method is demonstrated through its application to study the pathogenesis and biological processes of idiopathic pulmonary fibrosis (IPF) using a single-cell RNA-sequencing (scRNA-seq) data set, which contains 18,150 protein-coding genes across 38 cell types on lung tissues from 32 IPF patients and 28 normal controls.

CONCLUSIONS

The proposed MRF model is implemented in the R package MRFscRNAseq available on GitHub. By utilizing gene-gene and cell-cell networks, our method increases statistical power to detect differentially expressed genes from scRNA-seq data.

Ferroptosis-Related Genes in Bronchoalveolar Lavage Fluid Serves as Prognostic Biomarkers for Idiopathic Pulmonary Fibrosis

Background: Idiopathic pulmonary fibrosis (IPF) is a chronic progressive disease with unknown etiology and unfavorable prognosis. Ferroptosis is a form of regulated cell death with an iron-dependent way that is involved in the development of various diseases. Whereas the prognostic value of ferroptosis-related genes (FRGs) in IPF remains uncertain and needs to be further elucidated.

Methods: The FerrDb database and the previous studies were screened to explore the FRGs. The data of patients with IPF were obtained from the GSE70866 dataset. Wilcoxon's test and univariate Cox regression analysis were applied to identify the FRGs that are differentially expressed between normal and patients with IPF and associated with prognosis. Next, a multigene signature was constructed by the least absolute shrinkage and selection operator (LASSO)-penalized Cox model in the training cohort and evaluated by using calibration and receiver operating characteristic (ROC) curves. Then, 30% of the dataset samples were randomly selected for internal validation. Finally, the potential function and pathways that might be affected by the risk score-related differently expressed genes (DEGs) were further explored.

Results: A total of 183 FRGs were identified by the FerrDb database and the previous studies, and 19 of them were differentially expressed in bronchoalveolar lavage fluid (BALF) between IPF and healthy controls and associated with prognosis (p < 0.05). There were five FRGs (aconitase 1 [ACO1], neuroblastoma RAS viral (v-ras) oncogene homolog [NRAS], Ectonucleotide pyrophosphatase/phosphodiesterase 2 [ENPP2], Mucin 1 [MUC1], and ZFP36 ring finger protein [ZFP36]) identified as risk signatures and stratified patients with IPF into the two risk groups. The overall survival rate in patients with high risk was significantly lower than that in patients with low risk (p < 0.001). The calibration and ROC curve analysis confirmed the predictive capacity of this signature, and the results were further verified in the validation group. Risk score-related DEGs were found enriched in ECM-receptor interaction and focal adhesion pathways.

Conclusion: The five FRGs in BALF can be used for prognostic prediction in IPF, which may contribute to improving the management strategies of IPF.

Inhibition of the Arp2/3 complex represses human lung myofibroblast differentiation and attenuates bleomycin-induced pulmonary fibrosis

BACKGROUND AND PURPOSE

The Arp2/3 multiprotein complex regulates branched polymerisation of the actin cytoskeleton and may contribute to collagen synthesis and fibrogenesis in the lung.

EXPERIMENTAL APPROACH

Expression of Arp2/3 components was assessed in human lung fibroblasts and in the bleomycin-induced pulmonary fibrosis model in mice. The Arp2/3 complex was repressed with the allosteric inhibitor CK666 and with interfering RNAs targeting the ARP2, ARP3 and ARPC2 subunits (siARP2, siARP3 and siARPC2) in CCD-16Lu human lung fibroblasts in vitro. Mice received daily intraperitoneal injections of CK666 from the 7th to the 14th day after tracheal bleomycin instillation.

KEY RESULTS

Expression of Arp2/3 complex subunits mRNAs was increased in fibroblasts treated with TGF-β1 and in the lungs of bleomycin-treated mice compared with controls. In vitro, CK666 and siARPC2 inhibited cell growth and TGF-β1-induced α-smooth muscle actin (ACTA2) and collagen-1 (COL1) expression. CK666 also decreased ACTA2 and COL1 expression in unstimulated cells. CK666 reduced Akt phosphorylation and repressed phospho-GSK3β, β-catenin and MRTF-A levels in unstimulated fibroblasts. In vivo, CK666 reduced levels of both procollagen-1 and insoluble collagen in bleomycin-treated mice.

CONCLUSION AND IMPLICATIONS

Expression of the Arp2/3 complex was increased in profibrotic environments in vitro and in vivo. Inhibition of the Arp2/3 complex repressed ACTA2 and COL1 expression and repressed an Akt/phospho-GSK3β/β-catenin/MRTF-A pathway in lung fibroblasts. CK666 exerted antifibrotic properties in the lung in vivo. Inhibition of the Arp2/3 complex could represent an interesting new therapy for idiopathic pulmonary fibrosis and other fibrotic interstitial lung diseases.

Transcriptomic and Epigenetic Profiling of Fibroblasts in Idiopathic Pulmonary Fibrosis (IPF)

Idiopathic pulmonary fibrosis (IPF), a devastating, fibro-proliferative chronic lung disorder, is associated with expansion of fibroblasts/myofibroblasts, which leads to excessive production and deposition of extracellular matrix (ECM). IPF is typically clinically identified as end-stage lung disease, after fibrotic processes are well-established and advanced. Fibroblasts have been shown to be critically important in the development and progression of IPF. We hypothesize that differential chromatin access can drive genetic differences in IPF fibroblasts relative to healthy fibroblasts. To this end, we performed Assay of Transposase-Accessible Chromatin (ATAC)-sequencing to identify differentially accessible regions within the genomes of fibroblasts from healthy and IPF lungs. Multiple motifs were identified to be enriched in IPF fibroblasts compared to healthy fibroblasts, including binding motifs for TWIST1 and FOXA1. RNA-sequencing identified 93 genes that could be annotated to differentially accessible regions. Pathway analysis of the annotated genes identified cellular adhesion, cytoskeletal anchoring, and cell differentiation as important biological processes. In addition, single nucleotide polymorphisms (SNPs) analysis showed that linkage disequilibrium (LD) blocks of IPF risk SNPs with IPF accessible regions that have been identified to be located in genes which are important in IPF, including MUC5B, TERT and TOLLIP. Validation studies in isolated lung tissue confirmed increased expression for TWIST1 and FOXA1 in addition to revealing SHANK2 and CSPR2 as novel targets. Thus, modulation of differential chromatin access may be an important mechanism in the pathogenesis of lung fibrosis.

Fibroblast growth factor receptor 3 activates a network of profibrotic signaling pathways to promote fibrosis in systemic sclerosis

Aberrant activation of fibroblasts with progressive deposition of extracellular matrix is a key feature of systemic sclerosis (SSc), a prototypical idiopathic fibrotic disease. Here, we demonstrate that the profibrotic cytokine transforming growth factor β selectively up-regulates fibroblast growth factor receptor 3 (FGFR3) and its ligand FGF9 to promote fibroblast activation and tissue fibrosis, leading to a prominent FGFR3 signature in the SSc skin. Transcriptome profiling, in silico analysis and functional experiments revealed that FGFR3 induces multiple profibrotic pathways including endothelin, interleukin-4, and connective tissue growth factor signaling mediated by transcription factor CREB (cAMP response element-binding protein). Inhibition of FGFR3 signaling by fibroblast-specific knockout of FGFR3 or FGF9 or pharmacological inhibition of FGFR3 blocked fibroblast activation and attenuated experimental skin fibrosis in mice. These findings characterize FGFR3 as an upstream regulator of a network of profibrotic mediators in SSc and as a potential target for the treatment of fibrosis.

LncRNA CTD-2528L19.6 prevents the progression of IPF by alleviating fibroblast activation

Long non-coding RNAs (lncRNAs) have emerged as critical factors for regulating multiple biological processes during organ fibrosis. However, the mechanism of lncRNAs in idiopathic pulmonary fibrosis (IPF) remains incompletely understood. In the present study, two sets of lncRNAs were defined: IPF pathogenic lncRNAs and IPF progression lncRNAs. IPF pathogenic and progression lncRNAs-mRNAs co-expression networks were constructed to identify essential lncRNAs. Network analysis revealed a key lncRNA CTD-2528L19.6, which was up-regulated in early-stage IPF compared to normal lung tissue, and subsequently down-regulated during advanced-stage IPF. CTD-2528L19.6 was indicated to regulate fibroblast activation in IPF progression by mediating the expression of fibrosis related genes LRRC8C, DDIT4, THBS1, S100A8 and TLR7 et al. Further studies showed that silencing of CTD-2528L19.6 increases the expression of Fn1 and Collagen I both at mRNA and protein levels, promoted the transition of fibroblasts into myofibroblasts and accelerated the migration and proliferation of MRC-5 cells. In contrast, CTD-2528L19.6 overexpression alleviated fibroblast activation in MRC-5 cells induced by TGF-β1. LncRNA CTD-2528L19.6 inhibited fibroblast activation through regulating the expression of LRRC8C in vitro assays. Our results suggest that CTD-2528L19.6 may prevent the progression of IPF from early-stage and alleviate fibroblast activation during the advanced-stage of IPF. Thus, exploring the regulatory effect of lncRNA CTD-2528L19.6 may provide new sights for the prevention and treatment of IPF.

Association between renin-angiotensin system and chronic lung allograft dysfunction

Chronic lung allograft dysfunction (CLAD) is the major cause of death after lung transplantation. Angiotensin II (AngII), the main effector of the renin-angiotensin (RA) system, elicits fibrosis in both kidney and lung. We identified 6 AngII-regulated proteins (RHOB, BST1, LYPA1, GLNA, TSP1, LAMB1) increased in urine of patients with kidney allograft fibrosis. We hypothesized that RA system is active in CLAD and that AngII-regulated proteins are increased in bronchoalveolar lavage fluid (BAL) of CLAD patients.We performed immunostaining of AngII receptors (AGTR1 and AGTR2) and TSP1/GLNA in 10 CLAD lungs and 5 controls. Using mass spectrometry, we quantified peptides corresponding to AngII-regulated proteins in BAL of 40 lung transplant recipients (CLAD, stable and acute lung allograft dysfunction (ALAD)). Machine learning algorithms were developed to predict CLAD based on BAL peptide concentrations.Immunostaining demonstrated significantly more AGTR1+ cells in CLAD versus control lungs (p=0.02). TSP1 and GLNA immunostaining positively correlated with the degree of lung fibrosis (R²=0.42 and 0.57, respectively). In BAL, we noted a trend toward higher concentrations of AngII-regulated peptides in patients with CLAD at the time of bronchoscopy, and significantly higher concentrations of BST1, GLNA and RHOB peptides in patients that developed CLAD at follow-up (p<0.05). Support vector machine classifier discriminated CLAD from stable and ALAD patients at the time of bronchoscopy with AUC 0.86, and accurately predicted subsequent CLAD development (AUC 0.97).Proteins involved in the RA system are increased in CLAD lung and BAL. AngII-regulated peptides measured in BAL may accurately identify patients with CLAD and predict subsequent CLAD development.

Catalpol Protects Against Pulmonary Fibrosis Through Inhibiting TGF-β1/Smad3 and Wnt/β-Catenin Signaling Pathways

Idiopathic pulmonary fibrosis (IPF) is a fatal lung disease characterized by fibroblast proliferation and extracellular matrix remodeling; however, the molecular mechanisms underlying its occurrence and development are not yet fully understood. Despite it having a variety of beneficial pharmacological activities, the effects of catalpol (CAT), which is extracted from Rehmannia glutinosa, in IPF are not known. In this study, the differentially expressed genes, proteins, and pathways of IPF in the Gene Expression Omnibus database were analyzed, and CAT was molecularly docked with the corresponding key proteins to screen its pharmacological targets, which were then verified using an animal model. The results show that collagen metabolism imbalance, inflammatory response, and epithelial-mesenchymal transition (EMT) are the core processes in IPF, and the TGF-β1/Smad3 and Wnt/β-catenin pathways are the key signaling pathways for the development of pulmonary fibrosis. Our results also suggest that CAT binds to TGF-βR1, Smad3, Wnt3a, and GSK-3β through hydrogen bonds, van der Waals bonds, and other interactions to downregulate the expression and phosphorylation of Smad3, Wnt3a, GSK-3β, and β-catenin, inhibit the expression of cytokines, and reduce the degree of oxidative stress in lung tissue. Furthermore, CAT can inhibit the EMT process and collagen remodeling by downregulating fibrotic biomarkers and promoting the expression of epithelial cadherin. This study elucidates several key processes and signaling pathways involved in the development of IPF, and suggests the potential value of CAT in the treatment of IPF.

Identification of common signatures in idiopathic pulmonary fibrosis and lung cancer using gene expression modeling

Background

Idiopathic pulmonary fibrosis (IPF) is associated with an increased risk for lung cancer, but the underlying mechanisms driving malignant transformation remain largely unknown. This study aimed to identify differentially expressed genes (DEGs) distinguishing IPF and lung cancer from healthy individuals and common genes driving the transformation from healthy to IPF and lung cancer.

Methods

The gene expression data for IPF and non-small cell lung cancer (NSCLC) were retrieved from the Gene Expression Omnibus (GEO) database. The DEG signatures were identified via unsupervised two-way clustering (TWC) analysis, supervised support vector machine analysis, dimensional reduction, and mutual exclusivity analysis. Gene enrichment and pathway analyses were performed to identify common signaling pathways. The most significant signature genes in common among IPF and lung cancer were further verified by immunohistochemistry.

Results

The gene expression data from GSE24206 and GSE18842 were merged into a super array dataset comprising 86 patients with lung disorders (17 IPF and 46 NSCLC) and 51 healthy controls and measuring 23,494 unique genes. Seventy-nine signature DEGs were found among IPF and NSCLC. The peroxisome proliferator-activated receptor (PPAR) signaling pathway was the most enriched pathway associated with lung disorders, and matrix metalloproteinase-1 (MMP-1) in this pathway was mutually exclusive with several genes in IPF and NSCLC. Subsequent immunohistochemical analysis verified enhanced MMP1 expression in NSCLC associated with IPF.

Conclusions

For the first time, we defined common signature genes for IPF and NSCLC. The mutually exclusive sets of genes were potential drivers for IPF and NSCLC.

Identification of key modules and hub genes associated with lung function in idiopathic pulmonary fibrosis

Background

Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive interstitial lung disease, characterized by a decline in lung function. To date, the pathophysiologic mechanisms associated with lung dysfunction remain unclear, and no effective therapy has been identified to improve lung function.

Methods

In the present study, we used weighted gene co-expression network analysis (WGCNA) to identify key modules and hub genes associated with lung function in IPF. Three datasets, containing clinical information, were downloaded from Gene Expression Omnibus. WGCNA was performed on the GSE32537 dataset. Differentially expressed gene s (DEGs) between IPF patients and healthy controls were also identified to filter hub genes. The relationship between hub genes and lung function was then validated using the GSE47460 and GSE24206 datasets.

Results

The red module, containing 267 genes, was positively correlated with the St. George’s Respiratory Questionnaire score (r = 0.37, p < 0.001) and negatively correlated with the percent predicted forced vital capacity (FVC% predicted) (r =  − 0.46, p < 0.001) and the percent predicted diffusion capacity of the lung for carbon monoxide (Dlco% predicted) (r =  − 0.42, p < 0.001). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis suggested that the genes in the red module were primarily involved in inflammation and immune pathways. Based on Module Membership and Gene Significance, 32 candidate hub genes were selected in the red module to construct a protein-protein interaction network . Based on the identified DEGs and the degree of connectivity in the network, we identified three hub genes, including interleukin 6 (IL6), suppressor of cytokine signaling-3 (SOCS3), and serpin family E member 1 (SERPINE1). In the GSE47460 dataset, Spearman correlation coefficients between Dlco% predicted and expression levels of IL6, SERPINE1, SOCS3 were –0.32, –0.41, and –0.46, respectively. Spearman correlation coefficients between FVC% predicted and expression levels of IL6, SERPINE1, SOCS3 were –0.29, –0.33, and –0.27, respectively. In the GSE24206 dataset, all three hub genes were upregulated in patients with advanced IPF.

Conclusion

We identified three hub genes that negatively correlated with the lung function of IPF patients. Our results provide insights into the pathogenesis underlying the progressive disruption of lung function, and the identified hub genes may serve as biomarkers and potential therapeutictargets for the treatment of IPF patients.

Identification of transcriptomic markers for developing idiopathic pulmonary fibrosis: an integrative analysis of gene expression profiles

Idiopathic pulmonary fibrosis (IPF) remains a lethal disease with unknown etiology and unmet medical need. The aim of this study was to perform an integrative analysis of multiple public microarray datasets to investigate gene expression patterns between IPF patients and healthy controls. Moreover, functional interpretation of differentially expressed genes (DEGs) was performed to assess the molecular mechanisms underlying IPF progression. DEGs between IPF and normal lung tissues were picked out by GEO2R tool and Venn diagram software. Database for Annotation, Visualization and Integrated Discovery (DAVID) was applied to analyze gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway. Protein-protein interaction (PPI) of these DEGs was visualized by Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING). 5520 DEGs were identified in IPF based on six profile datasets, including 3714 up-regulated genes and 1806 down-regulated genes. Using Venn software, a total of 367 commonly altered DEGs were revealed, including 259 up-regulated genes mostly enriched in collagen catabolic process, heparin binding, and the extracellular region. For pathway analysis, up-regulated DEGs were mainly enriched in ECM-receptor interaction, protein digestion and absorption, and focal adhesion. Finally, 24 DEGs with degrees ≥10 were screened as hub genes from the PPI network, which were enriched in protein digestion and absorption, ECM-receptor interaction, focal adhesion, PI3K-Akt signaling pathway, amoebiasis, and platelet activation. The present integrative study identified DEGs and hub genes that may be diagnostic biomarkers or therapeutic targets, and provide novel insights into the pathogenesis of IPF.

A new computational drug repurposing method using established disease-drug pair knowledge

MOTIVATION

Drug repurposing is a potential alternative to the classical drug discovery pipeline. Repurposing involves finding novel indications for already approved drugs. In this work, we present a novel machine learning-based method for drug repurposing. This method explores the anti-similarity between drugs and a disease to uncover new uses for the drugs. More specifically, our proposed method takes into account three sources of information: (i) large-scale gene expression profiles corresponding to human cell lines treated with small molecules, (ii) gene expression profile of a human disease and (iii) the known relationship between Food and Drug Administration (FDA)-approved drugs and diseases. Using these data, our proposed method learns a similarity metric through a supervised machine learning-based algorithm such that a disease and its associated FDA-approved drugs have smaller distance than the other disease-drug pairs.

RESULTS

We validated our framework by showing that the proposed method incorporating distance metric learning technique can retrieve FDA-approved drugs for their approved indications. Once validated, we used our approach to identify a few strong candidates for repurposing.

AVAILABILITY AND IMPLEMENTATION

The R scripts are available on demand from the authors.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Integrated Analysis of a Gene Correlation Network Identifies Critical Regulation of Fibrosis by lncRNAs and TFs in Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF), the most frequent form of irreversible interstitial pneumonia with unknown etiology, is characterized by massive remodeling of lung architecture and followed by progressive loss of lung function. However, the key regulatory genes and the specific signaling pathways involved in the onset and progression of IPF still remain unclear. The present study is aimed at investigating the key role of long noncoding RNAs (lncRNAs) and transcription factors (TFs) involved in the pathogenesis of IPF through the integrated analysis of three gene expression profiles from the GEO dataset (GSE2052, GSE44723, and GSE24206). A total of 8483 differentially expressed genes (DEGs) including 988 upregulated and 7495 downregulated genes were filtered. Subsequently, following the intersection of these DEGs, 29 overlapping genes were identified and further analyzed using a bioinformatics approach. Furthermore, the protein-protein interaction (PPI) network was used to obtain 18 modules of related genes. The hub genes were identified through hypergeometric testing, which were closely associated with ubiquitin-mediated proteolysis, the spliceosome, and the cell cycle. The significant difference was observed in the expression of these key genes, such as lncRNA MALAT1, E2F1, and YBX1, in the peripheral blood of IPF patients when compared with those normal control subjects by real-time polymerase chain reaction (RT-PCR) analysis. This study indicated that lncRNA MALAT1, E2F1, and YBX1 may be key regulators for the pathogenesis of IPF.

Transcription factor YY1 inhibits the expression of THY1 to promote interstitial pulmonary fibrosis by activating the HSF1/miR-214 axis

Interstitial pulmonary fibrosis (IPF) is a progressive disease of diverse etiology manifesting with proliferation of lung fibroblasts and accumulation of extracellular matrix deposition in pulmonary interstitium. Recent studies show aberrant expression of mRNAs and microRNAs (miRNAs) in human embryonic pulmonary fibroblasts (HEPFs). In this study, we investigated effects of the YY1/HSF1/miR-214/THY1 axis on the functions of HEPFs and IPF. Loss- and gain-of-function tests were conducted to identify roles of YY1, HSF1, miR-214, and THY1 in IPF. As determined by RT-qPCR or western blot assay, silencing YY1 down-regulated HSF1 expression and attenuated the expression of pro-proliferative and fibrosis markers in HEPFs. Meanwhile, viability of HEPFs was impeded by YY1 knockdown. The binding relationship between miR-214 and THY1 was verified using dual-luciferase reporter assay. In HEPFs, down-regulation of HSF1 reduced miR-214 expression to repress proliferation and fibrogenic transformation of HEPFs, while inhibition of miR-214 expression could restrain the fibrogenic transformation property of HEPFs by up-regulating THY1. Subsequently, IPF model in mice was induced by bleomycin treatment. These animal experiments validated the protective effects of YY1 knockdown against IPF-induced lung pathological manifestations, which could be reversed by THY1 knockdown. Our study demonstrates the important involvement of YY1/HSF1/miR-214/THY1 axis in the development of IPF.

HYAL1 Is Downregulated in Idiopathic Pulmonary Fibrosis and Inhibits HFL-1 Fibroblast Proliferation When Upregulated

Background

Idiopathic pulmonary fibrosis (IPF), the most common interstitial lung disease, arises from transforming growth factor beta 1- (TGFβ1-) induced aberrant fibroproliferation in response to epithelial injury. The TGFβ1-) induced aberrant fibroproliferation in response to epithelial injury. The TGF

Methods

We first performed microarray data mining of previously published gene expression datasets to identify key gene signatures in IPF lung tissues. HYAL1 expression levels in IPF and normal lung tissues were then characterized using immunohistochemistry followed by real-time quantitative reverse transcription-PCR (qRT-PCR) and western blot analysis on isolated fibroblasts from fresh lung tissues of IPF and healthy donors. A human fetal lung fibroblast HFL-1 cell line, which was used in place of primary lung fibroblasts, was used to assess the proliferative or apoptotic effects associated with lentiviral-induced HYAL1 overexpression using CCK-8 cell proliferation assay and Annexin V-APC staining. The identification of potentially associated molecular pathways was performed using microarray analysis followed by qRT-PCR and western blot analysis.

Results

Lung tissue microarray data mining and immunohistochemistry revealed significantly downregulation of HYAL1 in IPF lung tissue. However, HYAL1 in IPF lung tissue. However, HYAL1 in IPF lung tissue. However, HYAL1 in IPF lung tissue. However, β1-) induced aberrant fibroproliferation in response to epithelial injury. The TGFβ1-) induced aberrant fibroproliferation in response to epithelial injury. The TGF

Conclusions

We showed that HYAL1 overexpression could prevent HFL-1 fibroproliferation. Furthermore, our findings suggest that transcriptional regulators and BMP receptor signaling may be involved in HYAL1 modulation in IPF therapy.HYAL1 in IPF lung tissue. However,

Systematic review of using medical informatics in lung transplantation studies

BACKGROUND

Lung transplantation is one of the advanced treatment options performed even in patients suffering from end-stage lung disease. Due to the positive results of medical informatics in other fields of medicine, lung transplant researchers have also conducted remarkable studies to improve transplant outcomes. The main objective of this article was to review the current studies of health information technology used in lung transplantation.

METHODS

A systematic search was performed in four scientific databases (Web of Science, Scopus, Science Direct, and PubMed) from January 2000 to December 2018. The criteria for inclusion were included in any study describing the use of health information technology or medical informatics in terms of lung transplantation, English papers, and original researchers. The retrieved articles were accordingly screened based on the inclusion and exclusion criteria to select relevant studies. The survey and synthesis of included articles were conducted based on predefined classification.

RESULTS

Out of 263 articles, 27 studies met our inclusion criteria. All included studies involved the application of health information technology in lung transplantation. The types of health information technology methods applied in reviewed articles included mhealth (11.1 %), DSS (7.4 %), decision aid tools (7.4 %), telemedicine (22.2 %), AI methods (11.1 %), data mining (37 %), and patient education (3.7 %). The majority of studies (88.9 %) showed the positive impact of health information technology to enhance lung transplantation outcomes. Finally, the main approaches in different phases of lung transplantation processes were interpreted and summarized in the visual model.

CONCLUSION

This systematic review provides new insights regarding the application of medical informatics in the lung transplantation domain. The missing areas of medical informatics in the lung transplantation domain were recognized through this study.

Pan-transcriptome-based candidate therapeutic discovery for idiopathic pulmonary fibrosis

BACKGROUND

There are two US Food and Drug Administration (FDA)-approved drugs, pirfenidone and nintedanib, for treatment of patients with idiopathic pulmonary fibrosis (IPF). However, neither of these drugs provide a cure. In addition, both are associated with several drug-related adverse events. Hence, the pursuit for newer IPF therapeutics continues. Recent studies show that joint analysis of systems-biology-level information with drug-disease connectivity are effective in discovery of biologically relevant candidate therapeutics.

METHODS

Publicly available gene expression signatures from patients with IPF were used to query a large-scale perturbagen signature library to discover compounds that can potentially reverse dysregulated gene expression in IPF. Two methods were used to calculate IPF-compound connectivity: gene expression-based connectivity and feature-based connectivity. Identified compounds were further prioritized if their shared mechanism(s) of action were IPF-related.

RESULTS

We found 77 compounds as potential candidate therapeutics for IPF. Of these, 39 compounds are either FDA-approved for other diseases or are currently in phase II/III clinical trials suggesting their repurposing potential for IPF. Among these compounds are multiple receptor kinase inhibitors (e.g. nintedanib, currently approved for IPF, and sunitinib), aurora kinase inhibitor (barasertib), epidermal growth factor receptor inhibitors (erlotinib, gefitinib), calcium channel blocker (verapamil), phosphodiesterase inhibitors (roflumilast, sildenafil), PPAR agonists (pioglitazone), histone deacetylase inhibitors (entinostat), and opioid receptor antagonists (nalbuphine). As a proof of concept, we performed in vitro validations with verapamil using lung fibroblasts from IPF and show its potential benefits in pulmonary fibrosis.

CONCLUSIONS

As about half of the candidates discovered in this study are either FDA-approved or are currently in clinical trials for other diseases, rapid translation of these compounds as potential IPF therapeutics is possible. Further, the integrative connectivity analysis framework in this study can be adapted in early phase drug discovery for other common and rare diseases with transcriptomic profiles.The reviews of this paper are available via the supplemental material section.

Mitogen-activated Protein Kinase-activated Protein Kinase 2 Inhibition Attenuates Fibroblast Invasion and Severe Lung Fibrosis

Severe pulmonary fibrosis such as idiopathic pulmonary fibrosis (IPF) is characterized by the accumulation of extracellular matrix and fibroblast activation. Targeting fibroblast activation has contributed to the development of antifibrotic therapeutics for patients with IPF. Mitogen-activated protein kinase-activated protein kinase 2 (MK2), downstream in the transforming growth factor-β/p38 mitogen-activated protein kinase pathway, has been implicated in inflammatory and fibrosing diseases. Increased concentrations of activated MK2 were expressed in IPF lung and in the mouse bleomycin model of lung fibrosis. The aim of the present study was to determine the role and the mechanisms of MK2 in fibroblast invasion and lung fibrosis. Our results showed that an MK2 inhibitor (MMI-0100) was able to inhibit the invasive capacity of lung fibroblasts isolated from patients with IPF, as well as fibroblasts isolated from both wild-type mice and mice with overexpressing hyaluronan synthase 2 (HAS2) in the myofibroblast compartment. We previously showed that hyaluronan and HAS2 regulate fibroblast invasion and lung fibrosis in vivo. The results of the present study showed that MMI-0100 reduced transforming growth factor-β-induced hyaluronan production in human and mouse fibroblasts in vitro and that HAS2 mediated MK2 activation, suggesting a feed-forward loop in fibroblast activation. More importantly, MK2 inhibition attenuated hyaluronan accumulation and reduced collagen content in bleomycin-injured mouse lungs in vivo. Conditional deletion of MK2 in fibroblasts attenuated bleomycin-induced lung fibrosis. These data provide evidence that MK2 has a role in fibroblast invasion and fibrosis and may be a novel therapeutic target in pulmonary fibrosis.

Role of B7H3/IL-33 Signaling in Pulmonary Fibrosis-induced Profibrogenic Alterations in Bone Marrow

Rationale: The impact of lung insult on the bone marrow (BM) and subsequent disease is unknown.Objectives: To study alterations in the BM in response to lung injury/fibrosis and examine their impact on subsequent lung insult.Methods: BM cells from control or bleomycin-treated donor mice were transplanted into naive mice, which were subsequently evaluated for bleomycin-induced pulmonary fibrosis. In addition, the effect of prior bleomycin treatment on subsequent fibrosis was examined in wild-type and B7H3-knockout mice. Samples from patients with idiopathic pulmonary fibrosis were analyzed for potential clinical relevance of the findings.Measurements and Main Results: Recipient mice transplanted with BM from bleomycin-pretreated donors showed significant exacerbation of subsequent fibrosis with increased B7H3+ cell numbers and a T-helper cell type 2-skewed phenotype. Pretreatment with a minimally fibrogenic/nonfibrogenic dose of bleomycin also caused exacerbation, but not in B7H3-deficient mice. Exacerbation was not observed if the mice received naive BM cell transplant after the initial bleomycin pretreatment. Soluble B7H3 stimulated BM Ly6Chi monocytic cell expansion in vitro and caused similar expansion in the lung in vivo. Notably, soluble B7H3 was elevated in plasma of patients with idiopathic pulmonary fibrosis and in BAL fluid in those with acute exacerbation. Finally, ST2 deficiency diminished the bleomycin-induced B7H3 and IL-13 upregulation, suggesting a role for type 2 innate lymphoid cells.Conclusions: Pulmonary fibrosis caused significant alterations in BM with expansion and activation of monocytic cells, which enhanced fibrosis when transplanted to naive recipients with potential mediation by a novel role for B7H3 in the pathophysiology of pulmonary fibrosis in both mice and humans.

Weighted Gene Coexpression Network Analysis Identifies Key Genes and Pathways Associated with Idiopathic Pulmonary Fibrosis

BACKGROUND Idiopathic pulmonary fibrosis (IPF) is a life-threatening disease with an unknown etiology. Gene expression microarray data have provided some insights into the molecular mechanisms of IPF. This study aimed to identify key genes and significant signaling pathways involved in IPF using bioinformatics analysis. MATERIAL AND METHODS Differentially expressed genes (DEGs) were identified using integrated analysis of gene expression data with a robust rank aggregation (RRA) method. The Connectivity Map (CMAP) was used to identify gene-expression signatures associated with IPF. Weighted gene coexpression network analysis (WGCNA) was used to explore the functional modules involved in the pathogenesis of IPF. RESULTS A total of 191 patients with IPF and 101 normal controls from six genome-wide expression datasets were included. CMAP predicted several small molecular agents as potential gene targets in IPF. Several functional modules were detected that showed the highest correlation with IPF, including an extracellular matrix (ECM) component, and a myeloid leukocyte migration and activation component involved in the immune response. Hub genes were identified in the key functional modules that might have a role in the progression of IPF. CONCLUSIONS WGCNA was used to identify functional modules and hub genes involved in the pathogenesis of IPF.