Epigenetic Regulation of Profibrotic Macrophages in Systemic Sclerosis-Associated Interstitial Lung Disease

Macrophages as determinants and regulators of systemic sclerosis-related interstitial lung disease

BACKGROUND

Interstitial lung disease (ILD) is the primary cause of mortality in systemic sclerosis (SSc), an autoimmune disease characterized by tissue fibrosis. SSc-related ILD (SSc-ILD) occurs more frequently in females aged 30-55 years, whereas idiopathic pulmonary fibrosis (IPF) is more prevalent in males aged 60-75 years. SSc-ILD occurs earlier than IPF and progresses rapidly. FCN1, FABP4, and SPP1 macrophages are involved in the pathogenesis of lung fibrosis; SPP1 macrophages demonstrate upregulated expression in both SSc-ILD and IPF. To identify the differences between SSc-ILD and IPF using single-cell analysis, clarify their distinct pathogeneses, and propose directions for prevention and treatment.

METHODS

We performed single-cell RNA sequencing on NCBI Gene Expression Omnibus (GEO) databases GSE159354 and GSE212109, and analyzed lung tissue samples across healthy controls, IPF, and SSc-ILD. The primary measures were the filtered genes integrated with batch correction and annotated cell types for distinguishing patients with SSc-ILD from healthy controls. We proposed an SSc-ILD pathogenesis using cell-cell interaction inferences, and predicted transcription factors regulating target genes using SCENIC. Drug target prediction of the TF gene was performed using Drug Bank Online.

RESULTS

A subset of macrophages activates the MAPK signaling pathway under oxidative stress. Owing to the lack of inhibitory feedback from ANNEXIN and the autoimmune characteristics, this leads to an earlier onset of lung fibrosis compared to IPF. During initial lung injury, fibroblasts begin to activate the IL6 pathway under the influence of SPP1 alveolar macrophages, but IL6 appears unrelated to other inflammatory and immune cells. This may explain why tocilizumab (an anti-IL6-receptor antibody) only preserves lung function in patients with early SSc-ILD. Finally, we identified BCLAF1 and NFE2L2 as influencers of MAPK activation in macrophages. Metformin downregulates NFE2L2 and could serve as a repurposed drug candidate.

CONCLUSIONS

SPP1 alveolar macrophages play a role in the profibrotic activity of IPF and SSc-ILD. However, SSc-ILD is influenced by autoimmunity and oxidative stress, leading to the continuous activation of MAPK in macrophages. This may result in an earlier onset of lung fibrosis than in IPF. Such differences could serve as potential research directions for early prevention and treatment.

Single cell analysis in systemic sclerosis - A systematic review

In recent years, rapid advances in research methods have made single cell analysis possible. Systemic sclerosis (SSc), a disease characterized by the triad of immune abnormalities, fibrosis, and vasculopathy, has also been the subject of various analyses. To summarize the results of single cell analysis in SSc accumulated to date and to deepen our understanding of SSc. Four databases were used to perform a database search on 23rd June 2023. Assessed Grading of Recommendations Assessment, Development and Evaluation certainty of evidence were performed according to PRISMA guidelines. The analysis was completed on July 2023. 17 studies with 358 SSc patients were included. Three studies used PBMCs, six used skin, nine used lung with SSc-interstitial lung diseases (ILDs), and one used lung with SSc-pulmonary arterial hypertension (PAH). The cells studied included immune cells such as T cells, natural killer cells, monocytes, macrophages, and dendritic cells, as well as endothelial cells, fibroblasts, keratinocytes, alveolar type I cells, basal epithelial cells, smooth muscle cells, mesothelial cells, etc. This systematic review revealed the results of single cell analysis, suggesting that PBMCs, skin, SSc-ILD, and SSc-PAH show activation and dysfunction of cells associated with immune-abnormalities, fibrosis, and vasculopathy, respectively.

Tumor-associated macrophage subtypes on cancer immunity along with prognostic analysis and SPP1-mediated interactions between tumor cells and macrophages

Tumor-associated macrophages (TAM) subtypes have been shown to impact cancer prognosis and resistance to immunotherapy. However, there is still a lack of systematic investigation into their molecular characteristics and clinical relevance in different cancer types. Single-cell RNA sequencing data from three different tumor types were used to cluster and type macrophages. Functional analysis and communication of TAM subpopulations were performed by Gene Ontology-Biological Process and CellChat respectively. Differential expression of characteristic genes in subpopulations was calculated using zscore as well as edgeR and Wilcoxon rank sum tests, and subsequently gene enrichment analysis of characteristic genes and anti-PD-1 resistance was performed by the REACTOME database. We revealed the heterogeneity of TAM, and identified eleven subtypes and their impact on prognosis. These subtypes expressed different molecular functions respectively, such as being involved in T cell activation, apoptosis and differentiation, or regulating viral bioprocesses or responses to viruses. The SPP1 pathway was identified as a critical mediator of communication between TAM subpopulations, as well as between TAM and epithelial cells. Macrophages with high expression of SPP1 resulted in poorer survival. By in vitro study, we showed SPP1 mediated the interactions between TAM clusters and between TAM and tumor cells. SPP1 promoted the tumor-promoting ability of TAM, and increased PDL1 expression and stemness of tumor cells. Inhibition of SPP1 attenuated N-cadherin and β-catenin expression and the activation of AKT and STAT3 pathway in tumor cells. Additionally, we found that several subpopulations could decrease the sensitivity of anti-PD-1 therapy in melanoma. SPP1 signal was a critical pathway of communication between macrophage subtypes. Some specific macrophage subtypes were associated with immunotherapy resistance and prognosis in some cancer types.

Deciphering the fibrotic process: mechanism of chronic radiation skin injury fibrosis

This review explores the mechanisms of chronic radiation-induced skin injury fibrosis, focusing on the transition from acute radiation damage to a chronic fibrotic state. It reviewed the cellular and molecular responses of the skin to radiation, highlighting the role of myofibroblasts and the significant impact of Transforming Growth Factor-beta (TGF-β) in promoting fibroblast-to-myofibroblast transformation. The review delves into the epigenetic regulation of fibrotic gene expression, the contribution of extracellular matrix proteins to the fibrotic microenvironment, and the regulation of the immune system in the context of fibrosis. Additionally, it discusses the potential of biomaterials and artificial intelligence in medical research to advance the understanding and treatment of radiation-induced skin fibrosis, suggesting future directions involving bioinformatics and personalized therapeutic strategies to enhance patient quality of life.

scGRN: a comprehensive single-cell gene regulatory network platform of human and mouse

Gene regulatory networks (GRNs) are interpretable graph models encompassing the regulatory interactions between transcription factors (TFs) and their downstream target genes. Making sense of the topology and dynamics of GRNs is fundamental to interpreting the mechanisms of disease etiology and translating corresponding findings into novel therapies. Recent advances in single-cell multi-omics techniques have prompted the computational inference of GRNs from single-cell transcriptomic and epigenomic data at an unprecedented resolution. Here, we present scGRN (https://bio.liclab.net/scGRN/), a comprehensive single-cell multi-omics gene regulatory network platform of human and mouse. The current version of scGRN catalogs 237 051 cell type-specific GRNs (62 999 692 TF-target gene pairs), covering 160 tissues/cell lines and 1324 single-cell samples. scGRN is the first resource documenting large-scale cell type-specific GRN information of diverse human and mouse conditions inferred from single-cell multi-omics data. We have implemented multiple online tools for effective GRN analysis, including differential TF-target network analysis, TF enrichment analysis, and pathway downstream analysis. We also provided details about TF binding to promoters, super-enhancers and typical enhancers of target genes in GRNs. Taken together, scGRN is an integrative and useful platform for searching, browsing, analyzing, visualizing and downloading GRNs of interest, enabling insight into the differences in regulatory mechanisms across diverse conditions.

Proteomic profiling identifies SPP1 associated with rapidly progressive interstitial lung disease in anti-MDA5-positive dermatomyositis

BACKGROUND

Anti-melanoma differentiation-associated gene five antibody positive (MDA5+) dermatomyositis (DM) is significantly associated with rapidly progressive interstitial lung disease (RP-ILD). Early detection of RP-ILD remains a major challenge. This study aims to identify and validate prognostic factors for RP-ILD in MDA5+ DM patients.

METHODS

Plasma samples from 20 MDA5+ DM patients and 10 healthy controls (HC) were collected for proteomic analysis using liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. The proteins of interest were validated in independent samples (20 HC, 20 MDA5+ DM with RP-ILD, and 20 non-RP-ILD patients) with enzyme-linked immunosorbent assay (ELISA).

RESULTS

A total of 413 differentially expressed proteins (DEPs) were detected between the MDA5+ DM patients and HC. When comparing DEPs between RP-ILD and non-RP-ILD patients, 79 proteins were changed in RP-ILD patients, implicating acute inflammatory response, coagulation, and complement cascades. Six candidate biomarkers were confirmed with ELISA. Secreted phosphoprotein 1 (SPP1), serum amyloid A1 (SAA1), and Kininogen 1 (KNG1) concentrations were significantly elevated in RP-ILD patients than those in non-RP-ILD patients and HC. In the different clinical subgroups, SPP1 was particularly elevated in the high-risk RP-ILD subgroup of MDA5+ DM.

CONCLUSION

This study provides novel insights into the pathogenesis of RP-ILD development in MDA5+ DM and suggests the plasma protein SPP1 could serve as a potential blood biomarker for RP-ILD early warning.

Non-classical circulating monocytes expressing high levels of microsomal prostaglandin E2 synthase-1 tag an aberrant IFN-response in systemic sclerosis

Systemic sclerosis (SSc) is a complex disease that affects the connective tissue, causing fibrosis. SSc patients show altered immune cell composition and activation in the peripheral blood (PB). PB monocytes (Mos) are recruited into tissues where they differentiate into macrophages, which are directly involved in fibrosis. To understand the role of CD14+ PB Mos in SSc, a single-cell transcriptome analysis (scRNA-seq) was conducted on 8 SSc patients and 8 controls. Using unsupervised clustering methods, CD14+ cells were assigned to 11 clusters, which added granularity to the known monocyte subsets: classical (cMos), intermediate (iMos) and non-classical Mos (ncMos) or type 2 dendritic cells. NcMos were significantly overrepresented in SSc patients and showed an active IFN-signature and increased expression levels of PTGES, in addition to monocyte motility and adhesion markers. We identified a SSc-related cluster of IRF7+ STAT1+ iMos with an aberrant IFN-response. Finally, a depletion of M2 polarised cMos in SSc was observed. Our results highlighted the potential of PB Mos as biomarkers for SSc and provided new possibilities for putative drug targets for modulating the innate immune response in SSc.

Treatable Traits in Systemic Sclerosis

Systemic sclerosis (SSc) is a chronic systemic disease within the spectrum of connective tissue diseases, specifically characterized by vascular abnormalities and inflammatory and fibrotic involvement of the skin and internal organs resulting in high morbidity and mortality. The clinical phenotype of SSc is heterogeneous, and serum autoantibodies together with the extent of skin involvement have a predictive value in the risk stratification. Current recommendations include an organ-based management according to the predominant involvement with only limited individual factors included in the treatment algorithm. Similar to what has been proposed for other chronic diseases, we hypothesize that a "treatable trait" approach based on relevant phenotypes and endotypes could address the unmet needs in SSc stratification and treatment to maximize the outcomes. We provide herein a comprehensive review and a critical discussion of the literature regarding potential treatable traits in SSc, focusing on established and candidate biomarkers, with the purpose of setting the bases for a precision medicine-based approach. The discussion, structured based on the organ involvement, allows to conjugate the pathogenetic mechanisms of tissue injury with the proposed predictors, particularly autoantibodies and other serum biomarkers. Ultimately, we are convinced that precision medicine is the ideal guide to manage a complex condition such as SSc for which available treatments are largely unsatisfactory.

Impact of enzymatic digestion on single cell suspension yield from peripheral human lung tissue

An increasing number of translational investigations of lung biology rely on analyzing single cell suspensions obtained from human lungs. To obtain these single cell suspensions, human lungs from biopsies or research-consented organ donors must be subjected to mechanical and enzymatic digestion prior to analysis with either flow cytometry or single cell RNA sequencing. A variety of enzymes have been used to perform tissue digestion, each with potential limitations. To better understand the limitations of each enzymatic digestion protocol and to establish a framework for comparing studies across protocols, we performed five commonly published protocols in parallel from identical samples obtained from 6 human lungs. Following mechanical (gentleMACS™) and enzymatic digestion, we quantified cell count and viability using a Nexcelom Cellometer and determined cell phenotype using multiparameter spectral flow cytometry (Cytek™ Aurora). We found that all protocols were superior in cellular yield and viability when compared to mechanical digestion alone. Protocols high in dispase cleaved immune markers CD4, CD8, CD69, and CD103 and contributed to an increased monocyte to macrophage yield. Similarly, dispase led to a differential epithelial cell yield, with increased TSPN8+ and ITGA6+ epithelial cells and reduced CD66e+ cells. When compared to collagenase D, collagenase P protocols yielded increased AT1 and AT2 cells and decreased endothelial cells. These results provide a framework for selecting an enzymatic digestion protocol best suited to the scientific question and allow for comparison of studies using different protocols.

Diagnostic and prognostic value of secreted phosphoprotein 1 for idiopathic pulmonary fibrosis: a systematic review and meta-analysis

BackgroundThere is an increasing number of studies on the diagnostic and prognostic biomarkers associated with IPF. The purpose of this study was to explore the diagnostic and prognostic value of secreted phosphoprotein 1 (SPP1) in IPF.MethodsUsing five database, appropriate studies were included. Pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR) and 95% confidence intervals (CIs) were calculated. Pooled hazard ratios (HRs) and 95% CIs related to prognosis were calculated.ResultsThirteen studies were included in the meta-analyses. The pooled sensitivity, specificity, PLR, NLR and DOR were 0.84 (95% CI 0.72-0.91), 0.89 (95% CI 0.83-0.94), 7.94 (95% CI 4.63-13.62), 0.18 (95% CI 0.10-0.33), 43.08 (95% CI 15.88-116.84) for SPP1 in the differential diagnosis of IPF and healthy people. The pooled sensitivity, specificity, PLR, NLR and DOR were 0.97 (95% CI 0.57-1.00), 0.93 (95% CI 0.73-0.98), 13.87 (95% CI 3.26-58.99), 0.03 (95% CI 0-0.68), 446.91 (95% CI 21.02-9504.41) for SPP1 to differentiate IPF and lung cancer patients. High SPP1 expression predicts poor prognosis for IPF patients (HR= 1.42, 95% CI = 1.27 and 1.58, P < 0.001).ConclusionsSPP1 is a potential diagnostic and prognostic biomarker for IPF patients.