Hck/Fgr Kinase Deficiency Reduces Plaque Growth and Stability by Blunting Monocyte Recruitment and Intraplaque Motility

Recent advances in hematopoietic cell kinase in cancer progression: Mechanisms and inhibitors

Hematopoietic cell kinase (Hck), a non-receptor tyrosine kinase belonging to the Src kinase family, is intricately linked to the pathogenesis of numerous human diseases, with a particularly pronounced association with cancer. Hck not only directly impacts the proliferation, migration, and apoptosis of cancer cells but also interacts with JAK/STAT, MEK/ERK, PI3K/AKT, CXCL12/CXCR4, and other pathways. Hck also influences the tumor microenvironment to facilitate the onset and progression of cancer. This paper delves into the functional role and regulatory mechanisms of Hck in various solid tumors. Additionally, it explores the implications of Hck in hematological malignancies. The review culminates with a summary of the current research status of Hck inhibitors, the majority of which are in the pre-clinical phase of investigation. Notably, these inhibitors are predominantly utilized in the therapeutic management of leukemia, with their combinatorial potential indicating promising avenues for future research. In conclusion, this review underscores the significance of the mechanism of Hck in solid tumors. This insight is crucial for comprehending the current research trends regarding Hck: targeted therapy against Hck shows great promise in both diagnosis and treatment of malignant tumors. Further investigation into the role of Hck in cancer, coupled with the development of specific inhibitors, has the potential to revolutionize approaches to cancer treatment.

Novel biomarkers identified by weighted gene co-expression network analysis for atherosclerosis

BACKGROUND

This study aimed to screen out the potential diagnostic biomarkers for atherosclerosis (AS).

METHODS

We downloaded the gene expression profiles GSE66360, GSE28829, GSE41571, GSE71226, and GSE100927 from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified using the "limma" package in R. Weighted gene co-expression network analysis (WGCNA) was applied to reveal the correlation between genes in different samples. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. The interaction pairs of proteins were retained by the STRING database, and the protein-protein interaction (PPI) network was visualized with the hub genes. Finally, the R packages "ggpubr" and "preprocessCore" were used to analyze immune cell infiltration.

RESULTS

In total, 40 overlapping genes both in GSE66360 and GSE28829 were found to be related to the occurrence of AS. Further, the top 10 network hub genes including TYROBP, CSF1R, TLR2, CD14, CCL4, FCER1G, CD163, TREM1, PLEK, and C5AR1 were identified as significant key genes. Moreover, four genes (TYROBP, CSF1R, FCGR1B, and CD14) were verified that could efficiently diagnose AS. Finally, the gene TYROBP was found to have a strong correlation with immune-infiltrating cells.

CONCLUSION

Our study identified four genes (TYROBP, CSF1R, FCGR1B, and CD14) that may be effective biomarkers for AS, with the potential to guide the clinical diagnosis of AS.

Detection of common pathogenesis of rheumatoid arthritis and atherosclerosis via microarray data analysis

Despite extensive research reveal rheumatoid arthritis (RA) is related to atherosclerosis (AS), common pathogenesis between these two diseases still needs to be explored. In current study, we explored the common pathogenesis between rheumatoid arthritis (RA) and atherosclerosis (AS) by identifying 297 Differentially Expressed Genes (DEGs) associated with both diseases. Through KEGG and GO functional analysis, we highlighted the correlation of these DEGs with crucial biological processes such as the vesicle transport, immune system process, signaling receptor binding, chemokine signaling and many others. Employing Protein-Protein Interaction (PPI) network analysis, we elucidated the associations between DEGs, revealing three gene modules enriched in immune system process, vesicle, signaling receptor binding, Pertussis, and among others. Additionally, through CytoHubba analysis, we pinpointed 11 hub genes integral to intergrin-mediated signaling pathway, plasma membrane, phosphotyrosine binding, chemokine signaling pathway and so on. Further investigation via the TRRUST database identified two key Transcription Factors (TFs), SPI1 and RELA, closely linked with these hub genes, shedding light on their regulatory roles. Finally, leveraging the collective insights from hub genes and TFs, we proposed 10 potential drug candidates targeting the molecular mechanisms underlying RA and AS pathogenesis. Further investigation on xCell revealed that 14 types of cells were all different in both AS and RA. This study underscores the shared pathogenic mechanisms, pivotal genes, and potential therapeutic interventions bridging RA and AS, offering valuable insights for future research and clinical management strategies.

Exploring the pathogenesis of chronic atrophic gastritis with atherosclerosis via microarray data analysis

Although several studies have reported a link between chronic atrophic gastritis (CAG) and atherosclerosis, the underlying mechanisms have not been elucidated. The present study aimed to investigate the molecular mechanisms common to both diseases from a bioinformatics perspective. Gene expression profiles were obtained from the Gene Expression Omnibus database. Data on atherosclerosis and CAG were downloaded from the GSE28829 and GSE60662 datasets, respectively. We identified the differentially expressed genes co-expressed in CAG and atherosclerosis before subsequent analyses. We constructed and identified the hub genes and performed functional annotation. Finally, the transcription factor (TF)-target genes regulatory network was constructed. In addition, we validated core genes and certain TFs. We identified 116 common differentially expressed genes after analyzing the 2 datasets (GSE60662 and GSE28829). Functional analysis highlighted the significant contribution of immune responses and the positive regulation of tumor necrosis factor production and T cells. In addition, phagosomes, leukocyte transendothelial migration, and cell adhesion molecules strongly correlated with both diseases. Furthermore, 16 essential hub genes were selected with cytoHubba, including PTPRC, TYROBP, ITGB2, LCP2, ITGAM, FCGR3A, CSF1R, IRF8, C1QB, TLR2, IL10RA, ITGAX, CYBB, LAPTM5, CD53, CCL4, and LY86. Finally, we searched for key gene-related TFs, especially SPI1. Our findings reveal a shared pathogenesis between CAG and atherosclerosis. Such joint pathways and hub genes provide new insights for further studies.

Insights on hematopoietic cell kinase: An oncogenic player in human cancer

Hematopoietic cell kinase (Hck) is a member of the Src family and is expressed in hematopoietic cells. By regulating multiple signaling pathways, HCK can interact with multiple receptors to regulate signaling events involved in cell adhesion, proliferation, migration, invasion, apoptosis, and angiogenesis. However, aberrant expression of Hck in various hematopoietic cells and solid tumors plays a crucial role in tumor-related properties, including cell proliferation and epithelial-mesenchymal transition. In addition, Hck signaling regulates the function of immune cells such as macrophages, contributing to an immunosuppressive tumor microenvironment. The clinical success of various kinase inhibitors targeting the Src kinase family has validated the efficacy of targeting Src, and therapies with highly selective Hck kinase inhibitors are in clinical trials. This article reviews Hck inhibition as an emerging cancer treatment strategy, focusing on the expressions and functions of Hck in tumors and its impact on the tumor microenvironment. It also explores preclinical and clinical pharmacological strategies for Hck targeting to shed light on Hck-targeted tumor therapy.

Immune-associated biomarkers identification for diagnosing carotid plaque progression with uremia through systematical bioinformatics and machine learning analysis

BACKGROUND

Uremia is one of the most challenging problems in medicine and an increasing public health issue worldwide. Patients with uremia suffer from accelerated atherosclerosis, and atherosclerosis progression may trigger plaque instability and clinical events. As a result, cardiovascular and cerebrovascular complications are more likely to occur. This study aimed to identify diagnostic biomarkers in uremic patients with unstable carotid plaques (USCPs).

METHODS

Four microarray datasets (GSE37171, GSE41571, GSE163154, and GSE28829) were downloaded from the NCBI Gene Expression Omnibus database. The Limma package was used to identify differentially expressed genes (DEGs) in uremia and USCP. Weighted gene co-expression network analysis (WGCNA) was used to determine the respective significant module genes associated with uremia and USCP. Moreover, a protein-protein interaction (PPI) network and three machine learning algorithms were applied to detect potential diagnostic genes. Subsequently, a nomogram and a receiver operating characteristic curve (ROC) were plotted to diagnose USCP with uremia. Finally, immune cell infiltrations were further analyzed.

RESULTS

Using the Limma package and WGCNA, the intersection of 2795 uremia-related DEGs and 1127 USCP-related DEGs yielded 99 uremia-related DEGs in USCP. 20 genes were selected as candidate hub genes via PPI network construction. Based on the intersection of genes from the three machine learning algorithms, three hub genes (FGR, LCP1, and C5AR1) were identified and used to establish a nomogram that displayed a high diagnostic performance (AUC: 0.989, 95% CI 0.971-1.000). Dysregulated immune cell infiltrations were observed in USCP, showing positive correlations with the three hub genes.

CONCLUSION

The current study systematically identified three candidate hub genes (FGR, LCP1, and C5AR1) and established a nomogram to assist in diagnosing USCP with uremia using various bioinformatic analyses and machine learning algorithms. Herein, the findings provide a foothold for future studies on potential diagnostic candidate genes for USCP in uremic patients. Additionally, immune cell infiltration analysis revealed that the dysregulated immune cell proportions were identified, and macrophages could have a critical role in USCP pathogenesis.

Stem Cell-based Therapies in Cardiovascular Diseases: From Pathophysiology to Clinical Outcomes

Over 20 years of intensified research in the field of stem cells brought about unprecedented possibilities in treating heart diseases. The investigators were initially fascinated by the idea of regenerating the lost myocardium and replacing it with new functional cardiomyocytes, but this was extremely challenging. However, the multifactorial effects of stem cell-based therapies beyond mere cardiomyocyte generation, caused by paracrine signaling, would open up new possibilities in treating cardiovascular diseases. To date, there is a strong body of evidence that the anti-inflammatory, anti-apoptotic, and immunomodulatory effects of stem cell therapy may alleviate atherosclerosis progression. In the present review, our objective is to provide a brief overview of the stem cell-based therapeutic options. We aim to delineate the pathophysiological mechanisms of their beneficial effects in cardiovascular diseases especially in coronary artery disease and to highlight some conclusions from important clinical studies in the field of regenerative medicine in cardiovascular diseases and how we could further move onwards.

Bioinformatics analysis of potential pathogenesis and risk genes of immunoinflammation-promoted renal injury in severe COVID-19

Renal injury secondary to COVID-19 is an important factor for the poor prognosis of COVID-19 patients. The pathogenesis of renal injury caused by aberrant immune inflammatory of COVID-19 remains unclear. In this study, a total of 166 samples from 4 peripheral blood transcriptomic datasets of COVID-19 patients were integrated. By using the weighted gene co-expression network (WGCNA) algorithm, we identified key genes for mild, moderate, and severe COVID-19. Subsequently, taking these genes as input genes, we performed Short Time-series Expression Miner (STEM) analysis in a time consecutive ischemia-reperfusion injury (IRI) -kidney dataset to identify genes associated with renal injury in COVID-19. The results showed that only in severe COVID-19 there exist a small group of genes associated with the progression of renal injury. Gene enrichment analysis revealed that these genes are involved in extensive immune inflammation and cell death-related pathways. A further protein-protein interaction (PPI) network analysis screened 15 PPI-hub genes: ALOX5, CD38, GSF3R, LGR, RPR1, HCK, ITGAX, LYN, MAPK3, NCF4, SELP, SPI1, WAS, TLR2 and TLR4. Single-cell sequencing analysis indicated that PPI-hub genes were mainly distributed in neutrophils, macrophages, and dendritic cells. Intercellular ligand-receptor analysis characterized the activated ligand-receptors between these immune cells and parenchyma cells in depth. And KEGG enrichment analysis revealed that viral protein interaction with cytokine and cytokine receptor, necroptosis, and Toll-like receptor signaling pathway may be potentially essential for immune cell infiltration leading to COVID-19 renal injury. Finally, we validated the expression pattern of PPI-hub genes in an independent data set by random forest. In addition, we found that the high expression of these genes was correlated with a low glomerular filtration rate. Including them as risk genes in lasso regression, we constructed a Nomogram model for predicting severe COVID-19. In conclusion, our study explores the pathogenesis of renal injury promoted by immunoinflammatory in severe COVID-19 and extends the clinical utility of its key genes.

Macrophages-Related Genes Biomarkers in the Deterioration of Atherosclerosis

Background

The macrophages are involved in all stages of cardiovascular diseases, demonstrating the correlation between inflammation, atherosclerosis, and myocardial infarction (MI). Here, we aim to investigate macrophages-related genes in the deterioration of atherosclerosis.

Methods

GSE41571 was downloaded and the abundance of immune cells was estimated by utilizing the xCell. By utilizing the limma test and correlation analysis, differentially expressed macrophages-related genes (DEMRGs) were documented. The functional pathways and the protein–protein interaction (PPI) network were analyzed and the hub DEMRGs were obtained. The hub DEMRGs and their interactions were analyzed using NetworkAnalyst 3.0 and for validation, the expressions of hub DEMRGs were analyzed using the GSE135055 and GSE116250 datasets as well as atherosclerosis and MI mice model.

Results

A total of 509 differentially expressed genes (DEGs) were correlated with the abundance of macrophages and were identified as DEMRGs (Pearson correlation coefficients (PCC) > 0.6), which were mainly enriched in extracellular structure organization, lysosomal membrane, MHC protein complex binding, and so on. After screening out, 28 hub DEMRGs were obtained with degrees ≥20, including GNAI1 (degree = 113), MRPS2 (degree = 56), HCK (degree = 45), SOCS3 (degree = 40), NET1 (degree = 28), and so on. After validating using Gene Expression Omnibus (GEO) datasets and the atherosclerosis and MI mice model, eight proteins were validated using ApoE-/- and C57 mice. The expression levels of proteins, including SYNJ2, NET1, FZD7, LCP2, HCK, GNB2, and PPP4C were positively correlated to left ventricular ejection fraction (LVEF), while that of EIF4EBP1 was negatively correlated to LVEF.

Conclusion

The screened hub DEMRGs, SYNJ2, NET1, FZD7, LCP2, HCK, GNB2, EIF4EBP1, and PPP4C, may be therapeutic targets for treatment and prediction in the patients with plaque progression and MI recurrent events. The kit of the eight hub DEMRGs may test plaque progression and MI recurrent events and help in the diagnosis and treatment of MI-induced heart failure (HF), thus decreasing mortality and morbidity.

Identification of hub genes and regulatory networks in histologically unstable carotid atherosclerotic plaque by bioinformatics analysis

Objective

This study identified underlying genetic molecules associated with histologically unstable carotid atherosclerotic plaques through bioinformatics analysis that may be potential biomarkers and therapeutic targets.

Methods

Three transcriptome datasets (GSE41571, GSE120521 and E-MTAB-2055) and one non-coding RNA dataset (GSE111794) that met histological grouping criteria of unstable plaque were downloaded. The common differentially expressed genes (co-DEGs) of unstable plaques identified from three mRNA datasets were annotated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomics (KEGG). A protein–protein interaction (PPI) network was constructed to present the interaction between co-DEGs and screen out hub genes. MiRNet database and GSE111794 dataset were used to identify the miRNAs targeting hub genes. Associated transcription factors (TFs) and drugs were also predicted. These predicted results were used to construct miRNA/TFs-hub gene and drug-hub gene regulatory networks.

Results

A total of 105 co-DEGs were identified, including 42 up-regulated genes and 63 down-regulated genes, which were mainly enriched in collagen-containing extracellular matrix, focal adhesion, actin filament bundle, chemokine signaling pathway and regulates of actin cytoskeleton. Ten hub genes (up-regulated: HCK, C1QC, CD14, FCER1G, LCP1 and RAC2; down-regulated: TPM1, MYH10, PLS3 and FMOD) were screened. HCK and RAC2 were involved in chemokine signaling pathway, MYH10 and RAC2 were involved in regulation of actin cytoskeleton. We also predicted 12 miRNAs, top5 TFs and 25 drugs targeting hub genes. In the miRNA/TF-hub gene regulatory network, PLS3 was the most connected hub genes and was targeted by six miRNAs and all five screened TFs. In the drug-hub gene regulatory network, HCK was targeted by 20 drugs including 10 inhibitors.

Conclusions

We screened 10 hub genes and predicted miRNAs and TFs targeting them. These molecules may play a crucial role in the progression of histologically unstable carotid plaques and serve as potential biomarkers and therapeutic targets.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01257-1.

Construction of genetic classification model for coronary atherosclerosis heart disease using three machine learning methods

Background

Although the diagnostic method for coronary atherosclerosis heart disease (CAD) is constantly innovated, CAD in the early stage is still missed diagnosis for the absence of any symptoms. The gene expression levels varied during disease development; therefore, a classifier based on gene expression might contribute to CAD diagnosis. This study aimed to construct genetic classification models for CAD using gene expression data, which may provide new insight into the understanding of its pathogenesis.

Methods

All statistical analysis was completed by R 3.4.4 software. Three raw gene expression datasets (GSE12288, GSE7638 and GSE66360) related to CAD were downloaded from the Gene Expression Omnibus database and included for analysis. Limma package was performed to identify differentially expressed genes (DEGs) between CAD samples and healthy controls. The WGCNA package was conducted to recognize CAD-related gene modules and hub genes, followed by recursive feature elimination analysis to select the optimal features genes (OFGs). The genetic classification models were established using support vector machine (SVM), random forest (RF) and logistic regression (LR), respectively. Further validation and receiver operating characteristic (ROC) curve analysis were conducted to evaluate the classification performance.

Results

In total, 374 DEGs, eight gene modules, 33 hub genes and 12 OFGs (HTR4, KISS1, CA12, CAMK2B, KLK2, DDC, CNGB1, DERL1, BCL6, LILRA2, HCK, MTF2) were identified. ROC curve analysis showed that the accuracy of SVM, RF and LR were 75.58%, 63.57% and 63.95% in validation; with area under the curve of 0.813 (95% confidence interval, 95% CI 0.761–0.866, P < 0.0001), 0.727 (95% CI 0.665–0.788, P < 0.0001) and 0.783 (95% CI 0.725–0.841, P < 0.0001), respectively.

Conclusions

In conclusion, this study found 12 gene signatures involved in the pathogenic mechanism of CAD. Among the CAD classifiers constructed by three machine learning methods, the SVM model has the best performance.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-022-02481-4.

Comprehensive Analysis to Identify Key Genes Involved in Advanced Atherosclerosis

Background

The study was aimed at finding accurate and effective therapeutic targets and deepening our understanding of the mechanisms of advanced atherosclerosis (AA).

Methods

We downloaded the gene expression datasets GSE28829, GSE120521, and GSE43292 from Gene Expression Omnibus. Weighted gene coexpression network analysis (WGCNA) was performed for GSE28829, and functional enrichment analysis and protein–protein interaction network analysis were conducted on the key module. Significant genes in the key module were analyzed by molecular complex detection, and genes in the most important subnetwork were defined as hub genes. Multiple dataset analyses for hub genes were conducted. Genes that overlapped between hub genes and differentially expressed genes (DEGs) of GSE28829 and GSE120521 were defined as key genes. Further validation for key genes was performed using GSE28829 and GSE43292. Gene set enrichment analysis (GSEA) was applied to key genes.

Results

A total of 77 significant genes in the key module of GSE28829 were screened out that were mainly associated with inflammation and immunity. The subnetwork was obtained from significant genes, and 18 genes in this module were defined as hub genes, which were related to immunity and expressed in multiple diseases, particularly systemic lupus erythematosus. Some hub genes were regulated by SPI1 and associated with the blood, spleen, and lung. After overlapping with DEGs of GSE28829 and GSE120521, a total of 10 genes (HCK, ITGAM, CTSS, TYROBP, LAPTM5, FCER1G, ITGB2, NCF2, AIF1, and CD86) were identified as key genes. All key genes were validated and evaluated successfully and were related to immune response pathways.

Conclusion

Our study suggests that the key genes related to immune and inflammatory responses are involved in the development of AA. This may deepen our understanding of the mechanisms of and provide valuable therapeutic targets for AA.

Early-onset pulmonary and cutaneous vasculitis driven by constitutively active SRC-family kinase HCK

BACKGROUND

Inborn errors of immunity (IEI) are genetic disorders characterized by various degrees of immune dysregulation that can manifest as immune deficiency, autoimmunity or autoinflammation. The routine use of next-generation sequencing in the clinic has facilitated the identification of an ever-increasing number of IEI, revealing the roles of immunologically important genes in human pathologies. However, despite this progress, treatment is still extremely challenging.

OBJECTIVE

We report a new monogenic autoinflammatory disorder caused by a de novo activating mutation, p.Tyr515*, in hematopoietic cell kinase (HCK). The disease is characterized by cutaneous vasculitis and chronic pulmonary inflammation that progresses to fibrosis.

METHODS

Whole-exome sequencing, Sanger sequencing, mass spectrometry and western blotting were performed to identify and characterize the pathogenic HCK mutation. Dysregulation of mutant HCK was confirmed ex vivo in primary cells and in vitro in transduced cell lines.

RESULTS

Mutant HCK lacking the C-terminal inhibitory tyrosine Tyr522 exhibited increased kinase activity and enhanced myeloid cell priming, migration and effector functions, such as production of the inflammatory cytokines IL-1β, IL-6, IL-8 and TNFα and production of reactive oxygen species. These aberrant functions were reflected by inflammatory leukocyte infiltration of the lungs and skin. Moreover, an overview of the clinical course of the disease, including therapies, provides evidence for the therapeutic efficacy of the Janus kinase (JAK) 1/2 inhibitor ruxolitinib in inflammatory lung disease.

CONCLUSION

We propose HCK-driven pulmonary and cutaneous vasculitis as a novel autoinflammatory disorder of IEI.

Targeting non-coding RNAs in unstable atherosclerotic plaques: Mechanism, regulation, possibilities, and limitations

Cardiovascular diseases (CVDs) caused by arteriosclerosis are the leading cause of death and disability worldwide. In the late stages of atherosclerosis, the atherosclerotic plaque gradually expands in the blood vessels, resulting in vascular stenosis. When the unstable plaque ruptures and falls off, it blocks the vessel causing vascular thrombosis, leading to strokes, myocardial infarctions, and a series of other serious diseases that endanger people's lives. Therefore, regulating plaque stability is the main means used to address the high mortality associated with CVDs. The progression of the atherosclerotic plaque is a complex integration of vascular cell apoptosis, lipid metabolism disorders, inflammatory cell infiltration, vascular smooth muscle cell migration, and neovascular infiltration. More recently, emerging evidence has demonstrated that non-coding RNAs (ncRNAs) play a significant role in regulating the pathophysiological process of atherosclerotic plaque formation by affecting the biological functions of the vasculature and its associated cells. The purpose of this paper is to comprehensively review the regulatory mechanisms involved in the susceptibility of atherosclerotic plaque rupture, discuss the limitations of current approaches to treat plaque instability, and highlight the potential clinical value of ncRNAs as novel diagnostic biomarkers and potential therapeutic strategies to improve plaque stability and reduce the risk of major cardiovascular events.

Gene deficiency or pharmacological inhibition of PDCD4-mediated FGR signaling protects against acute kidney injury

Recent studies have shown that programmed cell death 4 (PDCD4) modulates distinct signal transduction pathways in different pathological conditions. Despite acute and chronic immune responses elicited by ischemia contributing to the functional deterioration of the kidney, the contributions and mechanisms of PDCD4 in acute kidney injury (AKI) have remained unclear. Using two murine AKI models including renal ischemia/reperfusion injury (IRI) and cisplatin-induced AKI, we found that PDCD4 deficiency markedly ameliorated renal dysfunction and inflammatory responses in AKI mice. Consistently, upregulation of PDCD4 was also confirmed in the kidneys from patients with biopsy confirmed acute tubular necrosis from a retrospective cohort study. Moreover, we found that overexpression of Fgr, a member of the tyrosine kinase family, dramatically aggravated renal injury and counteracted the protective effects of PDCD4 deficiency in AKI mice. We discovered that FGR upregulated NOTCH1 expression through activating STAT3. Most importantly, we further found that systemic administration of ponatinib, a tyrosine kinase inhibitor, significantly ameliorated AKI in mice. In summary, we identified that PDCD4 served as an important regulator, at least in part, of FGR/NOTCH1-mediated tubular apoptosis and inflammation in AKI mice. Furthermore, our findings suggest that ponatinib-mediated pharmacologic targeting of this pathway had therapeutic potential for mitigating AKI.

Identifying RBM47, HCK, CD53, TYROBP, and HAVCR2 as Hub Genes in Advanced Atherosclerotic Plaques by Network-Based Analysis and Validation

Background: Atherosclerotic cardiovascular diseases accounted for a quarter of global deaths. Most of these fatal diseases like coronary atherosclerotic disease (CAD) and stroke occur in the advanced stage of atherosclerosis, during which candidate therapeutic targets have not been fully established. This study aims to identify hub genes and possible regulatory targets involved in treatment of advanced atherosclerotic plaques.

Material/Methods: Microarray dataset GSE43292 and GSE28829, both containing advanced atherosclerotic plaques group and early lesions group, were obtained from the Gene Expression Omnibus database. Weighted gene co-expression network analysis (WGCNA) was conducted to identify advanced plaque-related modules. Module conservation analysis was applied to assess the similarity of advanced plaque-related modules between GSE43292 and GSE28829. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of these modules were performed by Metascape. Differentially expressed genes (DEGs) were mapped into advanced plaque-related modules and module membership values of DEGs in each module were calculated to identify hub genes. Hub genes were further validated for expression in atherosclerotic samples, for distinguishing capacity of CAD and for potential functions in advanced atherosclerosis.

Results: The lightgreen module (MElightgreen) in GSE43292 and the brown module (MEbrown) in GSE28829 were identified as advanced plaque-related modules. Conservation analysis of these two modules showed high similarity. GO and KEGG enrichment analysis revealed that genes in both MElightgreen and MEbrown were enriched in immune cell activation, secretory granules, cytokine activity, and immunoinflammatory signaling. RBM47, HCK, CD53, TYROBP, and HAVCR2 were identified as common hub genes, which were validated to be upregulated in advanced atherosclerotic plaques, to well distinguish CAD patients from non-CAD people and to regulate immune cell function-related mechanisms in advanced atherosclerosis.

Conclusions: We have identified RBM47, HCK, CD53, TYROBP, and HAVCR2 as immune-responsive hub genes related to advanced plaques, which may provide potential intervention targets to treat advanced atherosclerotic plaques.

Vascular Cells Proteome Associated with Bradykinin and Leptin Inflammation and Oxidative Stress Signals

Among the primary contributors to cardiovascular diseases are inflammation and oxidative imbalance within the vessel walls as well as the fibrosis of rat aortic smooth muscle cell (RASMC). Bradykinin (BK) and leptin are inflammatory modulators that are linked to vascular injury. In this study, we employed tandem LC-MS/MS to identify protein signatures that encompass protein abundance in RASMC treated with BK or leptin followed by systems biology analyses to gain insight into the biological pathways and processes linked to vascular remodeling. In the study, 1837 proteins were identified in control untreated RASMC. BK altered the expression of 72 (4%) and 120 (6.5%) proteins, whereas leptin altered the expression of 189 (10.2%) and 127 (6.5%) proteins after 24 and 48 h, respectively, compared to control RASMC. BK increased the protein abundance of leptin receptor, transforming growth factor-β. On the other hand, leptin increased the protein abundance of plasminogen activator inhibitor 1 but decreased the protein abundance of cofilin. BK and leptin induced the expression of inflammatory cytokines such as tumor necrosis factor alpha (TNF-α) and interleukin-1β (IL-1β) and pathway analysis revealed the activation of mitogen-activated protein kinases (MAPKs) and AKT pathways. The proteome profile in response to BK and leptin revealed mechanistic interplay of multiple processes that modulate inflammation and oxidative stress signals in the vasculature.

Value of S100A12 in predicting in-stent restenosis in patients with coronary drug-eluting stent implantation

In-stent restenosis (ISR) after drug-eluting stent (DES) placement has recently emerged as a major concern for cardiologists. Identification of biomarkers to predict ISR may be invaluable for tailored management strategies. The present study aimed to evaluate the prognostic utility of circulating S100 calcium-binding protein A12 (S100A12) for ISR. Out of 2,443 patients with DES-based percutaneous coronary intervention (PCI) and follow-up angiography at ~1 year after DES-based PCI, 258 patients were diagnosed with ISR and 258 patients without ISR were randomly selected as controls. Serum S100A12 levels were determined in the two subsets on admission. The association between ISR and the circulating levels of S100A12 was determined by constructing two multivariate stepwise logistic regression models. In addition, S100A12 was assessed for its ability to predict ISR using receiver operating characteristic (ROC) curve analysis. The serum levels of S100A12 at baseline were significantly elevated in patients in the ISR group compared with those in the non-ISR group (P<0.001). In the multivariate logistic regression analysis, after adjusting for conventional cardiovascular risk factors, laboratory parameters and medication after the procedure, the S100A12 level was revealed to be independently associated with ISR. When a cut-off for serum S100A12 levels of 34.75 ng/ml was used, the ROC curve was able to predict ISR with 72.8% sensitivity and 79.1% specificity, and the area under the ROC curve was 0.796 (95% CI: 0.757 to 0.834, P<0.001). Furthermore, addition of S100A12 to established risk factors significantly improved the predictive power of reference models for ISR. S100A12 may serve as an independent marker to predict ISR in patients undergoing coronary DES implantation.

Deep Phenotyping by Mass Cytometry and Single-Cell RNA-Sequencing Reveals LYN-Regulated Signaling Profiles Underlying Monocyte Subset Heterogeneity and Lifespan

RATIONALE

Monocytes are key effectors of the mononuclear phagocyte system, playing critical roles in regulating tissue homeostasis and coordinating inflammatory reactions, including those involved in chronic inflammatory diseases such as atherosclerosis. Monocytes have traditionally been divided into 2 major subsets termed conventional monocytes and patrolling monocytes (pMo) but recent systems immunology approaches have identified marked heterogeneity within these cells, and much of what regulates monocyte population homeostasis remains unknown. We and others have previously identified LYN tyrosine kinase as a key negative regulator of myeloid cell biology; however, LYN's role in regulating specific monocyte subset homeostasis has not been investigated.

OBJECTIVE

We sought to comprehensively profile monocytes to elucidate the underlying heterogeneity within monocytes and dissect how Lyn deficiency affects monocyte subset composition, signaling, and gene expression. We further tested the biological significance of these findings in a model of atherosclerosis.

METHODS AND RESULTS

Mass cytometric analysis of monocyte subsets and signaling pathway activation patterns in conventional monocytes and pMos revealed distinct baseline signaling profiles and far greater heterogeneity than previously described. Lyn deficiency led to a selective expansion of pMos and alterations in specific signaling pathways within these cells, revealing a critical role for LYN in pMo physiology. LYN's role in regulating pMos was cell-intrinsic and correlated with an increased circulating half-life of Lyn-deficient pMos. Furthermore, single-cell RNA sequencing revealed marked perturbations in the gene expression profiles of Lyn^-/- monocytes with upregulation of genes involved in pMo development, survival, and function. Lyn deficiency also led to a significant increase in aorta-associated pMos and protected Ldlr^-/- mice from high-fat diet-induced atherosclerosis.

CONCLUSIONS

Together our data identify LYN as a key regulator of pMo development and a potential therapeutic target in inflammatory diseases regulated by pMos.

A Promising Candidate: Heparin-Binding Protein Steps onto the Stage of Sepsis Prediction

Sepsis is a systemic inflammatory response syndrome caused by infection. With high morbidity and mortality of this disease, there is a need to find early effective diagnosis and assessment methods to improve the prognosis of patients. Heparin-binding protein (HBP) is a granular protein derived from polynuclear neutrophils. The biosynthetic HBP in neutrophils is rapidly released under the stimulation of bacteria, resulting in increased vascular permeability and edema. It is reasonable to speculate that the HBP in plasma may serve as a novel diagnostic marker for sepsis, bacterial skin infection, acute bacterial meningitis, leptospirosis, protozoan parasites, and even some noncommunicable diseases. It implies that in the detection and diagnosis of sepsis, it will be possible to make relevant diagnosis through this new indicator in the future. In this review, we summarize the typical biological function of HBP and its latest research progress to provide theoretical basis for clinical prediction and diagnosis of sepsis.

A Novel Marker of Inflammation: Azurocidin in Patients with ST Segment Elevation Myocardial Infarction

(1) To investigate the role of azurocidin, an antimicrobial protein, in patients with ST segment elevation myocardial infarction (STEMI). (2) This single-center prospective observational study included patients with STEMI and healthy age- and sex-matched control subjects. Baseline demographic, clinical and biochemical data were compared between the two groups. Azurocidin levels at baseline were determined using an enzyme-linked immunosorbent assay. Multivariate linear regression analysis with enter method was used to test the association between azurocidin and independent variables, such as the thrombolysis in myocardial infarction (TIMI) score, synergy between percutaneous coronary intervention with TAXUS and cardiac surgery score, global registry of acute coronary events score, Killip class, C-reactive protein (CRP), and creatinine kinase-myocardial band (CK-MB). (3) A total of 76 patients with STEMI and 30 healthy control subjects were enrolled in the study. Mean ± SD azurocidin levels were significantly higher in patients compared with healthy controls (18.07 ± 13.99 versus 10.09 ± 5.29 ng/mL, respectively). In a receiver-operating characteristic curve analysis, an azurocidin cut-off level of >11.46 ng/mL had 74% sensitivity and 58% specificity in predicting myocardial infarction. Azurocidin levels had a positive correlation with TIMI score (r = 0.651). In multivariate linear regression analysis, the TIMI score was an independent predictor of the azurocidin level. (4) Azurocidin is an infection marker that may be important in patients with STEMI.

Immune cell subset differentiation and tissue inflammation

Immune cells were traditionally considered as major pro-inflammatory contributors. Recent advances in molecular immunology prove that immune cell lineages are composed of different subsets capable of a vast array of specialized functions. These immune cell subsets share distinct duties in regulating innate and adaptive immune functions and contribute to both immune activation and immune suppression responses in peripheral tissue. Here, we summarized current understanding of the different subsets of major immune cells, including T cells, B cells, dendritic cells, monocytes, and macrophages. We highlighted molecular characterization, frequency, and tissue distribution of these immune cell subsets in human and mice. In addition, we described specific cytokine production, molecular signaling, biological functions, and tissue population changes of these immune cell subsets in both cardiovascular diseases and cancers. Finally, we presented a working model of the differentiation of inflammatory mononuclear cells, their interaction with endothelial cells, and their contribution to tissue inflammation. In summary, this review offers an updated and comprehensive guideline for immune cell development and subset differentiation, including subset characterization, signaling, modulation, and disease associations. We propose that immune cell subset differentiation and its complex interaction within the internal biological milieu compose a “pathophysiological network,” an interactive cross-talking complex, which plays a critical role in the development of inflammatory diseases and cancers.

Human Gingiva-Derived Mesenchymal Stem Cells Modulate Monocytes/Macrophages and Alleviate Atherosclerosis

Atherosclerosis is the major cause of cardiovascular diseases. Current evidences indicate that inflammation is involved in the pathogenesis of atherosclerosis. Human gingiva-derived mesenchymal stem cells (GMSC) have shown anti-inflammatory and immunomodulatory effects on autoimmune and inflammatory diseases. However, the function of GMSC in controlling atherosclerosis is far from clear. The present study is aimed to elucidate the role of GMSC in atherosclerosis, examining the inhibition of GMSC on macrophage foam cell formation, and further determining whether GMSC could affect the polarization and activation of macrophages under different conditions. The results show that infusion of GMSC to AopE^−/− mice significantly reduced the frequency of inflammatory monocytes/macrophages and decreased the plaque size and lipid deposition. Additionally, GMSC treatment markedly inhibited macrophage foam cell formation and reduced inflammatory macrophage activation, converting inflammatory macrophages to anti-inflammatory macrophages in vitro. Thus, our study has revealed a significant role of GMSC on modulating inflammatory monocytes/macrophages and alleviating atherosclerosis.

Activated Mast Cells Mediate Low-Grade Inflammation in Type 2 Diabetes: Interleukin-37 Could Be Beneficial

Mast cells (MCs) promote guest immune responses to parasites and play a critical role in allergic and inflammatory reactions. Once they have been activated, MCs release highly inflammatory compounds that can provoke serious pathologic signs that can lead to death. MCs generate a number of preformed, de novo synthesized compounds and inflammatory cytokine/chemokine synthesis in response to the high-affinity (Kd=10^-10 M) immunoglobulin E receptor triggering. Circulating MC progenitors migrate into arterial intima and develop lesions, mediating inflammation. They are involved in several disorders, including metabolic diseases, such as type 2 diabetes mellitus, in which endothelial cells release several inflammatory compounds during acute and chronic vascular damage. Certain inflammatory cytokines, such as interleukin (IL)-1 and IL-33, not only are produced by MCs but also may activate them. These effects mediate systemic inflammatory responses in metabolic disorders. Proinflammatory cytokines, such as tumor necrosis factor, IL-33 and IL-6, secreted by MCs and other immune cells, contribute to insulin resistance by activating kinases. IL-37 (IL-1 family member 7), one of the latest cytokines discovered, binds the IL-18 receptor alpha (IL-18Rα) chain and suppresses innate and acquired immunity, with a therapeutic effect. It also inhibits cytokine levels, including IL-6, IL-18, IL-33, tumor necrosis factor and IL-1, and may improve insulin production and, therefore, the pathogenesis of diabetes, stroke and cardiovascular health. This describes a new concept of inhibition of and cure for inflammatory diseases. However, the safety, dosage and tolerability of this novel therapeutic agent, IL-37, still remains to be determined.

S100A4 regulates macrophage invasion by distinct myosin-dependent and myosin-independent mechanisms

S100A4, a member of the S100 family of Ca²⁺-binding proteins, is a key regulator of cell migration and invasion. Our previous studies showed that bone marrow–derived macrophages from S100A4^−/− mice exhibit defects in directional motility and chemotaxis in vitro and reduced recruitment to sites of inflammation in vivo. We now show that the loss of S100A4 produces two mechanistically distinct phenotypes with regard to macrophage invasion: a defect in matrix degradation, due to a disruption of podosome rosettes caused by myosin-IIA overassembly, and a myosin-independent increase in microtubule acetylation, which increases podosome rosette stability and is sufficient to inhibit macrophage invasion. Our studies point to S100A4 as a critical regulator of matrix degradation, whose actions converge on the dynamics and degradative functions of podosome rosettes.

The anti-inflammatory vasostatin-2 attenuates atherosclerosis in ApoE-/- mice and inhibits monocyte/macrophage recruitment

We showed previously that reduced level of vasostatin-2 (VS-2) correlates to the presence and severity of coronary artery disease. In this study, we aimed to figure out the role of chromogranin A (CGA) derived VS-2 in the development of atherosclerosis and monocyte/macrophage recruitment. Apolipoprotein E-deficient (ApoE-/-) mice fed a high-fat diet exhibited attenuated lesion size by 65 % and 41 % in En face and aortic root Oil red O staining, MOMA-2 positive area by 64 %, respectively, in VS-2 treatment group compared with PBS group. Proinflammatory cytokines tumour necrosis factor-alpha (TNF-α), monocyte chemoattractant protein-1 (MCP-1) and vascular cell adhesion molecule-1 (VCAM-1) were all remarkably reduced in aortic tissues after VS-2 treatment. Mechanistically, in adhesion assay using intravital microscopy in vivo, VS-2 suppressed the number of leukocytes adhering to the wall of apoE-/- mice mesenteric arteries. In chemotactic assay, flow cytometry analysis of peritoneal lavage exudate from C57BL/6 mice showed VS-2 significantly decreased the recruiment number of inflammatory monocytes/macrophages in a thioglycollate-induced peritonitis model. Furthermore, fewer fluorescent latex beads labelled Ly-6Chi monocytes accumulated in aortic sinus lesions of apoE-/- mice after VS-2 treatment. In addition, according to the microarray of human monocyte/macrophage, we found VS-2 stimulation caused a dose-dependent decrease of Rac1 expression and inactivation of Pak1 in mice primary monocytes as well as THP-1 cells and inhibited MCP-1/CCL-5 induced transmigration in vitro. In conclusion, the Chromogranin A-derived VS-2 attenuates atherosclerosis in apoE-/- mice and, in addition to its anti-inflammatory property, also acts as an inhibitor in monocyte/macrophage recruitment.

Supplementary Material to this article is available online at www.thrombosis-online.com.

Inhibition of Hematopoietic Cell Kinase Activity Suppresses Myeloid Cell-Mediated Colon Cancer Progression

Aberrant activation of the SRC family kinase hematopoietic cell kinase (HCK) triggers hematological malignancies as a tumor cell-intrinsic oncogene. Here we find that high HCK levels correlate with reduced survival of colorectal cancer patients. Likewise, increased Hck activity in mice promotes the growth of endogenous colonic malignancies and of human colorectal cancer cell xenografts. Furthermore, tumor-associated macrophages of the corresponding tumors show a pronounced alternatively activated endotype, which occurs independently of mature lymphocytes or of Stat6-dependent Th2 cytokine signaling. Accordingly, pharmacological inhibition or genetic reduction of Hck activity suppresses alternative activation of tumor-associated macrophages and the growth of colon cancer xenografts. Thus, Hck may serve as a promising therapeutic target for solid malignancies.