Endothelial inflammation is a multifaceted physiological process that plays a pivotal role in the pathogenesis and progression of diverse diseases, encompassing but not limited to acute lung infections like COVID-19, coronary artery disease, stroke, sepsis, metabolic syndrome, certain malignancies, and even psychiatric disorders such as depression. This inflammatory response is characterized by augmented expression of adhesion molecules and secretion of pro-inflammatory cytokines. In this study, we discovered that saponins from Allium macrostemon bulbs (SAMB) effectively inhibited inflammation in human umbilical vein endothelial cells induced by the exogenous inflammatory mediator lipopolysaccharide or the endogenous inflammatory mediator tumor necrosis factor-α, as evidenced by a significant reduction in the expression of pro-inflammatory factors and vascular cell adhesion molecule-1 (VCAM-1) with decreased monocyte adhesion. By employing the NF-κB inhibitor BAY-117082, we demonstrated that the inhibitory effect of SAMB on VCAM-1 expression may be attributed to the NF-κB pathway’s inactivation, as characterized by the suppressed IκBα degradation and NF-κB p65 phosphorylation. Subsequently, we employed a murine model of lipopolysaccharide-induced septic acute lung injury to substantiate the potential of SAMB in ameliorating endothelial inflammation and acute lung injury in vivo. These findings provide novel insight into potential preventive and therapeutic strategies for the clinical management of diseases associated with endothelial inflammation.

Abdominal aortic aneurysm (AAA) is a degenerative disease characterized by local abnormal dilation of the aorta accompanied by vascular smooth muscle cell (VSMC) dysfunction and chronic inflammation. VSMC dedifferentiation, transdifferentiation, and increased expression of matrix metalloproteinases (MMPs) are essential causes of AAA formation. Previous studies from us and others have shown that Anemoside B4 (AB4), a saponin from Pulsatilla chinensis, has anti-inflammatory, anti-tumor, and regulatory effects on VSMC dedifferentiation. The current study aimed to investigate whether AB4 inhibits AAA development and its underlying mechanisms. By using an Ang II induced AAA model in vivo and cholesterol loading mediated VSMC to macrophage transdifferentiation model in vitro, our study demonstrated that AB4 could attenuate AAA pathogenesis, prevent VSMC dedifferentiation and transdifferentiation to macrophage-like cells, decrease vascular inflammation, and suppress MMP expression and activity. Furthermore, KLF4 overexpression attenuated the effects of AB4 on VSMC to macrophage-like cell transition and VSMC inflammation in vitro. In conclusion, AB4 protects against AAA formation in mice by inhibiting KLF4 mediated VSMC transdifferentiation and inflammation. Our study provides the first proof of concept of using AB4 for AAA management.

Atherosclerosis (AS) is a lipid-induced, chronic inflammatory, autoimmune disease affecting multiple arteries. Although much effort has been put into AS research in the past decades, it is still the leading cause of death worldwide. The complex genetic network regulation underlying the pathogenesis of AS still needs further investigation to provide effective targeted therapy for AS. We performed a bioinformatic microarray data analysis at different atherosclerotic plaque stages from the Gene Expression Omnibus database with accession numbers GSE43292 and GSE28829. Using gene set enrichment analysis, we further confirmed the immune-related pathways that play an important role in the development of AS. We are reporting, for the first time, that the metabolism of the three branched-chain amino acids (BCAAs; leucine, isoleucine, and valine) and short-chain fatty acids (SCFA; propanoate, and butanoate) are involved in the progression of AS using microarray data of atherosclerotic plaque tissue. Immune and muscle system-related pathways were further confirmed as highly regulated pathways during the development of AS using gene expression pattern analysis. Furthermore, we also identified four modules mainly involved in histone modification, immune-related processes, macroautophagy, and B cell activation with modular differential connectivity in the dataset of GSE43292, and three modules related to immune-related processes, B cell activation, and nuclear division in the dataset of GSE28829 also display modular differential connectivity based on the weighted gene co-expression network analysis. Finally, we identified eight key genes related to the pathways of immune and muscle system function as potential therapeutic biomarkers to distinguish patients with early or advanced stages in AS, and two of the eight genes were validated using the gene expression dataset from gene-deficient mice. The results of the current study will improve our understanding of the molecular mechanisms in the progression of AS. The key genes and pathways identified could be potential biomarkers or new drug targets for AS management.

Background: Triple-negative breast cancer (TNBC) is a heterogeneous disease with a worse prognosis. Despite ongoing efforts, existing therapeutic approaches show limited success in improving early recurrence and survival outcomes for TNBC patients. Therefore, there is an urgent need to discover novel and targeted therapeutic strategies, particularly those focusing on the immune infiltrate in TNBC, to enhance diagnosis and prognosis for affected individuals.Methods: The gene co-expression network and gene ontology analyses were used to identify the differential modules and their functions based on the GEO dataset of GSE76275. The Weighted Gene Co-Expression Network Analysis (WGCNA) was used to describe the correlation patterns among genes across multiple samples. Subsequently, we identified key genes in TNBC by assessing genes with an absolute correlation coefficient greater than 0.80 within the eigengene of the enriched module that were significantly associated with breast cancer subtypes. The diagnostic potential of these key genes was evaluated using receiver operating characteristic (ROC) curve analysis with three-fold cross-validation. Furthermore, to gain insights into the prognostic implications of these key genes, we performed relapse-free survival (RFS) analysis using the Kaplan-Meier plotter online tool. CIBERSORT analysis was used to characterize the composition of immune cells within complex tissues based on gene expression data, typically derived from bulk RNA sequencing or microarray datasets. Therefore, we explored the immune microenvironment differences between TNBC and non-TNBC by leveraging the CIBERSORT algorithm. This enabled us to estimate the immune cell compositions in the breast cancer tissue of the two subtypes. Lastly, we identified key transcription factors involved in macrophage infiltration and polarization in breast cancer using transcription factor enrichment analysis integrated with orthogonal omics.Results: The gene co-expression network and gene ontology analyses revealed 19 modules identified using the dataset GSE76275. Of these, modules 5, 11, and 12 showed significant differences between in breast cancer tissue between TNBC and non-TNBC. Notably, module 11 showed significant enrichment in the WNT signaling pathway, while module 12 demonstrated enrichment in lipid/fatty acid metabolism pathways. Subsequently, we identified SHC4/KCNK5 and ABCC11/ABCA12 as key genes in module 11 and module 12, respectively. These key genes proved to be crucial in accurately distinguishing between TNBC and non-TNBC, as evidenced by the promising average AUC value of 0.963 obtained from the logistic regression model based on their combinations. Furthermore, we found compelling evidence indicating the prognostic significance of three key genes, KCNK5, ABCC11, and ABCA12, in TNBC. Finally, we also identified the immune cell compositions in breast cancer tissue between TNBC and non-TNBC. Our findings revealed a notable increase in M0 and M1 macrophages in TNBC compared to non-TNBC, while M2 macrophages exhibited a significant reduction in TNBC. Particularly intriguing discovery emerged with respect to the transcription factor FOXM1, which demonstrated a significant regulatory role in genes positively correlated with the proportions of M0 and M1 macrophages, while displaying a negative correlation with the proportion of M2 macrophages in breast cancer tissue.Conclusion: Our research provides new insight into the biomarkers and immune infiltration of TNBC, which could be useful for clinical diagnosis of TNBC.