Immune-related potential biomarkers and therapeutic targets in coronary artery disease

Platelet-derived sTLT-1 is associated with platelet-mediated inflammation in coronary artery disease patients

The development of coronary artery disease (CAD) depends heavily on platelet activation, and inflammation plays a major role in all stages of atherosclerosis. Platelet-specific soluble triggering receptor expressed on myeloid cells like transcript 1 (sTLT-1) facilitate clot formation and have been linked to chronic inflammation. In this study, we explored the role of platelet-derived sTLT-1 in platelet-mediated inflammation in CAD patients. Plasma levels of sTLT-1 were measured using enzyme-linked immunosorbent assay in CAD patients (n = 163) and healthy controls (n = 99). Correlation analysis was performed to determine the circulatory sTLT-1 levels with platelet activation markers, immune cells, and inflammatory cytokines/chemokines. Increased plasma sTLT-1 levels were observed in CAD patients compared with those in healthy controls (p < 0.0001). A positive correlation was observed between sTLT-1 and platelet activation markers (P-selectin, PAC-1), CD14++ CD16- cells (classical monocytes), Natural killer T (NKT) cells, and platelet-immune cell aggregates with monocytes, neutrophils, dendritic cells, CD11c+ cells, and NKT cells. In contrast, a significant negative correlation was observed with CD8 cells. Furthermore, a significant positive correlation was observed between sTLT-1 and inflammatory markers (TNF-α, IL-1β, IL-2, IL-6, IL-12p70, IL-18, CXCL-12, and CCL-11). Logistic regression analysis identified sTLT-1 and triglycerides as predictors of CAD. Receiver operating characteristic curve (ROC) analysis showed that sTLT-1 had a higher sensitivity and specificity for predicting CAD. Our findings suggest that platelet activation induces the release of sTLT-1 into the circulation in CAD patients, which aggregates with immune cells and enhances inflammatory responses.

The Impact of the Neutrophil-to-Lymphocyte Ratio on In-Hospital Outcomes in Patients With Acute ST-Segment Elevation Myocardial Infarction

Introduction The neutrophil-to-lymphocyte ratio (NLR) is a significant predictor of cardiovascular diseases, influencing their progression and prognosis. The exact role of the NLR in acute ST-segment elevation myocardial infarction (STEMI) is unclear. We investigated the possible association between peak NLR values within the first three days after STEMI onset and in-hospital outcomes in patients undergoing primary percutaneous coronary intervention (PCI). Methods This retrospective study included 641 patients who were diagnosed with acute STEMI and treated with primary PCI for 18 months at Dr. Siyami Ersek Hospital. The NLR was calculated using the maximum values obtained during the first three days after admission. The patients were divided into quartiles according to their NLR values for further analysis of potential complications during and after hospitalization, up to a follow-up period of three months. Results Significant differences were found in factors such as age, body mass index (BMI), and length of hospital stay among these groups. Specifically, we found that in-hospital mortality rates were significantly higher in the Q4 group, and there were variations in target vessel revascularization (TVR) rates, major adverse cardiac events (MACE) rates, and other clinical outcomes. Some parameters, such as reinfarction rates and certain procedural outcomes, did not show significant differences among the groups. However, despite the differences, most of the patients achieved successful outcomes after PCI, with the best results in the low NLR group and the worst results in the high NLR group. Conclusion Higher NLR values were associated with a higher risk of unfavorable outcomes during hospitalization.

Exploring the pathogenesis and key genes associated of acute myocardial infarction complicated with Alzheimer's disease

Despite mounting evidence linking Acute Myocardial Infarction (AMI) to Alzheimer's disease (AD), the shared mechanism of these two conditions' occurrence remains unclear. This research aims to delve deeper into the molecular process of the occurrence of the two diseases. We retrieved the gene expression profiles of AD (GSE5281) and AMI (GSE66360) from the Gene Expression Omnibus database. Then, a total of 22 common differentially expressed genes (DEGs) including one downregulated gene and 21 upregulated genes were chosen for further analysis. Following the discovery of the common DEGs between AMI and AD, we performed protein-protein interaction analysis and hub gene identification analysis. Next, ten important hub genes were identified. Additionally, the key genes were identified by the least absolute shrinkage and selection operator and support vector machine-recursive feature elimination and multivariable logistic regression analysis. The BCL6 was identified to be the most connected with AMI and AD. Finally, the BCL6 gene was validated in the GSE40680 (AMI) and GSE122063 (AD) datasets. Our research indicates that AMI and AD share a comparable pathophysiology. The Hub genes, especially BCL6, were essential in developing AMI and AD. In addition, these hub genes and shared pathways can offer fresh perspectives for additional mechanism investigation.

Use of Machine Learning for the Identification and Validation of Immunogenic Cell Death Biomarkers and Immunophenotypes in Coronary Artery Disease

Objective

Immunogenic cell death (ICD) is part of the immune system's response to coronary artery disease (CAD). In this study, we bioinformatically evaluated the diagnostic and therapeutic utility of immunogenic cell death-related genes (IRGs) and their relationship with immune infiltration features in CAD.

Methods

We acquired the CAD-related datasets GSE12288, GSE71226, and GSE120521 from the Gene Expression Omnibus (GEO) database and the IRGs from the GeneCards database. After identifying the immune cell death-related differentially expressed genes (IRDEGs), we developed a risk model and detected immune subtypes in CAD. IRDEGs were identified using least absolute shrinkage and selection operator (LASSO) analysis. Using a nomogram, we confirmed that both the LASSO model and ICD signature genes had good diagnostic performance.

Results

There was a high degree of coincidence and immune representativeness between two CAD groups based on characteristic genes and hub genes. Hub genes were associated with the interaction of neuroactive ligands with receptors and cell adhesion receptors. The two groups differed in terms of adipogenesis, allograft rejection, and apoptosis, as well as the ICD signature and hub gene expression levels. The two CAD-ICD subtypes differed in terms of immune infiltration.

Conclusion

Quantitative real-time PCR (qRT-PCR) correlated CAD with the expression of OAS3, ITGAV, and PIBF1. The ICD signature genes are candidate biomarkers and reference standards for immune grouping in CAD and can be beneficial in precise immune-targeted therapy.

Identification and characterization of interferon-γ signaling-based personalized heterogeneity and therapeutic strategies in patients with pancreatic cancer

Background

Interferon-γ (IFN-γ) is a key cytokine with diverse biological functions, including antiviral defense, antitumor activity, immune regulation, and modulation of cellular processes. Nonetheless, its role in pancreatic cancer (PC) therapy remains debated. Therefore, it is worthwhile to explore the role of Interferon-γ related genes (IFN-γGs) in the progression of PC development.

Methodology

Transcriptomic data from 930 PC were sourced from TCGA, GEO, ICGC, and ArrayExpress, and 93 IFN-γGs were obtained from the MSigDB. We researched the characteristics of IFN-γGs in pan-cancer. Subsequently, the cohort of 930 PC was stratified into two distinct subgroups using the NMF algorithm. We then examined disparities in the activation of cancer-associated pathways within these subpopulations through GSVA analysis. We scrutinized immune infiltration in both subsets and probed classical molecular target drug sensitivity variations. Finally, we devised and validated a novel IFN-γ related prediction model using LASSO and Cox regression analyses. Furthermore, we conducted RT-qPCR and immunohistochemistry assays to validate the expression of seven target genes included in the prediction model.

Results

We demonstrated the CNV, SNV, methylation, expression levels, and prognostic characteristics of IFN-γGs in pan-cancers. Notably, Cluster 2 demonstrated superior prognostic outcomes and heightened immune cell infiltration compared to Clusters 1. We also assessed the IC50 values of classical molecular targeted drugs to establish links between IFN-γGs expression levels and drug responsiveness. Additionally, by applying our prediction model, we segregated PC patients into high-risk and low-risk groups, identifying potential benefits of cisplatin, docetaxel, pazopanib, midostaurin, epothilone.B, thapsigargin, bryostatin.1, and AICAR for high-risk PC patients, and metformin, roscovitine, salubrinal, and cyclopamine for those in the low-risk group. The expression levels of these model genes were further verified through HPA website data and qRT-PCR assays in PC cell lines and tissues.

Conclusion

This study unveils IFN-γGs related molecular subsets in pancreatic cancer for the first time, shedding light on the pivotal role of IFN-γGs in the progression of PC. Furthermore, we establish an IFN-γGs related prognostic model for predicting the survival of PC, offering a theoretical foundation for exploring the precise mechanisms of IFN-γGs in PC.

Systematic Review on the Link between Sleep Bruxism and Systemic Chronic Inflammation

Sleep bruxism (SB) is a sleep-related behavior characterized as rhythmic (phasic) or non-rhythmic (tonic) masticatory muscle activity. SB is a common sleep behavior with a predominantly central origin. The aim of this systematic review was to evaluate the relationship between inflammatory status and SB according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 (PRISMA 2020). The research was registered at PROSPERO (CRD42023395985). We performed a systematic literature analysis using five different databases. Furthermore, the backward snowballing technique was applied to identify additional papers. Initially, 28 papers were screened from the database search, and 162 papers were revealed in the backward snowballing process. Eventually, five articles were included. Data concerning the inflammatory status of patients experiencing SB were investigated and summarized. Due to the heterogeneity of the compared studies, only a qualitative comparison and narrative summary were performed. The results suggest that SB could be associated with systemic inflammation. In fact, this systematic review revealed that there are no papers conclusively showing that the inflammatory status in bruxers is comparable to non-bruxers. However, each of the examined studies utilized different methods of assessing systemic inflammation, which makes the results dubious.