RPS4Y1 Promotes High Glucose-Induced Endothelial Cell Apoptosis and Inflammation by Activation of the p38 MAPK Signaling

Construction of lung adenocarcinoma subtype and prognosis model based on fatty acid metabolism-related genes

OBJECTIVE

To explore the role of genes related to fatty acid metabolism in lung adenocarcinoma classification and prognosis.

METHODS

Transcriptome and clinical data from the TCGA database and GEO database were collected, the expression of prognostic fatty acid metabolism-related genes in LUAD patients was analyzed, and key genes related to both fatty acid metabolism and subtype were identified. These key genes were further filtered via the LASSO regression method, and the retained genes were used to construct a risk-scoring model. The biological function of RPS4Y1 was verified by cell viability, colony formation, migration, and flow cytometry assays. Finally, immune infiltration and drug sensitivity were analyzed in the high- and low-risk groups.

RESULTS

31 key FAMGs associated with prognosis were identified in LUAD patients. LUAD cases were divided into 3 subtypes on the basis of the expression of these genes. The DEGs between the different subtypes were associated mainly with amino acid metabolic pathways. In addition, among the 46 DEGs between subtypes, 5 key FAMGs (SCGB3 A2, PGC, ADH7, RPS4Y1, and KRT6 A) were identified as the best prognostic markers via LASSO regression to establish a risk scoring model. Patients with low risk scores had a better prognosis and a greater degree of immune cell infiltration than those with high risk scores. RPS4Y1 is highly expressed in LUAD, and its knockdown significantly inhibits the growth of tumor cells. Moreover, we also analyzed drugs likely to be effective for the high- and low-risk groups.

CONCLUSION

FAMGs play important roles in LUAD, and the key genes identified may be new targets for LUAD treatment.

The role of hydrogen sulfide in the regulation of necroptosis across various pathological processes

Necroptosis is a programmed cell death form executed by receptor-interacting protein kinase (RIPK) 1, RIPK3 and mixed lineage kinase domain-like protein (MLKL), which assemble into an oligomer called necrosome. Accumulating evidence reveals that necroptosis participates in many types of pathological processes. Hence, clarifying the mechanism of necroptosis in pathological processes is particularly important for the prevention and treatment of various diseases. For over 300 years, hydrogen sulfide (H2S) has been widely known in the scientific community as a toxic and foul-smelling gas. However, after discovering the important physiological and pathological functions of H2S, human understanding of this small molecule changed, believing that H2S is the third gas signaling molecule after carbon monoxide (CO) and nitric oxide (NO). H2S plays an important role in various diseases, but the related mechanisms are not yet fully understood. In recent years, more and more studies have shown that H2S regulation of necroptosis is involved in various pathological processes. Herein, we focus on the recent progress on the role of H2S regulation of necroptosis in different pathological processes and profoundly analyze the related mechanisms.

Importance of STAT3 signaling in preeclampsia (Review)

Placentation is a key process that is tightly regulated that ensures the normal placenta and fetal development. Preeclampsia (PE) is a hypertensive pregnancy‑associated disorder characterized by increased oxidative stress and inflammation. STAT3 signaling plays a key role in modulating important processes such as cell proliferation, differentiation, invasion and apoptosis. The present review aimed to analyse the role of STAT3 signaling in PE pregnancies, discuss the main natural and synthetic compounds involved in modulation of this signaling both in vivo and in vitro and summarize the main cellular modulators of this signaling to identify possible therapeutic targets and treatments to improve the outcome of PE pregnancies.

Discovery of KDM5D as a novel biomarker for traumatic brain injury identified through bioinformatics analysis

Background and aim

Traumatic brain injury (TBI) poses a significant burden on the global economy due to its poor treatment and prognosis. Current TBI markers do not comprehensively reflect the disease status. Therefore, identifying more meaningful biomarkers is beneficial for improving the prognosis and clinical treatment of TBI patients.

Methods

The gene expression profile of TBI was obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were subjected to enrichment analysis, and key potential genes were identified through the protein-protein interaction network and cytoHubba modules. ROC curves were used to construct diagnostic models for hub genes. Immunofluorescence experiments were conducted to detect the expression of candidate biomarkers in TBI rat models. Finally, we investigated the expression of TBI biomarkers in normal human organs and pan-cancer tumor tissues, and evaluated their correlation with immune infiltration in different tumors.

Results

A total of 44 DEGs were identified across four brain regions of TBI patients. Enrichment analysis revealed that these genes were primarily involved in intracellular and cell signal transduction pathways. Furthermore, three hub genes- RPS4Y1, KDM5D and NLGN4Y-were identified through different module analysis. The ROC curve diagnostic model also confirmed that these genes also have high diagnostic value in serum. Subsequently, the presence of Kdm5d was detected in the brain tissue of TBI rats through immunofluorescence experiments. Compared to normal rats, Kdm5d expression increased in the cortical area of ​​TBI rats, with no significant change in the hippocampus area, aligning with observations in TBI patients. Immune infiltration analysis demonstrated changes in immune cell subsets in HIP and PCx, revealing that plasma cells and CD8 T cells were lowly expressed in TBI (HIP) and while neutrophils was under-expressed in TBI (PCx). Pan-cancer analysis indicated that KDM5D was significantly up-regulated in 23 cancers, down-regulated in 3 cancers, and significantly associated with immune infiltration in 10 cancers.

Conclusion

Based on the results of bioinformatics analysis and animal experiments, KDM5D serves as a potential biomarker for the diagnosis and prognosis of TBI. Additionally, research on KDM5D may develop into new serum markers, providing new indicators for further clinical liquid biopsy and aiding in the prevention of both TBI and tumors to a certain extent.

Ribosomal protein paralogues in ribosome specialization

Ribosomes are macromolecular complexes responsible for protein synthesis, comprising ribosomal proteins (RPs) and ribosomal RNA. While most RPs are present as single copies in higher eukaryotes, a handful of them have paralogues that emerged through duplication events. However, it is still unclear why a small subset of RP paralogues were preserved through evolution, and whether they can endow ribosomes with specialized functions. In this review, we focus on RP paralogue pairs present in humans, providing an overview of the most recent findings on RP paralogue functions and their roles in ribosome specialization.This article is part of the discussion meeting issue 'Ribosome diversity and its impact on protein synthesis, development and disease'.

Uncovering potential molecular markers and pathological mechanisms of Parkinson's disease and myocardial infarction based on bioinformatics analysis

BACKGROUND

The direct association between Parkinson's disease (PD) and Myocardial infarction (MI) has been the subject of relatively limited research.

OBJECTIVE

The purpose of this study was to identify the genes most associated with PD and MI to explore their common pathogenesis.

METHODS

The gene expression profiles of PD and MI were downloaded from GEO database. Differential expression analysis was performed to identify the common differential expression genes (DEGs) of PD and MI, followed by functional annotation. Subsequently, protein-protein interaction network were constructed, and hub DEGs were identified based on CytoHubba plugin and LASSO regression analysis. To explore the potential molecular mechanism of hub DEGs, GSEA analysis, immune correlation analysis, drug prediction and molecular docking were performed, and transcription factors (TF) and lncRNA-miRNA-mRNA (ceRNA) regulatory networks were constructed.

RESULTS

A total of 48 DEGs with the same expression trend were identified in the MI vs. normal control (NC) and PD vs. NC groups. Functional annotation results showed that the common DEGs were significantly enriched in immune and inflammation-related pathways. RPS4Y1 and UTY were the most relevant hub DEGs for PD and MI, and may be involved in the HALLMARK_MYC_TARGETS_V1 and HALLMARK_PROTEIN_SECRETION pathways. TP63 was a common TF of RPS4Y1 and UTY. The PVT1/KCNQ1OT1-hsa-miR-31-5p-RPS4Y1 and KCNQ1OT1-hsa-let-7a-5p/hsa-miR-19b-3p-UTY axes may play an important role in regulating PD and MI. CYCLOHEXIMIDE and ATALAREN may be potential drugs for the treatment of PD and MI comorbidity. In addition, PD and MI exhibit different patterns of immune cell infiltration and immune function status, which may be related to the specific pathological processes of the disease.

CONCLUSIONS

This study revealed for the first time that RPS4Y1 and UTY may be common biomarkers of PD and MI and may be potential therapeutic targets. This study provides new perspective on the common molecular mechanisms between PD and MI.

Construction of novel 10 signatures in diabetic retinopathy construction of model based on WGCNA: Mechanism of action of RPL3 and MRPL16 protein

Diabetic retinopathy is a common microvascular complication in diabetic patients, which can lead to blindness in severe cases. At present, although a variety of treatment methods are available, the pathological mechanism has not been fully elucidated. As ribosomal proteins, RPL3 and MRPL16 play important roles in cell metabolism and protein synthesis, but their specific roles in diabetic retinopathy are unclear. This study aims to construct new features of diabetic retinopathy by WGCNA method, and reveal the mechanism of RPL3 and MRPL16 protein in diabetic retinopathy, so as to provide new ideas for the early diagnosis and treatment of diabetic retinopathy. The study collected retinal tissue samples from patients with diabetic retinopathy and used high-throughput sequencing techniques to obtain gene expression data. Gene expression data were analyzed by WGCNA method to construct the characteristic module of diabetic retinopathy. On this basis, the genes significantly associated with diabetic retinopathy were screened out, and the mechanism of action of RPL3 and MRPL16 proteins in diabetic retinopathy was studied through bioinformatics analysis and experimental verification. Through WGCNA analysis, we successfully constructed a characteristic module of diabetic retinopathy and screened out genes significantly associated with the disease. Further studies have shown that RPL3 and MRPL16 proteins are up-regulated in diabetic retinopathy and play key roles in cell metabolism and protein synthesis. Through in vitro experiments and animal model verification, we found that the abnormal expression of RPL3 and MRPL16 proteins is closely related to the pathological process of diabetic retinopathy.

Study of the Synchronization and Transmission of Intracellular Signaling Oscillations in Cells Using Bispectral Analysis

The oscillation synchronization analysis in biological systems will expand our knowledge about the response of living systems to changes in environmental conditions. This knowledge can be used in medicine (diagnosis, therapy, monitoring) and agriculture (increasing productivity, resistance to adverse effects). Currently, the search is underway for an informative, accurate and sensitive method for analyzing the synchronization of oscillatory processes in cell biology. It is especially pronounced in analyzing the concentration oscillations of intracellular signaling molecules in electrically nonexcitable cells. The bispectral analysis method could be applied to assess the characteristics of synchronized oscillations of intracellular mediators. We chose endothelial cells from mouse microvessels as model cells. Concentrations of well-studied calcium and nitric oxide (NO) were selected for study in control conditions and well-described stress: heating to 40 °C and hyperglycemia. The bispectral analysis allows us to accurately evaluate the proportion of synchronized cells, their synchronization degree, and the amplitude and frequency of synchronized calcium and NO oscillations. Heating to 40 °C increased cell synchronization for calcium but decreased for NO oscillations. Hyperglycemia abolished this effect. Heating to 40 °C changed the frequencies and increased the amplitudes of synchronized oscillations of calcium concentration and the NO synthesis rate. The first part of this paper describes the principles of the bispectral analysis method and equations and modifications of the method we propose. In the second part of this paper, specific examples of the application of bispectral analysis to assess the synchronization of living cells in vitro are presented. The discussion compares the capabilities of bispectral analysis with other analytical methods in this field.

Single-cell analysis of CD4+ tissue residency memory cells (TRMs) in adult atopic dermatitis: A new potential mechanism

The pathophysiology of atopic dermatitis (AD) is complex. CD4+ T cells play an essential role in the development of lesions in AD. However, the underlying mechanism remains unclear. In the present study, we investigated the differentially expressed genes (DEGs) between adult AD lesioned and non-lesioned skin using two datasets from the Gene Expression Omnibus (GEO) database. 62 DEGs were shown to be related to cytokine response. Compared to non-lesioned skin, lesioned skin showed immune infiltration with increased numbers of activated natural killer (NK) cells and CD4+ T memory cells (p < 0.01). We then identified 13 hub genes with a strong association with CD4+ T cells using weighted correlation network analysis. Single-cell analysis of AD detected a novel CD4+ T subcluster, CD4+ tissue residency memory cells (TRMs), which were verified through immunohistochemistry (IHC) to be increased in the dermal area of AD. The significant relationship between CD4+ TRM and AD was assessed through further analyses. FOXO1 and SBNO2, two of the 13 hub genes, were characteristically expressed in the CD4+ TRM, but down-regulated in IFN-γ/TNF-α-induced HaCaT cells, as shown using quantitative polymerase chain reaction (qPCR). Moreover, SBNO2 expression was associated with increased Th1 infiltration in AD (p < 0.05). In addition, genes filtered using Mendelian randomization were positively correlated with CD4+ TRM and were highly expressed in IFN-γ/TNF-α-induced HaCaT cells, as determined using qPCR and western blotting. Collectively, our results revealed that the newly identified CD4+ TRM may be involved in the pathogenesis of adult AD.

Single-cell transcriptomic analysis reveals transcript enrichment in oxidative phosphorylation, fluid sheer stress, and inflammatory pathways in obesity-related glomerulopathy

Obesity-related glomerulopathy (ORG) is an independent risk factor for chronic kidney disease and even progression to end-stage renal disease. Efforts have been undertaken to elucidate the mechanisms underlying the development of ORG and substantial advances have been made in the treatment of ORG, but relatively little is known about cell-specific changes in gene expression. To define the transcriptomic landscape at single-cell resolution, we analyzed kidney samples from four patients with ORG and three obese control subjects without kidney disease using single-cell RNA sequencing. We report for the first time that immune cells, including T cells and B cells, are decreased in ORG patients. Further analysis indicated that SPP1 was significantly up-regulated in T cells and B cells. This gene is related to inflammation and cell proliferation. Analysis of differential gene expression in glomerular cells (endothelial cells, mesangial cells, and podocytes) showed that these cell types were mainly enriched in genes related to oxidative phosphorylation, cell adhesion, thermogenesis, and inflammatory pathways (PI3K-Akt signaling, MAPK signaling). Furthermore, we found that the podocytes of ORG patients were enriched in genes related to the fluid shear stress pathway. Moreover, an evaluation of cell-cell communications revealed that there were interactions between glomerular parietal epithelial cells and other cells in ORG patients, with major interactions between parietal epithelial cells and podocytes. Altogether, our identification of molecular events, cell types, and differentially expressed genes may facilitate the development of new preventive or therapeutic approaches for ORG.

scRNA+TCR+BCR-seq revealed the proportions and gene expression patterns of dual receptor T and B lymphocytes in NPC and NLH

While the relationship between single receptor lymphocytes and cancer has been deeply researched, the origin and biological roles of dual receptor lymphocytes in tumor microenvironment (TME) remain largely unknown. And since nasopharyngeal carcinoma (NPC) is a type of cancer closely associated with immune infiltration, studying the TME of NPC holds particular significance. Utilizing single-cell RNA sequencing combined with T cell receptor (TCR) and B cell receptor (BCR) sequencing (scRNA + TCR + BCR-seq), we analyzed data from 7 patients with NPC and 3 patients with nasopharyngeal lymphatic hyperplasia (NLH). In our research, it was firstly found that the presence of dual receptor lymphocytes in both the TME of NPC and the inflammatory environment of NLH. We also confirmed their clonal expansion, suggesting their potential involvement in the immune response. Subsequently, we further discovered the lineage and the pairing characteristics. It was found that the dual receptor lymphocytes in NPC and NLH mainly originate from memory cells, and the predominant pairing type for dual TCR was β+α1+α2 and dual BCR was heavy+κ+λ. By further analyzing their gene expression, we compared the function of dual receptor cells with single receptor cells in the context of both NPC and NLH. This groundbreaking research has enhanced our comprehension of the features of dual-receptor cells and has contributed to a better understanding of the TME in NPC. By comparing with NLH, it illuminates part of the alterations in the process of malignant transformation in NPC. These findings present the potential to acquire improved diagnostic markers and treatment modalities.

scGIR: deciphering cellular heterogeneity via gene ranking in single-cell weighted gene correlation networks

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for investigating cellular heterogeneity through high-throughput analysis of individual cells. Nevertheless, challenges arise from prevalent sequencing dropout events and noise effects, impacting subsequent analyses. Here, we introduce a novel algorithm, Single-cell Gene Importance Ranking (scGIR), which utilizes a single-cell gene correlation network to evaluate gene importance. The algorithm transforms single-cell sequencing data into a robust gene correlation network through statistical independence, with correlation edges weighted by gene expression levels. We then constructed a random walk model on the resulting weighted gene correlation network to rank the importance of genes. Our analysis of gene importance using PageRank algorithm across nine authentic scRNA-seq datasets indicates that scGIR can effectively surmount technical noise, enabling the identification of cell types and inference of developmental trajectories. We demonstrated that the edges of gene correlation, weighted by expression, play a critical role in enhancing the algorithm's performance. Our findings emphasize that scGIR outperforms in enhancing the clustering of cell subtypes, reverse identifying differentially expressed marker genes, and uncovering genes with potential differential importance. Overall, we proposed a promising method capable of extracting more information from single-cell RNA sequencing datasets, potentially shedding new lights on cellular processes and disease mechanisms.

Single-cell RNA sequencing shows the immune cell landscape in the kidneys of patients with idiopathic membranous nephropathy

Idiopathic membranous nephropathy (IMN) is a leading pathological type of the adult primary nephrotic syndrome. Some patients develop end-stage renal disease due to poor response to treatment with steroid and immunosuppressive agents. In order to explore the molecular mechanism of IMN, we collected renal tissue samples from IMN patients and healthy controls and performed analysis by single-cell RNA sequencing (scRNA-seq). A total of 11 kidney cell clusters were identified, including multiple myeloid cell clusters, NK/T cell clusters, and B cell clusters. Most kidney parenchymal and immune cells were enriched in the regulation of immune response, inflammation, fibrosis and endoplasmic reticulum stress. The macrophage population in the IMN group showed a highly activated profile with up-regulated genes related to chemotaxis, inflammation, phagocytosis and fibrosis. CD8+ T cells continued to be cytotoxic in IMN; however, a transition to "inflammageing" GZMK+ CD8+ T cells was observed. The proportion of activated B cells in renal tissues of IMN patients was much higher than that of normal controls, indicating that B cells in IMN might be activated by constant antigenic stimulation. Moreover, the cell-cell interaction analysis revealed the potential communication between renal glomerular cells and immune cells in IMN. Overall, scRNA-seq was applied to IMN to unravel the characteristics of immune cells and elucidate possible underlying mechanisms involved in the pathogenesis of IMN.

Comprehensive analysis of key m5C modification-related genes in type 2 diabetes

Background: 5-methylcytosine (m5C) RNA methylation plays a significant role in several human diseases. However, the functional role of m5C in type 2 diabetes (T2D) remains unclear.

Methods: The merged gene expression profiles from two Gene Expression Omnibus (GEO) datasets were used to identify m5C-related genes and T2D-related differentially expressed genes (DEGs). Least-absolute shrinkage and selection operator (LASSO) regression analysis was performed to identify optimal predictors of T2D. After LASSO regression, we constructed a diagnostic model and validated its accuracy. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to confirm the biological functions of DEGs. Gene Set Enrichment Analysis (GSEA) was used to determine the functional enrichment of molecular subtypes. Weighted gene co-expression network analysis (WGCNA) was used to select the module that correlated with the most pyroptosis-related genes. Protein-protein interaction (PPI) network was established using the STRING database, and hub genes were identified using Cytoscape software. The competitive endogenous RNA (ceRNA) interaction network of the hub genes was obtained. The CIBERSORT algorithm was applied to analyze the interactions between hub gene expression and immune infiltration.

Results: m5C-related genes were significantly differentially expressed in T2D and correlated with most T2D-related DEGs. LASSO regression showed that ZBTB4 could be a predictive gene for T2D. GO, KEGG, and GSEA indicated that the enriched modules and pathways were closely related to metabolism-related biological processes and cell death. The top five genes were identified as hub genes in the PPI network. In addition, a ceRNA interaction network of hub genes was obtained. Moreover, the expression levels of the hub genes were significantly correlated with the abundance of various immune cells.

Conclusion: Our findings may provide insights into the molecular mechanisms underlying T2D based on its pathophysiology and suggest potential biomarkers and therapeutic targets for T2D.

Suppression of SMOC2 alleviates myocardial fibrosis via the ILK/p38 pathway

Background

Fibrosis of the myocardium is one of the main pathological changes of adverse cardiac remodeling, which is associated with unsatisfactory outcomes in patients with heart disease. Further investigations into the precise molecular mechanisms of cardiac fibrosis are urgently required to seek alternative therapeutic strategies for individuals suffering from heart failure. SMOC2 has been shown to be essential to exert key pathophysiological roles in various physiological processes in vivo, possibly contributing to the pathogenesis of fibrosis. A study investigating the relationship between SMOC2 and myocardial fibrosis has yet to be conducted.

Methods

Mice received a continuous ISO injection subcutaneously to induce cardiac fibrosis, and down-regulation of SMOC2 was achieved by adeno-associated virus-9 (AAV9)-mediated shRNA knockdown. Neonatal fibroblasts were separated and cultured in vitro with TGFβ to trigger fibrosis and infected with either sh-SMOC2 or sh-RNA as a control. The role and mechanisms of SMOC2 in myocardial fibrosis were further examined and analyzed.

Results

SMOC2 knockdown partially reversed cardiac functional impairment and cardiac fibrosis in vivo after 21 consecutive days of ISO injection. We further demonstrated that targeting SMOC2 expression effectively slowed down the trans-differentiation and collagen deposition of cardiac fibroblasts stimulated by TGFβ. Mechanistically, targeting SMOC2 expression inhibited the induction of ILK and p38 in vivo and in vitro, and ILK overexpression increased p38 phosphorylation activity and compromised the protective effects of sh-SMOC2-mediated cardiac fibrosis.

Conclusion

Therapeutic SMOC2 silencing alleviated cardiac fibrosis through inhibition of the ILK/p38 signaling, providing a preventative and control strategy for cardiac remodeling management in clinical practice.