Identification of important genes related to ferroptosis and hypoxia in acute myocardial infarction based on WGCNA

Regulatory role of PDK1 via integrated gene analysis of mitochondria-immune response in periodontitis

AIMS

To investigate the association between mitochondrial events and immune response in periodontitis and related regulatory genes.

MAIN METHODS

Gene expression profiles in gingival tissues were retrieved from the Gene Expression Omnibus. Mitochondria-immune response-related differentially expressed genes (MIR-DEGs) between the healthy and periodontitis samples were determined. WGCNA, GO, and KEGG were used to investigate the function and the enriched pathways of MIR-DEGs. The correlation between MIR-DEGs expression and clinical probing pocket depth was analyzed. The MIR-DEGs were further identified and verified in animal samples. A periodontitis model was established in C57BL/6 mice with silk ligation. Micro-computed tomography was used to assess alveolar bone loss. Western blot, quantitative real-time polymerase chain reaction, and immunohistochemical analyses further validated the differential expression of the MIR-DEGs.

KEY FINDINGS

A total of ten MIR-DEGs (CYP24A1, PRDX4, GLDC, PDK1, BCL2A1, CBR3, ARMCX3, BNIP3, IFI27, and UNG) were identified, the expression of which could effectively distinguish patients with periodontitis from the healthy controls. Enhanced immune response was detected in the periodontitis group with that in the healthy controls, especially in B cells. PDK1 was a critical MIR-DEG correlated with B cell immune response and clinical periodontal probing pocket depth. Both animal and clinical periodontal samples presented higher gene and protein expression of PDK1 than the control samples. Additionally, PDK1 colocalized with B cells in both animal and clinical periodontal tissues.

SIGNIFICANCE

Mitochondria participate in the regulation of the immune response in periodontitis. PDK1 may be the key mitochondria-related gene regulating B-cell immune response in periodontitis.

CXCR4-mediated neutrophil dynamics in periodontitis

BACKGROUND AND OBJECTIVE

Periodontitis is a common oral disease closely related to immune response and this study is aimed to identify the key immune-related pathogenic genes and analyze the infiltration and function of immune cells in the disease using bioinformatics methods.

METHODS

Transcriptome datasets and single-cell RNA sequencing (scRNA-seq) datasets were downloaded from the GEO database. We utilized weighted correlation network analysis and least absolute selection and shrinkage operator, protein-protein interaction network construction to screen out key pathogenic genes as well as conducted the cell-type identification by estimating relative subsets of RNA transcripts algorithm to analyze and characterize immune cell types in periodontal tissues. In addition to bioinformatics validations, clinical and cell samples were collected and mouse periodontitis models were constructed to validate the important role of key genes in periodontitis.

RESULTS

Bioinformatics analysis pointed out the positive correlation between CXCR4 expression and periodontitis, and revealed the increased infiltration of neutrophils in periodontal inflammatory. Similar results were obtained from clinical samples and animal models. In addition, the clustering and functional enrichment results based on CXCR4 expression levels included activation of immune response and cell migration, implying the possible function of CXCR4 on regulating neutrophil dynamics, which might contribute to periodontitis. Subsequent validation experiments confirmed that the increased expression of CXCR4 in neutrophils under periodontitis, where cell migration-related pathways also were activated.

CONCLUSION

CXCR4 could be the key pathogenic gene of periodontitis and CXCR4/CXCL12 signal axial might contribute to the development of periodontitis by mediating neutrophil dynamics, suggesting that CXCR4 could be a potential target to help identify novel strategies for the clinical diagnosis and treatment of periodontitis.

Expression characteristics of lipid metabolism-related genes and correlative immune infiltration landscape in acute myocardial infarction

Lipid metabolism is an important part of the heart's energy supply. The expression pattern and molecular mechanism of lipid metabolism-related genes (LMRGs) in acute myocardial infarction (AMI) are still unclear, and the link between lipid metabolism and immunity is far from being elucidated. In this study, 23 Common differentially expressed LMRGs were discovered in the AMI-related mRNA microarray datasets GSE61144 and GSE60993. These genes were mainly related to "leukotriene production involved in inflammatory response", "lipoxygenase pathway", "metabolic pathways", and "regulation of lipolysis in adipocytes" pathways. 12 LMRGs (ACSL1, ADCY4, ALOX5, ALOX5AP, CCL5, CEBPB, CEBPD, CREB5, GAB2, PISD, RARRES3, and ZNF467) were significantly differentially expressed in the validation dataset GSE62646 with their AUC > 0.7 except for ALOX5AP (AUC = 0.699). Immune infiltration analysis and Pearson correlation analysis explored the immune characteristics of AMI, as well as the relationship between these identified LMRGs and immune response. Lastly, the up-regulation of ACSL1, ALOX5AP, CEBPB, and GAB2 was confirmed in the mouse AMI model. Taken together, LMRGs ACSL1, ALOX5AP, CEBPB, and GAB2 are significantly upregulated in AMI patients' blood, peripheral blood of AMI mice, myocardial tissue of AMI mice, and therefore might be new potential biomarkers for AMI.

Transcriptional profiling links unique human macrophage phenotypes to the growth of intracellular Salmonella enterica serovar Typhi

Macrophages provide a crucial environment for Salmonella enterica serovar Typhi (S. Typhi) to multiply during typhoid fever, yet our understanding of how human macrophages and S. Typhi interact remains limited. In this study, we delve into the dynamics of S. Typhi replication within human macrophages and the resulting heterogeneous transcriptomic responses of macrophages during infection. Our study reveals key factors that influence macrophage diversity, uncovering distinct immune and metabolic pathways associated with different stages of S. Typhi intracellular replication in macrophages. Of note, we found that macrophages harboring replicating S. Typhi are skewed towards an M1 pro-inflammatory state, whereas macrophages containing non-replicating S. Typhi exhibit neither a distinct M1 pro-inflammatory nor M2 anti-inflammatory state. Additionally, macrophages with replicating S. Typhi were characterized by the increased expression of genes associated with STAT3 phosphorylation and the activation of the STAT3 transcription factor. Our results shed light on transcriptomic pathways involved in the susceptibility of human macrophages to intracellular S. Typhi replication, thereby providing crucial insight into host phenotypes that restrict and support S. Typhi infection.

Curculigoside, a traditional Chinese medicine monomer, ameliorates oxidative stress in Alzheimer's disease mouse model via suppressing ferroptosis

Alzheimer's disease (AD) is a neurodegenerative disorder where oxidative stress, induced by ferroptosis, has been linked to neuronal damage and cognitive deficits. The objective of this study is to investigate if the potential therapeutic agent, Curculigoside (CUR), could ameliorate AD by inhibiting ferroptosis. The potential therapeutic targets, such as GPX4 and SLC7A11, were identified using weighted gene co-expression network analysis (WGCNA). Concurrently, CUR was also screened against these potential targets using various analytical methods. For the in vivo studies, intragastric administration of CUR significantly ameliorated cognitive impairment in AD model mice induced by scopolamine and okadaic acid (OA). In vitro, CUR protected neuronal cells by altering the levels of ferroptosis-related specific markers in OA and scopolamine-induced neurotoxicity. The administration of CUR through intragastric route significantly reduced the levels of AD-promoting factors (such as Aβ1-42, p-tau) and ferroptosis-promoting factors in the hippocampus and cortex of AD mice. Furthermore, CUR up-regulated the expression of GPX4 and decreased the expression of SLC7A11 in the ferroptosis signaling pathway, thereby increasing the ratio of glutathione (GSH)/oxidized glutathione (GSSG) in vivo and vitro. In conclusion, the cumulative results suggest that the natural compound CUR may serve as a promising therapeutic agent to ameliorate AD by inhibiting ferroptosis.

Exploring the molecular biology of ischemic cardiomyopathy based on ferroptosis‑related genes

Ischemic cardiomyopathy (ICM) is a serious cardiac disease with a very high mortality rate worldwide, which causes myocardial ischemia and hypoxia as the main damage. Further understanding of the underlying pathological processes of cardiomyocyte injury is key to the development of cardioprotective strategies. Ferroptosis is an iron-dependent form of regulated cell death characterized by the accumulation of lipid hydroperoxides to lethal levels, resulting in oxidative damage to the cell membrane. The current understanding of the role and regulation of ferroptosis in ICM is still limited, especially in the absence of evidence from large-scale transcriptomic data. Through comprehensive bioinformatics analysis of human ICM transcriptome data obtained from the Gene Expression Omnibus database, the present study identified differentially expressed ferroptosis-related genes (DEFRGs) in ICM. Subsequently, their potential biological mechanisms and cross-talk were analyzed, and hub genes were identified by constructing protein-protein interaction networks. Ferroptosis features such as reactive oxygen species generation, changes in ferroptosis marker proteins, iron ion aggregation and lipid oxidation, were identified in the H9c2 anoxic reoxygenation injury model. Finally, the diagnostic ability of Gap junction alpha-1 (GJA1), Solute carrier family 40 member 1 (SLC40A1), Alpha-synuclein (SNCA) were identified through receiver operating characteristic curves and the expression of DEFRGs was verified in an in vitro model. Furthermore, potential drugs (retinoic acid) that could regulate ICM ferroptosis were predicted based on key DEFRGs. The present article presents new insights into the role of ferroptosis in ICM, investigating the regulatory role of ferroptosis in the pathological process of ICM and advocating for ferroptosis as a potential novel therapeutic target for ICM based on evidence from the ICM transcriptome.

Identification of crucial genes through WGCNA in the progression of gastric cancer

Background: To explore the hub gene closely related to the progression of gastric cancer (GC), so as to provide a theoretical basis for revealing the therapeutic mechanism of GC. Methods: The gene expression profile and clinical data of GSE15459 in Gene Expression Omnibus (GEO) database were downloaded. The weighted gene co-expression network analysis (WGCNA) was used to screen the key modules related to GC progression. Survival analysis was used to assess the influence of hub genes on patients' outcomes. CIBERSORT analysis was used to predict the tissue infiltrating immune cells in patients. Immunohistochemical staining was conducted to further verify the expression of hub genes. Results: Through WGCNA, a total of 26 co-expression modules were constructed, in which salmon module and royalblue module had strong correlation with GC progression. The results of enrichment analysis showed that genes in the two modules were mainly involved in toll-like receptor signaling pathway, cholesterol metabolism and neuroactive ligand-receptor interaction. Six hub genes (C1QA, C1QB, C1QC, FCER1G, FPR3 and TYROBP) related to GC progression were screened. Survival analysis showed overall survival in the high expression group was significantly lower than that in the low expression group. CIBERSORT analysis revealed that immune characteristics difference between patients in early stage and advanced stage. Immunohistochemical results confirmed that C1QB, FCER1G, FPR3 and TYROBP were significantly associated with disease progression in GC. Conclusion: Our study identified that C1QB, FCER1G, FPR3 and TYROBP played important roles in the progression of GC, and their specific mechanisms are worth further study.

Xinnaotongluo liquid protects H9c2 cells from H/R-induced damage by regulating MDM2/STEAP3

Xinnaotongluo liquid has been used to improve the clinical symptoms of patients with myocardial infarction. However, the molecular mechanism of Xinnaotongluo liquid is not completely understood. H9c2 cells exposed to hypoxia/reoxygenation (H/R) was used to simulate damage to cardiomyocytes in myocardial infarction in vitro. The biological indicators of H9c2 cells were measured by cell counting kit-8, enzyme linked immunoabsorbent assay, and western blot assay. In H/R-induced H9c2 cells, a markedly reduced murine double minute 2 (MDM2) was observed. However, the addition of Xinnaotongluo liquid increased MDM2 expression in H/R-induced H9c2 cells. And MDM2 overexpression strengthened the beneficial effects of Xinnaotongluo liquid on H9c2 cells from the perspective of alleviating oxidative damage, cellular inflammation, apoptosis and ferroptosis of H/R-induced H9c2 cells. Moreover, MDM2 overexpression reduced the protein expression of p53 and Six-Transmembrane Epithelial Antigen of Prostate 3 (STEAP3). Whereas, STEAP3 overexpression hindered the function of MDM2-overexpression in H/R-induced H9c2 cells. Our results insinuated that Xinnaotongluo liquid could protect H9c2 cells from H/R-induced damage by regulating MDM2/STEAP3, which provide a potential theoretical basis for further explaining the working mechanism of Xinnaotongluo liquid.

PRDX6 alleviated heart failure by inhibiting doxorubicin-induced ferroptosis through the JAK2/STAT1 pathway inactivation

Peroxiredoxin 6 (PRDX6) is a protective biomarker associated with ferroptosis in heart failure (HF). This study investigated the specific mechanism of PRDX6 on doxorubicin (DOX)-induced ferroptosis in HF. Wistar rats and H9c2 cells were induced by DOX to construct HF models. Pathological changes and collagen deposition in myocardium were investigated using HE and Masson staining. PRDX6 levels, indexes of ferroptosis, and JAK2/STAT1 pathway were detected by qRT-PCR, Western blot, and biochemical kits. DOX promoted heart weight/body weight, increased inflammation and collagen deposition, increased PTGS2 and MDA levels, and decreased SLC7A11, GPX4, FTH1, and PRDX6 levels in myocardium. PRDX6 overexpression reduced PTGS2, MDA, Fe2+, and LDH levels, inhibited JAK2 and STAT1 phosphorylation, and increased SLC7A11, GPX4, and FTH1 levels in DOX-added H9c2 cells. RO8191 and erastin reversed the inhibition of PRDX6 on ferroptosis through the JAK2/STAT1 pathway. Overall, PRDX6 alleviated HF by inhibiting DOX-induced ferroptosis through the JAK2/STAT1 pathway inactivation.

A Novel Conductive Polypyrrole-Chitosan Hydrogel Containing Human Endometrial Mesenchymal Stem Cell-Derived Exosomes Facilitated Sustained Release for Cardiac Repair

Myocardial infarction (MI) results in cardiomyocyte necrosis and conductive system damage, leading to sudden cardiac death and heart failure. Studies have shown that conductive biomaterials can restore cardiac conduction, but cannot facilitate tissue regeneration. This study aims to add regenerative capabilities to the conductive biomaterial by incorporating human endometrial mesenchymal stem cell (hEMSC)-derived exosomes (hEMSC-Exo) into poly-pyrrole-chitosan (PPY-CHI), to yield an injectable hydrogel that can effectively treat MI. In vitro, PPY-CHI/hEMSC-Exo, compared to untreated controls, PPY-CHI, or hEMSC-Exo alone, alleviates H2O2-induced apoptosis and promotes tubule formation, while in vivo, PPY-CHI/hEMSC-Exo improves post-MI cardiac functioning, along with counteracting against ventricular remodeling and fibrosis. All these activities are facilitated via increased epidermal growth factor (EGF)/phosphoinositide 3-kinase (PI3K)/AKT signaling. Furthermore, the conductive properties of PPY-CHI/hEMSC-Exo are able to resynchronize cardiac electrical transmission to alleviate arrythmia. Overall, PPY-CHI/hEMSC-Exo synergistically combines the cardiac regenerative capabilities of hEMSC-Exo with the conductive properties of PPY-CHI to improve cardiac functioning, via promoting angiogenesis and inhibiting apoptosis, as well as resynchronizing electrical conduction, to ultimately enable more effective MI treatment. Therefore, incorporating exosomes into a conductive hydrogel provides dual benefits in terms of maintaining conductivity, along with facilitating long-term exosome release and sustained application of their beneficial effects.

Screening of key immunerelated gene in Parkinsons disease based on WGCNA and machine learning

OBJECTIVES

Abnormal immune system activation and inflammation are crucial in causing Parkinson's disease. However, we still don't fully understand how certain immune-related genes contribute to the disease's development and progression. This study aims to screen key immune-related gene in Parkinson's disease based on weighted gene co-expression network analysis (WGCNA) and machine learning.

METHODS

This study downloaded the gene chip data from the Gene Expression Omnibus (GEO) database, and used WGCNA to screen out important gene modules related to Parkinson's disease. Genes from important modules were exported and a Venn diagram of important Parkinson's disease-related genes and immune-related genes was drawn to screen out immune related genes of Parkinson's disease. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze the the functions of immune-related genes and signaling pathways involved. Immune cell infiltration analysis was performed using the CIBERSORT package of R language. Using bioinformatics method and 3 machine learning methods [least absolute shrinkage and selection operator (LASSO) regression, random forest (RF), and support vector machine (SVM)], the immune-related genes of Parkinson's disease were further screened. A Venn diagram of differentially expressed genes screened using the 4 methods was drawn with the intersection gene being hub nodes (hub) gene. The downstream proteins of the Parkinson's disease hub gene was identified through the STRING database and a protein-protein interaction network diagram was drawn.

RESULTS

A total of 218 immune genes related to Parkinson's disease were identified, including 45 upregulated genes and 50 downregulated genes. Enrichment analysis showed that the 218 genes were mainly enriched in immune system response to foreign substances and viral infection pathways. The results of immune infiltration analysis showed that the infiltration percentages of CD4+ T cells, NK cells, CD8+ T cells, and B cells were higher in the samples of Parkinson's disease patients, while resting NK cells and resting CD4+ T cells were significantly infiltrated in the samples of Parkinson's disease patients. ANK1 was screened out as the hub gene. The analysis of the protein-protein interaction network showed that the ANK1 translated and expressed 11 proteins which mainly participated in functions such as signal transduction, iron homeostasis regulation, and immune system activation.

CONCLUSIONS

This study identifies the Parkinson's disease immune-related key gene ANK1 via WGCNA and machine learning methods, suggesting its potential as a candidate therapeutic target for Parkinson's disease.

Potential mechanisms and drug prediction of Rheumatoid Arthritis and primary Sjögren's Syndrome: A public databases-based study

Rheumatoid arthritis (RA) and primary Sjögren's syndrome (pSS) are the most common systemic autoimmune diseases, and they are increasingly being recognized as occurring in the same patient population. These two diseases share several clinical features and laboratory parameters, but the exact mechanism of their co-pathogenesis remains unclear. The intention of this study was to investigate the common molecular mechanisms involved in RA and pSS using integrated bioinformatic analysis. RNA-seq data for RA and pSS were picked up from the Gene Expression Omnibus (GEO) database. Co-expression genes linked with RA and pSS were recognized using weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) analysis. Then, we screened two public disease-gene interaction databases (GeneCards and Comparative Toxicogenomics Database) for common targets associated with RA and pSS. The DGIdb database was used to predict therapeutic drugs for RA and pSS. The Human microRNA Disease Database (HMDD) was used to screen out the common microRNAs associated with RA and pSS. Finally, a common miRNA-gene network was created using Cytoscape. Four hub genes (CXCL10, GZMA, ITGA4, and PSMB9) were obtained from the intersection of common genes from WGCNA, differential gene analysis and public databases. Twenty-four drugs corresponding to hub gene targets were predicted in the DGIdb database. Among the 24 drugs, five drugs had already been reported for the treatment of RA and pSS. Other drugs, such as bortezomib, carfilzomib, oprozomib, cyclosporine and zidovudine, may be ideal drugs for the future treatment of RA patients with pSS. According to the miRNA-gene network, hsa-mir-21 may play a significant role in the mechanisms shared by RA and pSS. In conclusion, we identified commom targets as potential biomarkers in RA and pSS from publicly available databases and predicted potential drugs based on the targets. A new understanding of the molecular mechanisms associated with RA and pSS is provided according to the miRNA-gene network.

A study on the role of Taxifolin in inducing apoptosis of pancreatic cancer cells: screening results using weighted gene co-expression network analysis

Pancreatic adenocarcinoma (PAAD) is a frequent malignant tumor in the pancreas. The incomplete understanding of cancer etiology and pathogenesis, as well as the limitations in early detection and diagnostic methods, have created an urgent need for the discovery of new therapeutic targets and drugs to control this disease. As a result, the current therapeutic options are limited. In this study, the weighted gene co-expression network analysis (WGCNA) method was employed to identify key genes associated with the progression and prognosis of pancreatic adenocarcinoma (PAAD) patients in the Gene Expression Profiling Interactive Analysis (GEPIA) database. To identify small molecule drugs with potential in the treatment of pancreatic adenocarcinoma (PAAD), we compared key genes to the reference dataset in the CMAP database. First, we analyzed the antitumor properties of small molecule drugs using cell counting kit-8 (CCK-8), AO/EB and Transwell assays. Subsequently, we integrated network pharmacology with molecular docking to explore the potential mechanisms of the identified molecules' anti-tumor effects. Our findings indicated that the progression and prognosis of PAAD patients in pancreatic cancer were associated with 11 genes, namely, DKK1, S100A2, CDA, KRT6A, ITGA3, GPR87, IL20RB, ZBED2, PMEPA1, CST6, and MUC16. These genes were filtered based on their therapeutic potential through comparing them with the reference dataset in the CMAP database. Taxifolin, a natural small molecule drug with the potential for treating PAAD, was screened by comparing it with the reference dataset in the CMAP database. Cell-based experiments have validated the potential of Taxifolin to facilitate apoptosis in pancreatic cancer cells while restraining their invasion and metastasis. This outcome is believed to be achieved via the HIF-1 signaling pathway. In conclusion, this study provided a theoretical basis for screening genes related to the progression of pancreatic cancer and discovered potentially active small molecule drugs. The experimental results confirm that Taxifolin has the ability to promote apoptosis in pancreatic cancer cells.

Identification and validation of hub genes and molecular classifications associated with chronic myeloid leukemia

Background

Chronic myeloid leukemia (CML) is a kind of malignant blood tumor, which is prone to drug resistance and relapse. This study aimed to identify novel diagnostic and therapeutic targets for CML.

Methods

Differentially expressed genes (DEGs) were obtained by differential analysis of the CML cohort in the GEO database. Weighted gene co-expression network analysis (WGCNA) was used to identify CML-related co-expressed genes. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to screen hub genes and construct a risk score model based on hub genes. Consensus clustering algorithm was used for the identification of molecular subtypes. Clinical samples and in vitro experiments were used to verify the expression and biological function of hub genes.

Results

A total of 378 DEGs were identified by differential analysis. 369 CML-related genes were identified by WGCNA analysis, which were mainly enriched in metabolism-related signaling pathways. In addition, CML-related genes are mainly involved in immune regulation and anti-tumor immunity, suggesting that CML has some immunodeficiency. Immune infiltration analysis confirmed the reduced infiltration of immune killer cells such as CD8+ T cells in CML samples. 6 hub genes (LINC01268, NME8, DMXL2, CXXC5, SCD and FBN1) were identified by LASSO regression analysis. The receiver operating characteristic (ROC) curve confirmed the high diagnostic value of the hub genes in the analysis and validation cohorts, and the risk score model further improved the diagnostic accuracy. hub genes were also associated with cell proliferation, cycle, and metabolic pathway activity. Two molecular subtypes, Cluster A and Cluster B, were identified based on hub gene expression. Cluster B has a lower risk score, higher levels of CD8+ T cell and activated dendritic cell infiltration, and immune checkpoint expression, and is more sensitive to commonly used tyrosine kinase inhibitors. Finally, our clinical samples validated the expression and diagnostic efficacy of hub genes, and the knockdown of LINC01268 inhibited the proliferation of CML cells, and promoted apoptosis.

Conclusion

Through WGCNA analysis and LASSO regression analysis, our study provides a new target for CML diagnosis and treatment, and provides a basis for further CML research.

Chronic bee paralysis virus exploits host antimicrobial peptides and alters gut microbiota composition to facilitate viral infection

The significance of gut microbiota in regulating animal immune response to viral infection is increasingly recognized. However, how chronic bee paralysis virus (CBPV) exploits host immune to disturb microbiota for its proliferation remains elusive. Through histopathological examination, we discovered that the hindgut harbored the highest level of CBPV, and displayed visible signs of damages. The metagenomic analysis showed that a notable reduction in the levels of Snodgrassella alvi and Lactobacillus apis, and a significant increase in the abundance of the opportunistic pathogens such as Enterobacter hormaechei and Enterobacter cloacae following CBPV infection. Subsequent co-inoculation experiments showed that these opportunistic pathogens facilitated the CBPV proliferation, leading to accelerated mortality in bees and exacerbation of bloated abdomen symptoms after CBPV infection. The expression level of antimicrobial peptide (AMP) was found to be significantly up-regulated by over 1000 times in response to CBPV infection, as demonstrated by subsequent transcriptome and quantitative real-time PCR investigations. In particular, through correlation analysis and a bacteriostatic test revealed that the AMPs did not exhibit any inhibitory effect against the two opportunistic pathogens. However, they did demonstrate inhibitory activity against S. alvi and L. apis. Our findings provide different evidence that the virus infection may stimulate and utilize the host's AMPs to eradicate probiotic species and facilitate the proliferation of opportunistic bacteria. This process weakens the intestinal barrier and ultimately resulting in the typical bloated abdomen.

Identification of clinical prognostic factors and analysis of ferroptosis-related gene signatures in the bladder cancer immune microenvironment

BACKGROUND

Bladder cancer (BLCA) is a prevalent malignancy affecting the urinary system and poses a significant burden in terms of both incidence and mortality rates on a global scale. Among all BLCA cases, non-muscle invasive bladder cancer constitutes approximately 75% of the total. In recent years, the concept of ferroptosis, an iron-dependent form of regulated cell death marked by the accumulation of lipid peroxides, has captured the attention of researchers worldwide. Nevertheless, the precise involvement of ferroptosis-related genes (FRGs) in the anti-BLCA response remains inadequately elucidated.

METHODS

The integration of BLCA samples from the TCGA and GEO datasets facilitated the quantitative evaluation of FRGs, offering potential insights into their predictive capabilities. Leveraging the wealth of information encompassing mRNAsi, gene mutations, CNV, TMB, and clinical features within these datasets further enriched the analysis, augmenting its robustness and reliability. Through the utilization of Lasso regression, a prediction model was developed, enabling accurate prognostic assessments within the context of BLCA. Additionally, co-expression analysis shed light on the complex relationship between gene expression patterns and FRGs, unraveling their functional relevance and potential implications in BLCA.

RESULTS

FRGs exhibited increased expression levels in the high-risk cohort of BLCA patients, even in the absence of other clinical indicators, suggesting their potential as prognostic markers. GSEA revealed enrichment of immunological and tumor-related pathways specifically in the high-risk group. Furthermore, notable differences were observed in immune function and m6a gene expression between the low- and high-risk groups. Several genes, including MYBPH, SOST, SPRR2A, and CRNN, were found to potentially participate in the oncogenic processes underlying BLCA. Additionally, CYP4F8, PDZD3, CRTAC1, and LRTM1 were identified as potential tumor suppressor genes. Significant discrepancies in immunological function and m6a gene expression were observed between the two risk groups, further highlighting the distinct molecular characteristics associated with different prognostic outcomes. Notably, strong correlations were observed among the prognostic model, CNVs, SNPs, and drug sensitivity profiles.

CONCLUSIONS

FRGs are associated with the onset and progression of BLCA. A FRGs signature offers a viable alternative to predict BLCA, and these FRGs show a prospective research area for BLCA targeted treatment in the future.

Mechanism Exploration on the Immunoregulation of Allogeneic Heart Transplantation Rejection in Rats With Exosome miRNA and Proteins From Overexpressed IDO1 BMSCs

Immunoregulation and indoleamine 2,3-dioxygenase 1 (IDO1) play pivotal roles in the rejection of allogeneic organ transplantation. This study aims to elucidate the immune-related functional mechanisms of exosomes (Exos) derived from bone marrow-derived mesenchymal stem cells (BMSCs) overexpressing IDO1 in the context of allogeneic heart transplantation (HTx) rejection. A rat model of allogeneic HTx was established. Exos were extracted after transfection with oe-IDO1 and oe-NC from rat BMSCs. Exos were administered via the caudal vein for treatment. The survival of rats was analyzed, and reverse transcription qualitative PCR (RT-qPCR) and immunohistochemistry (IHC) were employed to detect the expression of related genes. Histopathological examination was conducted using hematoxylin and eosin (HE) staining, and flow cytometry was utilized to analyze T-cell apoptosis. Proteomics and RNA-seq analyses were performed on Exos. The data were subjected to functional enrichment analysis using the R language. A protein interaction network was constructed using the STRING database, and miRWalk, TargetScan, and miRDB databases predicted the target genes, differentially expressed miRNAs, and transcription factors (TFs). Exos from BMSCs overexpressing IDO1 prolonged the survival time of rats undergoing allogeneic HTx. These Exos reduced inflammatory cell infiltration, mitigated myocardial damage, induced CD4 T-cell apoptosis, and alleviated transplantation rejection. The correlation between Exos from BMSCs overexpressing IDO1 and immune regulation was profound. Notably, 13 immune-related differential proteins (Anxa1, Anxa2, C3, Ctsb, Hp, Il1rap, Ntn1, Ptx3, Thbs1, Hspa1b, Vegfc, Dcn, and Ptpn11) and 10 significantly different miRNAs were identified. Finally, six key immune proteins related to IDO1 were identified through common enrichment pathways, including Thbs1, Dcn, Ptpn11, Hspa1b, Il1rap, and Vegfc. Thirteen TFs of IDO1-related key miRNAs were obtained, and a TF-miRNA-mRNA-proteins regulatory network was constructed. Exosome miRNA derived from BMSCs overexpressing IDO1 may influence T-cell activation and regulate HTx rejection by interacting with mRNA.

Deciphering the Hypoxia-immune interface in esophageal squamous carcinoma: a prognostic network model

Introduction

The rapid progress and poor prognosis of the exercise of esophageal squamous cell carcinoma (ESCA) bring great challenges to the treatment. Hypoxia in the tumor microenvironment has become a key factor in the pathogenesis of tumors. However, due to the lack of clear therapeutic targets, hypoxia targeted therapy of ESCA is still in the exploratory stage.

Methods

To bridge this critical gap, we mined a large number of gene expression profiles and clinical data on ESCA from public databases. First, weighted gene co-expression network analysis (WGCNA) and functional enrichment analysis were performed. We next delved into the relationship between hypoxia and apoptotic cell interactions. Meanwhile, using LASAS-Cox regression, we designed a robust prognostic risk score, which was subsequently validated in the GSE53625 cohort. In addition, we performed a comprehensive analysis of immune cell infiltration and tumor microenvironment using cutting-edge computational tools.

Results

Hypoxia-related genes were identified and classified by WGCNA. Functional enrichment analysis further elucidated the mechanism by which hypoxia affected the ESCA landscape. The results of the interaction analysis of hypoxia and apoptotic cells revealed their important roles in driving tumor progression. The validation results of the prognostic risk score model in the GSE53625 cohort obtained a good area under the receiver operating characteristic (ROC) curve, and the risk score was independently verified as a significant predictor of ESCA outcome. The results of immune cell infiltration and tumor microenvironment analysis reveal the profound impact of immune cell dynamics on tumor evolution.

Conclusion

Overall, our study presents a pioneering hypoxiacentered gene signature for prognostication in ESCA, providing valuable prognostic insights that could potentially revolutionize patient stratification and therapeutic management in clinical practice.

Expression and diagnostic value of PIWI-interacting RNA by serum in acute myocardial infarction

OBJECTIVE

To detect the expression level of PIWI-interacting RNA in the serum of patients with acute myocardial infarction, and to explore the role of PIWI-interacting RNA in acute myocardial infarction.

METHODS

RNA was extracted from the serum of acute myocardial infarction patients and healthy subjects, and high-throughput sequencing of PIWI-interacting RNAs was performed to screen differentially expressed PIWI-interacting RNAs. Quantitative polymerase chain reaction was used to detect the expression of four differentially expressed PIWI-interacting RNAs in 52 patients with acute myocardial infarction and 30 healthy people. Receiver operating characteristic (ROC) curve was further used to analyze the correlation between differentially expressed PIWI-interacting RNAs and the occurrence of acute myocardial infarction. Kyoto Encyclopedia of Genes and Genomes analysis was used to analyze the role of PIWI-interacting RNA in the occurrence of acute myocardial infarction.

RESULTS

RNA sequencing and bioinformatics analysis revealed that most piRNAs were upregulated in AMI patients, with 195 upregulated and 13 downregulated. Among them, piR-hsa-9010, piR-hsa-28646, and piR-hsa-23619 were significantly up-regulated in the serum of patients with acute myocardial infarction, but their expression in the acute heart failure group and coronary heart disease group was not significantly different from that in the healthy group. ROC curve analysis showed that piR-hsa-9010, piR-hsa-28646, and piR-hsa-23619 had high diagnostic values in acute myocardial infarction. In vitro, there was no significant difference in the expression of piR-hsa-9010 among THP-1, HUVEC, and AC16, while the expression of piR-hsa-28646 and piR-hsa-23619 in HUVEC was significantly higher than that in THP-1 and AC16. Pathway analysis showed that piR-hsa-23619 was mainly involved in TNF signaling pathway, and piR-hsa-28646 was mainly involved in Wnt signaling pathway.

CONCLUSION

piR-hsa-9010, piR-hsa-28646, and piR-hsa-23619 were significantly up-regulated in the serum of patients with acute myocardial infarction. It can be used as a new biomarker for the diagnosis of acute myocardial infarction, which may be a therapeutic target for acute myocardial infarction.

Identification of Ferroptosis-Related Genes in Heart Failure Induced by Transverse Aortic Constriction

Background

Heart failure (HF) is a common clinical syndrome due to ventricular dysfunction and is a major cause of mortality worldwide. Ferroptosis, marked by excessive iron-dependent lipid peroxidation, is closely related to HF. Therefore, the purpose of this study is to explore and validate ferroptosis-related markers in HF by bioinformatics analysis and animal experiments validation.

Materials and Methods

The gene expression profiles (GSE36074) of murine transverse aortic constriction (TAC) were obtained from the Gene Expression Omnibus (GEO); From the FerrDb database, ferroptosis-related genes (FRGs) were identified. Using GEO2R, differential expressed genes (DEGs) were screened. An overlapping analysis was conducted among DEGs and FRGs to identify ferroptosis-related DEGs (FRDEGs). We then performed clustering, functional enrichment analysis, and protein-protein interaction (PPI) analyses. In addition, the key FRDEGs were extracted by cytoHubba plugin and the networks of transcription factors (TFs)-key FRDEGs and microRNA-key FRDEGs were constructed. Lastly, the key FRDEGs were carried by quantitative reverse transcription PCR (RT-qPCR) and immunohistochemistry (IHC).

Results

Fifty-nine FRGs showing significantly different expression were identified from a total of 1918 DEGs in mice heart by transverse aortic constriction. GO and KEGG functional enrichment analysis revealed that these 59 ferroptosis-related DEGs mostly associated with positive regulation of apoptotic process, FoxO signaling pathway, VEGF signaling pathway, Apoptosis, Ferroptosis. Five key FRDEGs (Mapk14, Hif1a, Ddit3, Tlr4 and Ptgs2) were identified using PPI networks; Based on TFs-key FRDEGs networks, we found that Mapk14, Hif1a, Tlr4 and Ptgs2 were regulated by 3, 4, 5, and 29 TFs, respectively; however, Ddit3 was not regulated by any TF; By analyzing the miRNA-key FRDEGs networks, we found that 39, 74, 11, 28, and 18 miRNAs targets regulate the expression of Mapk14, Hif1a, Ddit3, Tlr4 and Ptgs2, respectively. Lastly, five key FRDEGs were validated at the mRNA and protein levels by RT-qPCR and IHC, which were in line with our bioinformatics analysis.

Conclusion

Our findings reveal that Mapk14, Hif1a, Ddit3, Tlr4 and Ptgs2 may be involved in the development of HF through regulating ferroptosis and as potential targets for HF.

The mechanism of ferroptosis and its related diseases

Ferroptosis, a regulated form of cellular death characterized by the iron-mediated accumulation of lipid peroxides, provides a novel avenue for delving into the intersection of cellular metabolism, oxidative stress, and disease pathology. We have witnessed a mounting fascination with ferroptosis, attributed to its pivotal roles across diverse physiological and pathological conditions including developmental processes, metabolic dynamics, oncogenic pathways, neurodegenerative cascades, and traumatic tissue injuries. By unraveling the intricate underpinnings of the molecular machinery, pivotal contributors, intricate signaling conduits, and regulatory networks governing ferroptosis, researchers aim to bridge the gap between the intricacies of this unique mode of cellular death and its multifaceted implications for health and disease. In light of the rapidly advancing landscape of ferroptosis research, we present a comprehensive review aiming at the extensive implications of ferroptosis in the origins and progress of human diseases. This review concludes with a careful analysis of potential treatment approaches carefully designed to either inhibit or promote ferroptosis. Additionally, we have succinctly summarized the potential therapeutic targets and compounds that hold promise in targeting ferroptosis within various diseases. This pivotal facet underscores the burgeoning possibilities for manipulating ferroptosis as a therapeutic strategy. In summary, this review enriched the insights of both investigators and practitioners, while fostering an elevated comprehension of ferroptosis and its latent translational utilities. By revealing the basic processes and investigating treatment possibilities, this review provides a crucial resource for scientists and medical practitioners, aiding in a deep understanding of ferroptosis and its effects in various disease situations.

Time-course transcriptome analysis of lungs from mice infected with inhaled aerosolized Stenotrophomonas maltophilia

Background

Stenotrophomonas maltophilia (SMA) has emerged as an important pathogen capable of causing an opportunistic and nosocomial infection. We performed RNA sequencing (RNA-seq) of lung tissues from mice with pulmonary SMA infection over time via aerosolized intratracheal inhalation to investigate transcription profile changes in SMA-infected lungs.

Methods

A mouse model of acute lethal SMA pneumonia was established in this study using aerosolized intratracheal inhalation, laying the groundwork for future SMA research. RNA-seq was then used to create a transcriptional profile of the lungs of the model mice at 0, 4, 12, 24, 48, and 72 hours post-infection (hpi). Mfuzz time clustering, weighted gene coexpression network analysis (WGCNA), and Immune Cell Abundance Identifier for mouse (ImmuCellAI-mouse) were used to analyze RNA-seq data.

Results

A gradual change in the lung transcriptional profile was observed, which was consistent with the expected disease progression. At 4 hpi, the expression of genes related to the acute phase inflammatory response increased, as predicted abundance of innate immune cells. At this stage, an increased demand for energy was also observed, including an increase in the expression of genes involved in circulation, muscle function and mitochondrial respiratory chain function. The expression of genes associated with endoplasmic reticulum stress (ERS) and autophagy increased at 24 hpi. Unlike the number of natural killer (NK) cells following most bacterial lung infections, the abundance of NK cells decreased following infection with SMA. The expression levels of Cxcl10, Cd14, Gbp5, Cxcr2, Tnip1, Zc3h12a, Egr1, Sell and Gbp2 were high and previously unreported in SMA pneumonia, and they may be important targets for future studies.

Conclusions

To our knowledge, this is the first study to investigate the pulmonary transcriptional response to SMA infection. The findings shed light on the molecular mechanisms underlying the pathogenesis of SMA pneumonia, which may aid in the development of therapies to reduce the occurrence of SMA pulmonary infection.

Potential diagnostic biomarkers: 6 cuproptosis- and ferroptosis-related genes linking immune infiltration in acute myocardial infarction

The current diagnostic biomarkers of acute myocardial infarction (AMI), troponins, lack specificity and exist as false positives in other non-cardiac diseases. Previous studies revealed that cuproptosis, ferroptosis, and immune infiltration are all involved in the development of AMI. We hypothesize that combining the analysis of cuproptosis, ferroptosis, and immune infiltration in AMI will help identify more precise diagnostic biomarkers. The results showed that a total of 19 cuproptosis- and ferroptosis-related genes (CFRGs) were differentially expressed between the healthy and AMI groups. Functional enrichment analysis showed that the differential CFRGs were mostly enriched in biological processes related to oxidative stress and the inflammatory response. The immune infiltration status analyzed by ssGSEA found elevated levels of macrophages, neutrophils, and CCR in AMI. Then, we screened 6 immune-related CFRGs (CXCL2, DDIT3, DUSP1, CDKN1A, TLR4, STAT3) to construct a nomogram for predicting AMI and validated it in the GSE109048 dataset. Moreover, we also identified 5 pivotal miRNAs and 10 candidate drugs that target the 6 feature genes. Finally, RT-qPCR analysis verified that all 6 feature genes were upregulated in both animals and patients. In conclusion, our study reveals the significance of immune-related CFRGs in AMI and provides new insights for AMI diagnosis and treatment.

Bioinformatics and experimental analyses of glutamate receptor and its targets genes in myocardial and cerebral ischemia

BACKGROUND

There is a mutual hemodynamic and pathophysiological basis between the heart and brain. Glutamate (GLU) signaling plays an important role in the process of myocardial ischemia (MI) and ischemic stroke (IS). To further explore the common protective mechanism after cardiac and cerebral ischemic injuries, the relationship between GLU receptor-related genes and MI and IS were analyzed.

RESULTS

A total of 25 crosstalk genes were identified, which were mainly enriched in the Toll-like receptor signaling pathway, Th17 cell differentiation, and other signaling pathways. Protein-protein interaction analysis suggested that the top six genes with the most interactions with shared genes were IL6, TLR4, IL1B, SRC, TLR2, and CCL2. Immune infiltration analysis suggested that immune cells such as myeloid-derived suppressor cells and monocytes were highly expressed in the MI and IS data. Memory B cells and Th17 cells were expressed at low levels in the MI and IS data; molecular interaction network construction suggested that genes such as JUN, FOS, and PPARA were shared genes and transcription factors; FCGR2A was a shared gene of MI and IS as well as an immune gene. Least absolute shrinkage and selection operator logistic regression analysis identified nine hub genes: IL1B, FOS, JUN, FCGR2A, IL6, AKT1, DRD4, GLUD2, and SRC. Receiver operating characteristic analysis revealed that the area under the curve of these hub genes was > 65% in MI and IS for all seven genes except IL6 and DRD4. Furthermore, clinical blood samples and cellular models showed that the expression of relevant hub genes was consistent with the bioinformatics analysis.

CONCLUSIONS

In this study, we found that the GLU receptor-related genes IL1B, FOS, JUN, FCGR2A, and SRC were expressed in MI and IS with the same trend, which can be used to predict the occurrence of cardiac and cerebral ischemic diseases and provide reliable biomarkers to further explore the co-protective mechanism after cardiac and cerebral ischemic injury.

Bioinformatics analysis and identification of hub genes associated with female acute myocardial infarction patients by using weighted gene co-expression networks

To explore potential biomarkers of acute myocardial infarction (AMI) in females by using bioinformatics analysis. In this study, we explored potential biomarkers of AMI in females using bioinformatics analysis. We screened a total of 186 differentially expressed genes from the Gene Expression Omnibus. In the study, we found that weighted gene co-expression network analysis explored the co-expression network of genes and identified key modules. Simultaneously, we chose brown modules as key modules related to AMI. In this study, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis revealed that genes in the brown module were mainly enriched in "heparin" and 'complementation and coagulation cascade. Based on the protein-protein interaction network, we identified S100A9, mitogen-activated protein kinase (MAPK) 3, MAPK1, MMP3, interleukin (IL)-17A, and HSP90AB1 as hub gene sets. Whereas, polymerase chain reaction results showed that S100A9, MAPK3, MAPK1, MMP3, IL-17A, and HSP90AB1 were highly expressed compared with the control group. The IL-17 signaling pathway associated with an inflammatory response may be a potential biomarker and target for the treatment of women with myocardial infarction.

Identification of key genes for IgA nephropathy based on machine learning algorithm and correlation analysis of immune cells

INTRODUCTION

The pathogenesis and progression mechanism of Immunoglobulin A nephropathy (IgAN) is not fully understood. There is a lack of panoramic analysis of IgAN immune cell infiltration and algorithms that are more efficient and accurate for screening key pathogenic genes.

METHODS

RNA sequencing (RNA-seq) data sets on IgAN were downloaded from the Gene Expression Omnibus (GEO) database, including GSE93798, GSE35489, and GSE115857. The RNA-seq data set of kidney tissue as control samples were downloaded from the Genotype-Tissue Expression (GTEx) database. Three machine learning algorithms-weighted gene co-expression network analysis (WGCNA), least absolute shrinkage and selection operator (LASSO), and support vector machine-were used to identify the key pathogenic gene sets of the IgAN disease. The ssGSEA method was applied to calculate the immune cell infiltration (ICI) of IgAN samples, whereas the Spearman test was used for correlation analysis. The receiver operator characteristic curve (ROC) was used to evaluate the diagnostic efficacy of key genes. The correlation between the key genes and ICI was analyzed using the Spearman test.

RESULTS

A total of 177 genes were screened out as differentially expressed genes (DEGs) for IgAN, including 135 up-regulated genes and 42 down-regulated genes. The DEGs were significantly enriched in the inflammatory- or immune-related pathways (gene sets). Activating transcription factor 3 (AFT3), C-X-C Motif Chemokine Ligand 6 (CXCL6), and v-fos FBJ murine osteosarcoma viral oncogene homolog B (FOSB) were identified using WGCNA, support vector machine, and LASSO algorithms. These three genes revealed good diagnostic efficacy in the training and test cohorts. The CXCL6 expression positively correlated with activated B cells and memory B cells.

CONCLUSION

ATF3, FOSB, and CXCL6 genes were identified as potential biomarkers of IgAN. These three genes exhibited good diagnostic efficacy for IgAN. We described the landscape of immune cell infiltration for IgAN. Activated B cells and memory B cells were more highly expressed in the IgAN samples than in the control samples. CXCL6 seems crucial to the pathogenesis of IgAN and may induce IgAN by enriching immune cells. Our study may contribute to developing CXCL6 inhibitors that target B cells for IgAN therapy.

Machine learning algorithms assisted identification of post-stroke depression associated biological features

Objectives

Post-stroke depression (PSD) is a common and serious psychiatric complication which hinders functional recovery and social participation of stroke patients. Stroke is characterized by dynamic changes in metabolism and hemodynamics, however, there is still a lack of metabolism-associated effective and reliable diagnostic markers and therapeutic targets for PSD. Our study was dedicated to the discovery of metabolism related diagnostic and therapeutic biomarkers for PSD.

Methods

Expression profiles of GSE140275, GSE122709, and GSE180470 were obtained from GEO database. Differentially expressed genes (DEGs) were detected in GSE140275 and GSE122709. Functional enrichment analysis was performed for DEGs in GSE140275. Weighted gene co-expression network analysis (WGCNA) was constructed in GSE122709 to identify key module genes. Moreover, correlation analysis was performed to obtain metabolism related genes. Interaction analysis of key module genes, metabolism related genes, and DEGs in GSE122709 was performed to obtain candidate hub genes. Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and random forest, were used to identify signature genes. Expression of signature genes was validated in GSE140275, GSE122709, and GSE180470. Gene set enrichment analysis (GSEA) was applied on signature genes. Based on signature genes, a nomogram model was constructed in our PSD cohort (27 PSD patients vs. 54 controls). ROC curves were performed for the estimation of its diagnostic value. Finally, correlation analysis between expression of signature genes and several clinical traits was performed.

Results

Functional enrichment analysis indicated that DEGs in GSE140275 enriched in metabolism pathway. A total of 8,188 metabolism associated genes were identified by correlation analysis. WGCNA analysis was constructed to obtain 3,471 key module genes. A total of 557 candidate hub genes were identified by interaction analysis. Furthermore, two signature genes (SDHD and FERMT3) were selected using LASSO and random forest analysis. GSEA analysis found that two signature genes had major roles in depression. Subsequently, PSD cohort was collected for constructing a PSD diagnosis. Nomogram model showed good reliability and validity. AUC values of receiver operating characteristic (ROC) curve of SDHD and FERMT3 were 0.896 and 0.964. ROC curves showed that two signature genes played a significant role in diagnosis of PSD. Correlation analysis found that SDHD (r = 0.653, P < 0.001) and FERM3 (r = 0.728, P < 0.001) were positively related to the Hamilton Depression Rating Scale 17-item (HAMD) score.

Conclusion

A total of 557 metabolism associated candidate hub genes were obtained by interaction with DEGs in GSE122709, key modules genes, and metabolism related genes. Based on machine learning algorithms, two signature genes (SDHD and FERMT3) were identified, they were proved to be valuable therapeutic and diagnostic biomarkers for PSD. Early diagnosis and prevention of PSD were made possible by our findings.

Enlightening the mechanism of ferroptosis in epileptic heart

Epilepsy is a chronic neurological degenerative disease with a high incidence, affecting all age groups. Refractory Epilepsy (RE) occurs in approximately 30-40% of cases with a higher risk of sudden unexpected death in epilepsy (SUDEP). Recent studies have shown that spontaneous seizures developed in epilepsy can be related to an increase in oxidative stress and reactive oxygen derivatives (ROS) production. Increasing ROS concentration causes lipid peroxidation, protein oxidation, destruction of nuclear genetic material, enzyme inhibition, and cell death by a mechanism known as "ferroptosis" (Fts). Inactivation of glutathione peroxidase 4 (GPX4) induces Fts, while oxidative stress is linked with increased intracellular free iron (Fe+2) concentration. Fts is also a non-apoptotic programmed cell death mechanism, where a hypoxia-inducible factor 1 alpha (HIF-141) dependent hypoxic stress-like condition appears to occur with accumulation of iron and cytotoxic ROS in affected cells. Assuming convulsive crises as hypoxic stress, repetitive convulsive/hypoxic stress can be an effective inducer of the "epileptic heart" (EH), which is characterized by altered autonomic function and a high risk of malignant or fatal bradycardia. We previously reported that experimental recurrent seizures induce cardiomyocyte Fts associated with SUDEP. Furthermore, several genes related to Fts and hypoxia have recently been identified in acute myocardial infarction. An emerging theme from recent studies indicates that inhibition of GPX4 through modulating expression or activities of the xCT antiporter system (SLC7A11) governs cell sensitivity to oxidative stress from ferroptosis. Furthermore, during hypoxia, an increased expression of stress transcriptional factor ATF3 can promote Fts induced by erastin in a HIF-141-dependent manner. We propose that inhibition of Fts with ROS scavengers, iron chelators, antioxidants, and transaminase inhibitors could provide a therapeutic effect in epilepsy and improve the prognosis of SUDEP risk by protecting the heart from ferroptosis.

Identification of Clinical Prognostic Regulators and Analysis of Ferroptosis-Related Signatures in the Tumor Immune Microenvironment in Lung Squamous Cell Carcinoma

Objective

Lung squamous cell carcinoma (LUSC) is a common respiratory malignancy and presents an increasing prevalence. Ferroptosis is a newly identified controlled cell death that has captured clinical attention worldwide. However, the ferroptosis-related lncRNA expression in LUSC and its relevance to prognosis remain elusive.

Methods

The research measured predictive ferroptosis-related lncRNAs in LUSC samples from the TCGA datasets. Data on the stemness indices (mRNAsi) and corresponding clinical characteristics were obtained from TCGA. A prognosis model was established using the LASSO regression. Changes within the neoplasm microenvironment (TME) and medicine association were examined to grasp higher immune cell infiltration in numerous risk teams. In line with coexpression studies, the expression of lncRNAs is closely associated with that of ferroptosis. They were overexpressed in unsound people in the absence of alternative clinical symptoms.

Results

The low-risk and speculative teams were considered to have substantial differences in CCR and inflammation-promoting genes. C10orf55, AC016924.1, AL161431.1, LUCAT1, AC104248.1, and MIR3945HG were highly expressed in the high-risk group, suggesting their involvement in the oncology process of LUSC. Moreover, AP006545.2 and AL122125.1 were considerably higher in the low-risk group, implying the potential of these genes as LUSC tumor suppressor genes. The biomarkers listed above may serve as therapeutic targets for LUSC. lncRNAs were also linked to patient outcomes in the LUSC trial.

Conclusion

lncRNAs of ferroptosis were overexpressed in the high-risk cohort without other clinical signs, implying their potential to predict BLCA prognosis. GSEA highlighted immunological and tumor-related pathways in the high-risk group. LUSC occurrence and progression are linked to lncRNAs of ferroptosis. Corresponding prognostic models help forecast the prognosis of LUSC patients. lncRNAs of ferroptosis and associated immune cell infiltration in the tumor microenvironment (TME) may serve as potential therapeutic targets in LUSC, which requires further trials. In addition, the lncRNAs of ferroptosis signature offer a viable alternative to predict LUSC, and these ferroptosis-lncRNAs show a prospective research area for LUSC-targeted treatment in the future.

Ginsenoside Rg5 attenuates hypoxia-induced cardiomyocyte apoptosis via regulating the Akt pathway

Ginsenoside Rg5 has been implicated in a variety of diseases. However, it is unknown whether Ginsenoside Rg5 can protect against hypoxia-induced neonatal rat cardiomyocytes (NRMs). The purpose of this study was to look into the effect of Ginsenoside Rg5 on hypoxia-induced NRMs apoptosis as well as the underlying molecular mechanism. In this study, following isolation and culture of ventricular myocardial cells from neonatal rats, the appropriate concentration of Rg5 was determined using the MTT assay, the effect of Rg5 on apoptosis was assessed employing TUNEL staining and flow cytometry assays. Levels of apoptosis-related proteins and phosphorylated level of Akt (ser 473 and ser 308) were analyzed using the western blot analysis. Finally, the experimental results shown that Ginsenoside Rg5 significantly inhibited hypoxia-induced NRMs apoptosis, decreased the expression pro-apoptotic protein Bax, increased the expression of anti-apoptotic protein Bcl-2 ratio and the level of cleaved caspase 3. Akt signaling activation was found to be the mechanism of Ginsenoside Rg5s protective effect on hypoxia-induced NRMs apoptosis, as an Akt inhibitor eliminated the anti-apoptotic effects of Ginsenoside Rg5. Various analyses were performed and verified, ginsenoside Rg5 suppressed hypoxia-induced apoptosis in NRMs via activation of the Akt signaling.

Inflammation, dysregulated iron metabolism, and cardiovascular disease

Iron is an essential trace element associated with both pathologic deficiency and toxic overload. Thus, systemic and cell iron metabolism are highly controlled processes regulated by protein expression and localization, as well as turnover, through the action of cytokines and iron status. Iron metabolism in the heart is challenging because both iron overload and deficiency are associated with cardiac disease. Also associated with cardiovascular disease is inflammation, as many cardiac diseases are caused by or include an inflammatory component. In addition, iron metabolism and inflammation are closely linked. Hepcidin, the master regulator of systemic iron metabolism, is induced by the cytokine IL-6 and as such is among the acute phase proteins secreted by the liver as part of the inflammatory response. In an inflammatory state, systemic iron homeostasis is dysregulated, commonly resulting in hypoferremia, or low serum iron. Less well characterized is cardiac iron metabolism in general, and even less is known about how inflammation impacts heart iron handling. This review highlights what is known with respect to iron metabolism in the heart. Expression of iron metabolism-related proteins and processes of iron uptake and efflux in these cell types are outlined. Evidence for the strong co-morbid relationship between inflammation and cardiac disease is also reviewed. Known connections between inflammatory processes and iron metabolism in the heart are discussed with the goal of linking inflammation and iron metabolism in this tissue, a connection that has been relatively under-appreciated as a component of heart function in an inflammatory state. Therapeutic options connecting inflammation and iron balance are emphasized, with the main goal of this review being to bring attention to alterations in iron balance as a component of inflammatory diseases of the cardiovascular system.

Knockdown of ATF3 suppresses the progression of ischemic stroke through inhibiting ferroptosis

Objective

Current therapies towards ischemic stroke (IS) are still not satisfied, and alternative strategies targeting ferroptosis may be another choice. The purpose of this study is to screen potential ferroptosis-related genes involving in IS.

Methods

A rat model of IS was established via middle cerebral artery occlusion. Differentially expressed genes (DEGs) were screened from the model rats through transcriptional sequencing. Among the isolated DEGs, the expression of several attractive DEGs relating with ischemic injury was confirmed by qRT-PCR. Then, ATF3 relating with both IS and ferroptosis was selected a candidate gene for functional assays. After knockdown of ATF3 in the model rats, the infarction, histopathology, apoptosis, and ferroptosis in brain tissues were evaluated.

Results

IS model was successfully established in rats, exhibiting the emergence of infarction area, histopathological injury, and enhanced cell apoptosis. Total 699 up-regulated DEGs and 461 down-regulated DEGs were screened from the model rats. qRT-PCR verified the up-regulation of Hspa1b, Tfpi2, Ptx3, and Atf3, and the down-regulation of Smyd1 and Tacr2 in the Model group compared with those in the Sham group. It is noteworthy that knockdown of ATF3 decreased the infarction area, relieved histopathological injury, weakened apoptosis, and inhibited ferroptosis in the model rats.

Conclusion

Several candidate genes in relation with IS were revealed. More importantly, knockdown of ATF3 may relieve IS through inhibiting ferroptosis.

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

Background

Coronary artery disease (CAD) is a complex illness with unknown pathophysiology. Peripheral biomarkers are a non-invasive method required to track the onset and progression of CAD and have unbeatable benefits in terms of early identification, prognostic assessment, and categorization of the diagnosis. This study aimed to identify and validate the diagnostic and therapeutic potential of differentially expressed immune-related genes (DE-IRGs) in CAD, which will aid in improving our knowledge on the etiology of CAD and in forming genetic predictions.

Methods

First, we searched coronary heart disease in the Gene Expression Omnibus (GEO) database and identified GSE20680 (CAD = 87, Normal = 52) as the trial set and GSE20681 (CAD = 99, Normal = 99) as the validation set. Functional enrichment analysis using protein-protein interactions (PPIs), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) was carried out on the identified differentially expressed genes. Optimal feature genes (OFGs) were generated using the support vector machine recursive feature elimination algorithm and the least absolute shrinkage and selection operator (LASSO) algorithm. Furthermore, immune infiltration in CAD patients and healthy controls was compared using CIBERSORT, and the relationship between immune cells and OFGs was examined. In addition, we constructed potential targeted drugs for this model through the Drug-Gene Interaction database (DGIdb) database. Finally, we verify the expression of S100A8-dominated OFGs in the GSE20681 dataset to confirm the universality of our study.

Results

We identified the ten best OFGs for CAD from the DE-IRGs. Functional enrichment analysis showed that these marker genes are crucial for receptor-ligand activity, signaling receptor activator activity, and positive control of the response to stimuli from the outside world. Additionally, CIBERSORT revealed that S100A8 could be connected to alterations in the immune microenvironment in CAD patients. Furthermore, with the help of DGIdb and Cytoscape, a total of 64 medicines that target five marker genes were subsequently discovered. Finally, we verified the expression of the OFGs genes in the GSE20681 dataset between CAD patients and normal patients and found that there was also a significant difference in the expression of S100A8.

Conclusion

We created a 10-gene immune-related prognostic model for CAD and confirmed its validity. The model can identify potential biomarkers for CAD prediction and more accurately gauge the progression of the disease.

Effects of Ferroptosis on Cardiovascular Diseases

Ferroptosis is a novel form of programmed cell death characterized by the accumulation of iron-dependent lipid peroxides, which causes membrane injury. Under the catalysis of iron ions, cells deficient in glutathione peroxidase (GPX4) cannot preserve the balance in lipid oxidative metabolism, and the buildup of reactive oxygen species on the membrane lipids leads to cell death. An increasing body of evidence suggests that ferroptosis plays a significant role in the development and occurrence of cardiovascular diseases. In this paper, we mainly elaborated on the molecular mechanisms regulating ferroptosis and its impact on cardiovascular disease to lay the groundwork for future studies on the prophylaxis and treatment of this patient population.

Construction of the ceRNA network in the progression of acute myocardial infarction

Acute myocardial infarction (AMI) is a common disease that induced by sudden occlusion of a coronary artery and myocardial necrosis, which causes a great medical burden worldwide. Noncoding RNAs, such as circRNA, lncRNA and miRNA, play crucial roles in the progression of cardiovascular diseases. However, the circRNA-miRNA-mRNA network in the occurrence and development of AMI needs further investigation. In this study, we downloaded three AMI datasets, including circRNA (GSE160717), miRNA (GSE24591), and mRNA (GSE66360) from GEO database. The differentially expressed candidates, and GO and KEGG functions were analyzed by RStudio, and subsequently import to PPI and Cytoscape to obtain the hub genes. By using the starbase target prediction database, we further screen the ceRNA network of circRNA-miRNA-mRNA based on the selected differentially expressed candidates. We found 46 differential expressed mRNAs, 65 miRNAs, and five circRNAs. GO functions and KEGG enrichment of the 46 mRNAs focused on immune response and functions, involving IL-17 signaling pathway, Toll-like receptor signaling pathway, cytokine-cytokine receptor interaction, TNF signaling pathway, chemokine signaling pathway, and NF-kappaB signaling pathway, which may aggravate the pathologies of AMI. PPI and Cytoscape analysis showed 10 hub genes, including TLR2, IL1B, CCL4, CCL3, CCR5, TREM1, CXCL2, NLRP3, CSF3, and CCL20. By using starbase and circinteractome databases, ceRNA network construction showed that circRNA_023461 and circRNA_400027 regulate several miRNA-mRNA axes in AMI. In summary, this study uncovered the circRNA-miRNA-mRNA network based on three AMI datasets. The differentially expressed genes, including CCL20, CCL4, CSF3, and IL1B, focus on immune functions and pathways. Furthermore, circRNA_023461 and circRNA_400027 regulate several miRNA-mRNA axes, exerting important roles in AMI progression. Our founding provides new insights into AMI and improve the therapeutic strategies for AMI.

Angiotensin receptor-neprilysin inhibitor attenuates ischemia-hypoxia-induced myocardial injury via inhibition of autophagy

OBJECTIVES

Angiotensin receptor-neprilysin inhibitor (ARNI) improves cardiac function and protects from an ischemic myocardium. However, the role and mechanism of ARNI on autophagy in cardiac ischemic injury are poorly understood. Here, we investigated the protective effect and underlying mechanisms of ARNI on autophagy in H9c2 cardiomyocytes induced through ischemia and hypoxia (IH) treatment.

METHODS

The cytotoxicity of IH injury on H9C2 cells with and without ARNI were evaluated using cell counting kit-8 (CCK-8) and lactate dehydrogenase (LDH) release assays. The effect of ARNI on apoptosis was detected using flow cytometry. The expression of autophagic proteins (LC3-II, Beclin 1, and p62) was detected using western blot.

RESULTS

The viability of H9c2 cells was significantly decreased at different IH-treated time points; ARNI pretreatment increased cell viability and inhibited IH injury in a dose-dependent manner. H9c2 cells treated with IH (6 h) significantly increased LDH release, while ARNI dose-dependently improved LDH release, with 20 μmol/L ARNI having the most significant effect. ARNI also ameliorated IH-induced apoptosis. IH treatment increased the protein expression of LC3-II and Beclin 1 and decreased the expression of p62, which were reversed by ARNI pretreatment. Furthermore, autophagy was further increased after pretreatment with rapamycin in IH-induced H9c2 cells, which abrogated the protective effect of ARNI.

CONCLUSIONS

Our study shows that ARNI has a protective effect on IH-induced cardiomyocyte injury, which may be related to the inhibition of autophagy.

Identification and exploration of novel M2 macrophage-related biomarkers in the development of acute myocardial infarction

Background

Acute myocardial infarction (AMI), one of the most severe and fatal cardiovascular diseases, is a major cause of morbidity and mortality worldwide. Macrophages play a critical role in ventricular remodeling after AMI. The regulatory mechanisms of the AMI progression remain unclear. This study aimed to identify hub regulators of macrophage-related modules and provide translational experiments with potential therapeutic targets.

Materials and methods

The GSE59867 dataset was downloaded from the Gene Expression Omnibus (GEO) database for bioinformatics analysis. The expression patterns of 22 types of immune cells were determined using CIBERSORT. GEO2R was used to identify differentially expressed genes (DEGs) through the limma package. Then, DEGs were clustered into different modules, and relationships between modules and macrophage types were analyzed using weighted gene correlation network analysis (WGCNA). Further functional enrichment analysis was performed using significantly associated modules. The module most significantly associated with M2 macrophages (Mϕ2) was chosen for subsequent analysis. Co-expressed DEGs of AMI were identified in the GSE123342 and GSE97320 datasets and module candidate hub genes. Additionally, hub gene identification was performed in GSE62646 dataset and clinical samples.

Results

A total of 8,760 DEGs were identified and clustered into ten modules using WGCNA analysis. The blue and turquoise modules were significantly related to Mϕ2, and 482 hub genes were discerned from two hub modules that conformed to module membership values > 0.8 and gene significance values > 0.25. Subsequent analysis using a Venn diagram assessed 631 DEGs in GSE123342, 1457 DEGs in GSE97320, and module candidate hub genes for their relationship with Mϕ2 in the progression of AMI. Finally, four hub genes (CSF2RB, colony stimulating factor 2 receptor subunit beta; SIGLEC9, sialic acid-binding immunoglobulin-like lectin 9; LRRC25, leucine-rich repeat containing 25; and CSF3R, colony-stimulating factor-3 receptor) were validated to be differentially expressed and to have high diagnostic value in both GSE62646 and clinical samples.

Conclusion

Using comprehensive bioinformatics analysis, we identified four novel genes that may play crucial roles in the pathophysiological mechanism of AMI. This study provides novel insights into the impact of macrophages on the progression of AMI and directions for Mϕ2-targeted molecular therapies for AMI.

Integrative analysis identifies potential ferroptosis-related genes of hypoxia adaptation in yak

There are studies on the hypoxia adaptation in yak, but there are few studies on the regulation of ferroptosis by hypoxia. This study was the first time to explore ferroptosis-related genes about hypoxia in yak. In this study, the oviduct epithelial cells between yak and bovine are performed by integrative analysis for functions, regulating network and hub genes. The results showed 29 up-regulated ferroptosis genes and 67 down-regulated ferroptosis genes, and GO-KEGG analysis showed that up-regulated differentially expressed genes (DEGs) were significantly enriched in ribosome pathway and oxidative phosphorylation pathway. Down-regulated DEGs were significantly enriched in longevity regulating pathway-mammal pathway. Mitophagy-Animal Pathway was a significant enrichment pathway for the up-regulated differentially expressed ferroptosis genes (DE-FRGs). HIF-1 signaling pathway is a significant pathway for the down-regulated DE-FRGs. By constructing DE-FRGs protein-protein interaction (PPI) network, 10 hub DE-FRGs (Jun, STAT3, SP1, HIF1A, Mapk1, Mapk3, Rela, Ulk1, CDKN1A, EPAS1) were obtained. The bta-mir-21-5p, bta-mir-10a and bta-mir-17-5p related to STAT3 were predicted. The results of this study indicated the important genes and pathways of the hypoxia in yak, and it was the first time to study ferroptosis genes and pathways related to the hypoxia adaptation by bulk-seq in yak. This study provided sufficient transcriptome datas for hypoxia adaptation.

Potential biomarkers for predicting the overall survival outcome of kidney renal papillary cell carcinoma: an analysis of ferroptosis-related LNCRNAs

Background

Kidney renal papillary cell carcinoma (KIRP) is a dangerous cancer, which accounts for 15–20% of all kidney malignancies. Ferroptosis is a rare kind of cell death that overcomes medication resistance. Ferroptosis-related long non-coding RNAs (LNCRNAs) in KIRP, remain unknown.

Method

We wanted to express how ferroptosis-related LNCRNAs interact with immune cell infiltration in KIRP. Gene set enrichment analysis in the GO and KEGG databases were used to explore gene expression enrichment. The prognostic model was constructed using Lasso regression. In addition, we also analyzed the modifications in the tumor microenvironment (TME) and immunological association.

Result

The expression of LNCRNA was closely connected to the ferroptosis, according to co-expression analyses. CASC19, AC090197.1, AC099850.3, AL033397.2, LINC00462, and B3GALT1-AS1 were found to be significantly increased in the high-risk group, indicating that all of these markers implicates the malignancy processes for KIRP patients and may be cancer-promoting variables. LNCTAM34A and AC024022.1 were shown to be significantly elevated in the low-risk group; these might represent as the KIRP tumor suppressor genes. According to the TCGA, CCR, and inflammation-promoting genes were considered to be significantly different between the low-risk and high-risk groups. The expression of CD160, TNFSF4, CD80, BTLA, and TNFRSF9 was different in the two risk groups.

Conclusion

LNCRNAs associated with ferroptosis were linked to the occurrence and progression of KIRP. Ferroptosis-related LNCRNAs and immune cell infiltration in the TME may be potential biomarkers in KIRP that should be further investigated.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12894-022-01037-0.

The underlying pathological mechanism of ferroptosis in the development of cardiovascular disease

Cardiovascular diseases (CVDs) have been attracting the attention of academic society for decades. Numerous researchers contributed to figuring out the core mechanisms underlying CVDs. Among those, pathological decompensated cellular loss posed by cell death in different kinds, namely necrosis, apoptosis and necroptosis, was widely regarded to accelerate the pathological development of most heart diseases and deteriorate cardiac function. Recently, apart from programmed cell death revealed previously, ferroptosis, a brand-new cellular death identified by its ferrous-iron-dependent manner, has been demonstrated to govern the occurrence and development of different cardiovascular disorders in many types of research as well. Therefore, clarifying the regulatory function of ferroptosis is conducive to finding out strategies for cardio-protection in different conditions and improving the prognosis of CVDs. Here, molecular mechanisms concerned are summarized systematically and categorized to depict the regulatory network of ferroptosis and point out potential therapeutic targets for diverse cardiovascular disorders.

The Identification and Validation of Hub Genes Associated with Acute Myocardial Infarction Using Weighted Gene Co-Expression Network Analysis

Acute myocardial infarction (AMI), one of the most severe and fatal cardiovascular diseases, remains the main cause of mortality and morbidity worldwide. The objective of this study is to investigate the potential biomarkers for AMI based on bioinformatics analysis. A total of 2102 differentially expressed genes (DEGs) were screened out from the data obtained from the gene expression omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) explored the co-expression network of DEGs and determined the key module. The brown module was selected as the key one correlated with AMI. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses demonstrated that genes in the brown module were mainly enriched in ‘ribosomal subunit’ and ‘Ribosome’. Gene Set Enrichment Analysis revealed that ‘TNFA_SIGNALING_VIA_NFKB’ was remarkably enriched in AMI. Based on the protein–protein interaction network, ribosomal protein L9 (RPL9) and ribosomal protein L26 (RPL26) were identified as the hub genes. Additionally, the polymerase chain reaction (PCR) results indicated that the expression levels of RPL9 and RPL26 were both downregulated in AMI patients compared with controls, in accordance with the bioinformatics analysis. In summary, the identified DEGs, modules, pathways, and hub genes provide clues and shed light on the potential molecular mechanisms of AMI.

Identification of key molecular markers of acute coronary syndrome using peripheral blood transcriptome sequencing analysis and mRNA-lncRNA co-expression network construction

Acute coronary syndrome (ACS) is a term used to describe major cardiovascular diseases, and treatment of in-stent restenosis in patients with ACS remains a major clinical challenge. Further investigation into molecular markers of ACS may aid early diagnosis, and the treatment of ACS and post-treatment recurrence. In the present study, total RNA was extracted from the peripheral blood samples of 3 patients with ACS, 3 patients with percutaneous coronary intervention (PCI)_non-restenosis, 3 patients with PCI_restenosis and 3 healthy controls. Subsequently, RNA library construction and high-throughput sequencing were performed. DESeq2 package in R was used to screen genes that were differentially expressed between the different samples. Moreover, the intersection of the differentially expressed mRNAs (DEmRNAs) and differentially expressed long noncoding RNAs (DElncRNAs) obtained. GeneCodis4.0 was used to perform function enrichment for DEmRNAs, and lncRNA-mRNA co-expression network was constructed. The GSE60993 dataset was utilized for diagnostic analysis, and the aforementioned investigations were verified using in vitro studies. Results of the present study revealed a large number of DEmRNAs and DElncRNAs in the different groups. We selected genes in the top 10 of differential expression and also involved in the co-expression of lncRNA-mRNA for diagnostic analysis in the GSE60993 dataset. The area under curve (AUC) of PDZK1IP1 (0.747), PROK2 (0.769) and LAMP3 (0.725) were all >0.7. These results indicated that the identified mRNAs and lncRNAs may act as potential clinical biomarkers, and more specifically, PDZK1IP1, PROK2 and LAMP3 may act as potential biomarkers for the diagnosis of ACS.