Interaction Network Analysis Research Articles

Perfluorooctane sulfonic acid: a possible risk factor of endothelial dysfunction based on in silico and in vitro studies.

Perfluorooctane sulfonic acid (PFOS) is a fluorinated chemical utilized in a variety of industrial and household products. PFOS has been detected in human serum and is associated with multiple human adverse health effects. Epidemiological evidence has linked PFOS exposure to endothelial dysfunction, which is a key contributor to atherosclerosis. However, the underlying mechanisms of PFOS-induced endothelial dysfunction associated atherosclerosis has not been investigated. In the present study, human microvascular endothelial cells (HMEC-1) exposed to PFOS (15μM) for 72h, mimicking long-term exposure. We further employed integrated RNA-sequencing (RNA-seq) and transcriptomic analysis to identify differentially expressed genes (DEGs) for biological alterations: gene ontology (GO), pathway enrichment analysis (KEGG), protein-protein interaction network and modular clustering analysis. Furthermore, the Metascape database was used for disease association, tissue specificity, and transcription factor analysis. Hub genes were verified using atherosclerosis patient data sets from the GEO dataset. Alteration of hub genes in patients was then validated using immunoblotting and ELISA. Our results revealed that PFOS altered amino acid biosynthesis, lipid metabolism and induced the ER-stress response through the HRI/eIF2α/ATF4 pathway, leading to endothelial dysfunction. Interestingly, we found that PFOS induced inflammation by increasing COX-2, ICAM-1 and IL-6 expression through NF-κB and JAK2/STAT3 pathway in endothelial cells. Moreover, up-regulated C/EBPβ and ATF4 were observed in both patients and PFOS-exposed endothelium, which may use as an early biomarker and may have a potential role in PFOS-induced endothelial dysfunction. These findings provide novel insight into the underlying molecular mechanisms of PFOS-induced endothelial dysfunction associated with atherosclerosis.

Preliminary exploration of the potential role of salvianolic acid F in regulating ovarian cancer cell proliferation, migration, invasion, and apoptosis and its association with the EP300/PI3K/AKT pathway.

Salvianolic acid F (SAF), an important water-soluble monomeric component, is derived from the herbal medicine Salvia miltiorrhiza (SM) Bunge. Although SAF has been suggested to suppress various cancers, its role in ovarian cancer (OC) and the underlying mechanisms remain largely unclear. This study aimed to investigate the effects of SAF on OC cell growth, invasion, migration, and apoptosis, as well as to elucidate the underlying mechanisms, including those involving the EP300/PI3K/AKT signaling pathway. In vitro cell culture experiments were conducted to assess the effects of SAF on the proliferation, migration, invasion, and apoptosis of OVCAR-3 (Ovarian Cancer Cell Line 3) and SK-OV-3 (Sloan-Kettering Ovarian Cancer 3) cells. Network pharmacology was further employed to explore SAF's impact on OC and to elucidate the potential underlying mechanisms. The EP300-mediated PI3K/AKT signaling pathway was selected for validation to confirm SAF's effects on inducing apoptosis and inhibiting cell proliferation in these OC cell lines. Salvianolic acid F suppressed the growth, invasion and migration of SK-OV-3 and OVCAR-3 cells, and induced apoptosis. A network pharmacology analysis of SAF's effects on OC identified core targets, TP53, EP300, STAT3, MMP9, NFKB1, HIF1A, and PTGS2, through protein-protein interaction (PPI) network analysis using the STRING database. Salvianolic acid F inhibited EP300 expression in SK-OV-3 cells, reduced the p-PI3K/PI3K ratio, and increased both the Bax/Bcl-2 ratio and the cleaved caspase-3/caspase-3 ratio in OVCAR-3 and SK-OV-3 cells. However, the addition of A485, an EP300 inhibitor, did not further enhance the effects of SAF. Salvianolic acid F inhibited OC cell growth, migration and invasion while promoting apoptosis. The EP300/PI3K/AKT pathway is a key mechanism through which SAF regulates OC progression. Additionally, SAF may represent a promising candidate drug for treating OC.

Proteomic analysis of liver fibrosis reveals EFEMP1 as a new modulator of focal adhesion and migration of hepatic stellate cells.

Liver fibrosis is characterized by an excessive accumulation of extracellular matrix (ECM) leading to liver dysfunction. Proteomic approaches help to decipher ECM alterations during fibrosis progression. Using a decellularization method, we performed a proteomic analysis of 18 fibrotic human liver samples and identified 106 deregulated ECM proteins. Three members of the fibulin protein family (fibulin-2, -3, and -5) expressed by hepatic stellate cells were significantly associated with fibrosis progression. Integrative analyses of protein-protein interaction networks highlighted different functional annotations for these three fibulins. Gene silencing studies showed that unlike fibulin-2 (FBLN2), fibulin-3 (EFEMP1) depletion impaired focal adhesions, FAK phosphorylation, the fibronectin network, and cell migration. These findings are the first to demonstrate the critical involvement of fibulin-3 in the regulation of hepatic stellate cell focal adhesions and migration, emphasizing the intricate link between chronic liver disease progression and remodeling of the microenvironment.

Identification of CDKN1A as a potential key risk factor in MASLD progression.

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously referred to as non-alcoholic fatty liver disease (NAFLD), is recognized as a highly heterogeneous condition. The elusive mechanisms driving its progression contribute to the lack of reliable diagnostic markers and effective treatments. In this study, we first identified 52 differentially expressed genes (DEGs) in MASLD stage by analyzing two public datasets, GSE126848 and GSE135251, using the DESeq2 and edgeR packages. Subsequently, these DEGs were subjected to protein-protein interaction (PPI) network analysis, revealing the top 10 hub genes. By intersecting the top 10 hub genes with another public dataset GSE260222, we observed that CDKN1A was the sole gene consistently upregulated in the livers of MASLD patients across all analyses. The elevated protein expression of CDKN1A was further validated in the livers of MASLD patients compared to control subjects. Consistently, compared to their respective control groups, both CDKN1A mRNA and protein levels were dramatically increased in the livers of MASLD animal models, including high-fat diet (HFD) induced obese mice, leptin-deficient obese (ob/ob) mice and leptin receptor-deficient (db/db) mice, and in mouse primary hepatocytes treated with free fatty acids (FFA), respectively. Interestingly, we found that CDKN1A transcript levels were progressively and significantly increased with the severity of MASLD in four out of five datasets and positively correlated with both the NAFLD activity score (NAS) and fibrosis stage, two important clinicopathological features of MASLD. Collectively, our results illustrated that CDKN1A may serve as a promising biomarker and therapeutic target for MASLD; however, its role in the disease's pathology warrants further investigation.

Germline variants in patients from the Iranian hereditary colorectal cancer registry

Background and aimHereditary cancer syndromes account for 6–10% of all colorectal cancer (CRC) cases and 20% of early-onset CRC. Identifying novel pathogenic germline variants can impact genetic testing, counseling, and surveillance. This study aimed to determine the prevalence of germline variants associated with hereditary CRC in the Iranian population.MethodsWhole exome sequencing (WES) was conducted on DNA from 101 patients in the Iranian Hereditary Colorectal Cancer Registry (IHCCR). The cohort included 63 high-risk Lynch Syndrome (LS) patients and 38 colorectal polyposis patients. Germline variants and phenotype spectrum were assessed. Relatives of individuals with the mutations received counseling and cascade testing. Gene ontology and protein-protein interaction (PPI) analyses were conducted to elucidate gene roles on protein function.ResultsPathogenic/likely pathogenic (P/LP) variants were identified in Lynch-related genes in 36.51% of patients. P/LP variants in non-Lynch genes (ATM, FH (mono-allelic), MSH3, PMS1, and TP53) were identified in 26.98% of patients. Among polyposis patients, 50% had P/LP variants in the APC gene, and 15.79% had P/LP variants in the MUTYH gene. Additionally, 7.89% carried P/LP variants in non-FAP/MAP genes (BLM, BRCA2, and PTEN). MLH1 variants were most common in exons 10 and 18, MSH2 in exon 12, and APC gene in exon 16. Cascade testing identified 50% of the tested relatives (40/80). Topology analysis of the protein-protein interaction networks in high-risk LS cases highlighted stronger connections among nodes for genes such as TP53, ATM, POLD1, CDH1, MUTYH, WRN, NOTCH1, SMAD4, ERCC4, ERCC1, and MSH3. These genes were associated with high penetrance in CRC. The protein-protein interaction analyses of polyposis patients indicated that genes like POLE, MSH6, MSH2, BRCA2, BRCA1, MLH1, TOPBP1, BLM, RAD50, MUTYH, MSH3, MLH3, PTEN, BRIP1, and POLK had a higher degree value and were also associated with high penetrance. Gene ontology and protein-protein interaction (PPI) analysis showed that some of the top-scoring non-Lynch genes were TP53, ATM, POLD1, CDH1, MUTYH, WRN, NOTCH1, SMAD4, ERCC4, ERCC1, and MSH3.ConclusionsThe study identified crucial germline variants for hereditary polyposis and non-polyposis CRC pathogenesis in the Iranian population. A selective strategy and cascade genetic testing are recommended for the diagnosis of hereditary colorectal cancer syndromes.

KPNA2 promotes osteosarcoma progression by regulating the alternative splicing of DDX3X mediated by YBX1.

Osteosarcoma (OS) is a rapidly progressive primary malignant bone tumor that occurs in children and adolescents aged between 15 and 19 years and adults aged over 60 years. As alternative splicing (AS) changes caused by abnormal splicing factors contribute to tumor progression, gene expression and AS analyses were performed on 44 osteosarcoma patients to create a genome-wide co-expression network of RNA-binding proteins (RBPs), AS events, and AS genes. A gain- or loss-of-function osteosarcoma cell model was established, and an interactive network analysis and enrichment analysis were performed. Karyopherin Subunit Alpha 2 (KPNA2) negatively correlated with patient survival. KPNA2 transports splicing factor Y-box Binding Protein 1 (YBX1) into the nucleus and YBX1 accelerates the degradation of the ATP-dependent RNA helicase DDX3X (DDX3X) through the nonsense-mediated decay (NMD) pathway to promote intron retention of the DDX3X gene, thus reducing DDX3X protein levels. KPNA2/YBX1 axis regulates the stability of DDX3X mRNA and cell cycle progression. KPNA2/YBX1/DDX3X axis might be potential targets for inhibiting disease progression and improving OS patient survival. It integrates AS control of DDX3X into the progression of OS and represents a potential prognostic biomarker and therapeutic target for OS therapy.

NUF2 and NEK2 promote malignant progression of gallbladder cancer by remodeling the extracellular matrix.

Gallbladder cancer (GBC) ranks as the most common malignant tumor of the biliary tract, which has been characterized by late diagnosis, low excisional rate, and poor prognosis. Recent studies exploring the roles of malignant progression associated genes in GBC remain limited. Our study aims to identify significant hub genes involved in its pathogenesis, which may serve as novel potential therapeutic targets for GBC. Here, we employed RNA-seq analysis to identify differentially expressed genes (DEGs) of 7 GBC samples and 5 matched adjacent samples. After screening the DEGs in clinical sequencing data and GSE139682, we further obtained 549 genes with consistent expression trend in two datasets, including 155 upregulated and 394 downregulated genes. Gene Ontology (GO) enrichment analysis revealed that these genes were significantly enriched in extracellular matrix (ECM) related processes, such as organization, structure, and composition, which hint us that remodeling of ECM may be the main driving factor for the malignant progression of GBC. Additionally, we screened 17 candidate hub genes through protein-protein interaction (PPI) network analysis and Cytoscape, subsequent GO and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that the remodeled ECM mainly functions by affecting cell division. Moreover, we found that NEK2 and NUF2 were overexpressed in GBC tumor tissues and validated their function in pro-proliferation of GBC cell. Our results highlight that NEK2 and NUF2 may be hub genes promoting the malignant progression of GBC and are expected to be reliable new therapeutic targets for GBC.

Exploring the Potential of Dolutegravir in Alzheimer's Disease Treatment: Insights from Network Pharmacology and In Silico Docking Studies.

The search for effective treatments for neurodegenerative diseases, particularly Alzheimer's disease, has been fraught with challenges. Alzheimer's disease accounts for 60-80% of dementia cases globally, affecting approximately about 50 million people. Currently, drug repurposing has emerged as a promising strategy in new drug development, attracting significant attention from regulatory agencies, such as the US FDA. This study aimed to investigate the potential therapeutic role of dolutegravir in Alzheimer's disease (AD) treatment using a novel network pharmacology approach. Specifically, it explored the interaction of dolutegravir with key molecular targets involved in AD pathology, predicted its effects on relevant biological pathways, and evaluated its viability as a new therapeutic candidate. This study employed a network pharmacology framework to evaluate dolutegravir, an antiretroviral drug, as a potential treatment for Alzheimer's disease, shedding light on its possible therapeutic mechanisms. A network pharmacology approach was used to predict the drug targets of dolutegravir. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to identify interacting pathways. Additionally, protein- protein interaction (PPI) network analysis was conducted to assess key interactions and molecular docking studies were performed to evaluate the binding affinity of dolutegravir to the predicted targets. PPI network analysis revealed that dolutegravir interacted with several key targets, including BRAF, mTOR, MAPK1, MAPK3, NOS1, BACE1, CAPN1, CASP3, CASP7, CASP8, CHUK, IKBKB, PIK3CA, and PIK3CD. KEGG pathway analysis suggested that dolutegravir could influence amyloid-beta formation, amyloid precursor protein metabolism, and the cellular response to amyloid-beta. Molecular docking results showed the highest binding affinity of dolutegravir for PI3KCD (-8.5 kcal/mol) and MTOR (-8.7 kcal/mol). The findings indicated that dolutegravir holds significant potential in modulating key pathways involved in Alzheimer's disease pathogenesis. These results provide a strong foundation for further investigations into the therapeutic efficacy and safety of dolutegravir in the treatment of Alzheimer's disease. The use of drug repurposing strategies, leveraging Dolutegravir's established pharmacological profile, offers a promising route for accelerated therapeutic development in AD.

Analysis of hemolysis-associated acute myeloid leukemia genes obtained using weighted gene co-expression network analysis and a Mendelian randomization study

PurposeWe used bioinformatics methods and Mendelian randomization (MR) analysis to investigate the hub genes involved in acute myeloid leukemia (AML) and their causal relationship with hemolysis, to explore a new direction for molecular biology research of AML.MethodsWe first differentially analyzed peripheral blood samples from 62 healthy volunteers and 65 patients with AML from the Gene Expression Omnibus database to obtain differentially expressed genes (DEGs), and intersected them with genes sourced from weighted gene co-expression network analysis (WGCNA) and the GeneCards database to obtain target genes. Target genes were screened using protein–protein interaction (PPI) network analysis and ROC curves to identify genes associated with AML. Finally, we analyzed the correlation between genes and immune cells and the relationship between toll-like receptor 4 (TLR4) and AML using MR.ResultsWe compared peripheral blood expression profiles using an array of 62 healthy volunteers (GSE164191) and 65 patients with AML (GSE89565) (M0:25; M1:11; M2:10; M3:1; M4:7; M4 eo t [16;16] ou inv [16]:4; M5:6; M6:1) and obtained 7,339 DEGs (3,733 upregulated and 3,606 downregulated). We intersected these DEGs with 4,724 genes from WGCNA and 1,330 genes related to hemolysis that were identified in the GeneCards database to obtain 190 target genes. After further screening these genes using the PPI network, we identified TLR4, PTPRC, FCGR3B, STAT1, and APOE, which are closely associated with hemolysis in patients with AML. Finally, we found a causal relationship between TLR4 and AML occurrence using MR analysis (p < 0.05).ConclusionWe constructed a WGCNA-based co-expression network and identified hemolysis-associated AML genes.

Molecular typing of gliomas on the basis of integrin family genes and a functional study of ITGA7

Gliomas are highly malignant tumors of the central nervous system, and their complex molecular heterogeneity poses major therapeutic challenges. Integrins are important members of the class of cell adhesion molecules (CAMs), consisting of α-subunits and β-subunits that form 24 different heterodimers. To elucidate the complex role of integrins in glioma pathogenesis, we analyzed integrin family genes. We used a scoring system based on gene set enrichment analysis (GSEA) to identify prognostic biomarkers and nonnegative matrix factorization (NMF) to establish a new integrin-based molecular classification of gliomas. Subsequent analyses of the clinical relevance of the molecular subtypes and the underlying mechanisms demonstrated a strong correlation between integrin-based molecular subtypes and glioma malignancy. We further characterized the different clinical features and tumor microenvironments (TMEs) associated with these subtypes. We identified subtype-specific driver genes using the limma R package and weighted gene coexpression network analysis (WGCNA). We subsequently identified key integrin-mediated genes that significantly contribute to poor prognosis through a combined approach of machine learning (ML) and protein‒protein interaction (PPI) network analysis. Finally, we performed in vitro cellular experiments on the integrin family gene ITGA7 and demonstrated that ITGA7 can serve as a biomarker for gliomas. Our findings provide important insights into the multifaceted roles of integrins in glioma biology, provide an opportunity for the discovery of novel targeted therapies on the basis of the subtype-specific vulnerability of integrins, and provide a basis for the study of the role of ITGA7 in gliomas.

Identification and validation of pyroptosis patterns in AML via comprehensive bioinformatics analysis

Pyroptosis, a lytic inflammatory cell death mechanism, plays dual roles in tumorigenesis, but its clinical relevance in acute myeloid leukemia (AML) remains poorly understood. Through an integrative analysis of 40 pyroptosis-related genes in newly diagnosed AML patients (TCGA, n = 151) and healthy controls (GTEx, n = 386), we identified 32 genes with aberrant expression. Among these, 9 genes were found to be significant prognostic markers, including ELANE (protective), and CASP1, CHMP4B, BAK1, and CHMP2A (risk), which retained their prognostic significance after adjusting for age and gender. Using unsupervised nonnegative matrix factorization (NMF) on TCGA data, we classified AML into two pyroptosis patterns: the ELANEhigh subtype, associated with favorable survival, and the ELANElow subtype, which was enriched in poor karyotypes and adverse outcomes. This classification was validated in an independent cohort (GSE10358, n = 91). Single-cell RNA sequencing data (GSE116256, n = 15) revealed that the ELANElow subtype is characterized by an immunologically active microenvironment, marked by an expansion of cytotoxic T cells and naive CD4 + /CD8 + T cells. Factor analysis revealed associations between pyroptosis patterns and other forms of cell death, including ferroptosis, autophagy, and apoptosis, as well as with karyotype, leukemia stemness, and TP53/FLT3-ITD mutations. Prognostic immune gene sets enriched in the ELANElow subtype were associated with interferon signaling and ubiquitin-mediated degradation pathways. Furthermore, protein–protein interaction (PPI) network analysis identified three sub-networks and nine key hub genes. This study integrates gene expression data from newly diagnosed AML patients, revealing the heterogeneity of pyroptosis patterns within the population. It highlights the potential links between distinct pyroptosis patterns, the immune microenvironment, various cell death pathways, leukemia stemness, and genomic alterations, offering novel biomarkers and therapeutic targets for risk stratification and immunomodulatory interventions in AML.

A network pharmacology approach and experimental validation to investigate the neuroprotective mechanism of quercetin against alcoholic brain injury via the JNK/P38 MAPK signaling pathway.

A network pharmacology approach and experimental validation to investigate the neuroprotective mechanism of quercetin against alcoholic brain injury via the JNK/P38 MAPK signaling pathway.

Network Pharmacology and Molecular Dynamics Identified Potential Androgen Receptor-Targeted Metabolites in Crocus alatavicus

The objective of this study is to identify the active components of Crocus alatavicus and potential targets through a combination of network pharmacology, molecular docking technology combined with molecular dynamics simulation, and binding free energy analyses. A total of 253 active ingredients from C. alatavicus were screened, and 1360 associated targets were predicted through systematic searches conducted using TCMSP, SwissDrugDesign, and SymMap, which were integrated to construct a pharmacological network to dissect the relationships among active components, targets, diseases, and pathways; we found prostate cancer-related genes were significantly enriched among the targets. Subsequently, the core prostate cancer-related targets were identified in the network, and the binding interactions between protein targets and active components were evaluated using molecular docking technology. Furthermore, molecular dynamics simulation and binding free energy analyses were performed to verify the binding stability of the most promising complex. Then, protein–protein interaction network analysis was conducted to evaluate the core target sites, leading to the identification of nine target proteins with significant correlations, providing potential targets for cancer treatment. Furthermore, these targets were found to be associated with 20 signaling pathways, including neuroactive ligand–receptor interactions, prostate cancer, lipid metabolism and atherosclerosis, as well as calcium signaling pathways. The active component–target–disease–pathway network diagram suggests that Capillarisin, Eugenol, 1-(4-Methoxyphenyl)-1-propanol, 2,4,2′,4′-tetrahydroxy-3′-prenylchalcone, and 4-Hydroxymandelonitrile may serve as key components targeting prostate cancer. Molecular docking analyses demonstrated that Capillarisin has a high affinity for the androgen receptor (AR), and molecular dynamics simulation was performed to further verify the binding stability, indicating that Capillarisin may exert its pharmacological effects in prostate cancer. Based on the integrated strategies of network pharmacology, molecular docking, molecular dynamics simulation, and binding free energy analysis, this study generated novel insights into the active components of C. alatavicus and potential targets related to prostate cancer, thus providing valuable biological resources for future drug research and development.

Advances in the chemical synthesis of human proteoforms.

Access to structurally-defined human proteoforms is essential to the biochemical studies on human health and medicine. Chemical protein synthesis provides a bottom-up and atomic-resolution approach for the preparation of homogeneous proteoforms bearing any number of post-translational modifications of any structure, at any position, and in any combination. In this review, we summarize the development of chemical protein synthesis, focusing on the recent advances in synthetic methods, product characterizations, and biomedical applications. By analyzing the chemical protein synthesis studies on human proteoforms reported to date, this review demonstrates the significant methodological improvements that have taken place in the field of human proteoform synthesis, especially in the last decade. Our analysis shows that although further method development is needed, all the human proteoforms could be within reach in a cost-effective manner through a divide-and-conquer chemical protein synthesis strategy. The synthetic proteoforms have been increasingly used to support biomedical research, including spatial-temporal studies and interaction network analysis, activity quantification and mechanism elucidation, and the development and evaluation of diagnostics and therapeutics.

Exploration of the shared gene signatures and molecular mechanisms between cardioembolic stroke and ischemic stroke

IntroductionThis study aimed to investigate the shared molecular mechanisms underlying cardioembolic stroke (CS) and ischemic stroke (IS) using integrated bioinformatics analysis.MethodsMicroarray datasets for the CS (GSE58294, blood samples from CS and controls) and IS (GSE16561, blood from IS and controls; GSE22255, peripheral blood mononuclear cells from IS and matched controls) were acquired from the Gene Expression Omnibus database. Differential expression analysis and weighted gene co-expression network analysis were utilized to identify shared genes between the two diseases. Protein-protein interaction (PPI) network and topology analyses were conducted to identify the core shared genes. Three machine learning algorithms were employed to detect biomarkers from the core shared genes, and the diagnostic value of the hub genes was evaluated by establishing a predictive nomogram. Immune infiltration was evaluated using single-sample gene set enrichment analysis (ssGSEA), and pathways were analyzed with gene set enrichment analysis.ResultsThere were 125 shared up-regulated genes and 2 shared down-regulated between CS and IS, which were mainly involved in immune inflammatory response-related biological functions. The Maximum Clique Centrality algorithm identified 25 core shared genes in the PPI network constructed using the shared genes. ABCA1, CLEC4E, and IRS2 were identified as biomarkers for both CS and IS and performed well in predicting the onset risk of CS and IS. All three biomarkers were highly expressed in both CS and IS compared to their corresponding controls. These biomarkers significantly correlated with neutrophil infiltration and autophagy activation in both CS and IS. Particularly, all three biomarkers were associated with the activation of neutrophil extracellular trap formation, but only in the IS.ConclusionABCA1, CLEC4E, and IRS2 were identified as potential key biomarkers and therapeutic targets for CS and IS. Autophagy and neutrophil infiltration may represent the common mechanisms linking these two diseases.

Scouting Biomarkers for Alzheimer’s Disease via Network Analysis of Exosome Proteomics Data

Background: Exosomes are a group of extracellular vesicles that are released by almost all mammalian cell types and engage in intracellular communication. Studies conducted in recent years have shown that exosomes are involved in a variety of diseases, where they may act as “vehicles” for the transmission of biomolecules and biomolecular information. Amyloidoses constitute a critical subgroup of these diseases, caused by extracellular deposition or intracellular inclusions of insoluble protein fibrils in cells and tissues. However, how exosomes are involved in these diseases remains largely unexplored. Methods: To detect possible links between amyloid proteins and exosomes, protein data from amyloidosis-isolated exosomes were collected and visualized using biological networks. Results: This biomedical informatics approach for the analysis of interaction networks, in combination with the existing literature, highlighted the involvement of exosomes in amyloidosis while strengthening existing hypotheses regarding their mechanism of action. Conclusion: This work is focused on exosomes from patients with Alzheimer’s disease and identifies important amyloidogenic proteins found in exosomes. These proteins can be used for future research in the field of exosome-based biomarkers of amyloidosis and potential prognostic or preventive approaches.

Evaluating the role of astragalus polysaccharide in modulating immune infiltration and enhancing prognostic biomarkers in pediatric acute myeloid leukemia

BackgroundChildhood acute myeloid leukemia (AML) constitutes a significant proportion of pediatric malignancies, with current treatment options remaining limited. This study aimed to investigate the role of Astragalus polysaccharide (APS) in immune infiltration and prognosis of pediatric AML.MethodsDifferentially expressed genes (DEGs) were identified from the GEO database (dataset GSE2191), and APS-related genes (APSRGs) were obtained from the Swiss Target Prediction platform. DEGs with |logFC| &amp;gt; 1 and p &amp;lt; 0.05 were intersected with APSRGs to identify APS-related differentially expressed genes (APSRDEGs), visualized using a Venn diagram. A protein-protein interaction (PPI) network analysis was conducted to identify hub genes. Gene Ontology (GO) and KEGG enrichment analyses were performed to determine biological processes (BP), cellular components (CC), molecular functions (MF), and relevant pathways associated with the hub genes. Correlation analysis, receiver operating characteristic (ROC) curve analysis, and immune infiltration analysis were conducted to assess the relationship between hub genes and pediatric AML.ResultsThe GSE2191 dataset was divided into pediatric AML (PAML) and control groups. A total of 1,881 DEGs were identified, of which 20 were APSRDEGs. PPI network analysis revealed that 13 APSRDEGs were interconnected, and nine hub genes were identified: CASP3, PTPRC, ELANE, HMOX1, CHUK, FLT1, JAK3, CTSL, and AURKA. GO and KEGG enrichment analyses indicated that these genes were significantly associated with key biological processes, cellular components, molecular functions, and pathways involved in AML. ROC curve analysis revealed that the expression levels of the nine hub genes differed significantly between the PAML and control groups. Immune infiltration analysis demonstrated a strong correlation between several hub genes and immune cells, with HMOX1 showing the strongest positive correlation with neutrophils.ConclusionThis study identified nine hub genes related to APS in pediatric AML. These findings suggest that APS may significantly affect immune infiltration and prognosis in pediatric AML, highlighting its potential as a therapeutic modulator for the disease.

Identification of endothelial cell key genes associated with pathogenesis and invasion of human venous malformations using single-nucleus RNA sequencing-based co-expression network analysis

Objective: This study aimed to identify key genes in endothelial cell (EC) associated with the pathogenesis and progression of human venous malformations (VMs) through bioinformatics analysis, providing potential biomarkers for early screening and targeted therapy of VMs. Methods: A case-control study was conducted using surgically resected tissue specimens from VMs patients at the Third Affiliated Hospital of Zhengzhou University (from September 2021 to September 2023), with malformed venous tissues as the experimental group and distal normal venous tissues as controls. Single-nucleus RNA sequencing (snRNA-seq) was performed on paired experimental and control samples from four VM patients. High-dimensional weighted gene co-expression network analysis (hdWGCNA), combined with gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), and protein-protein interaction (PPI) network analysis, identified critical genes. Validation experiments included 15 additional VM cases and controls using reverse transcription quantitative polymerase chain reaction (RT-qPCR), immunohistochemistry (IHC), and Western blot. Results: A total of 55 430 nuclei were captured using snRNA-seq, with 30 391 nuclei from the experimental group and 25 039 nuclei from the control group. Cluster analysis identified 22 distinct cell populations, which were annotated into 8 cell types. hdWGCNA revealed four modules associated with invasion, which were enriched in angiogenesis, integrin signaling, and cell adhesion according to GO analysis. KEGG pathway analysis indicated that the PI3K-AKT signaling pathway and focal adhesion are key regulatory mechanisms. PPI network analysis combined with cytoscape identified EGFL7, TEK, and FLT1 as key genes. RT-qPCR results demonstrated that the relative mRNA expression levels of these three genes in the experimental group (6.66±2.31, 1.86±0.62, 3.49±0.58) were significantly higher than those in the control group (1.05±0.14, 1.00±0.14, 1.06±0.25), with statistically significant differences (t=9.37, 4.27, 11.20, P<0.05). Immunohistochemical analysis showed that the relative protein expression levels of these three genes in the cytoplasm of the experimental group (0.84±0.15, 0.68±0.14, 0.85±0.12) were also significantly higher than those in the control group (0.19±0.05, 0.23±0.06, 0.30±0.05), with statistically significant differences (t=16.62, 5.93, 11.68, P<0.05). Western blot analysis confirmed that the relative protein expression levels of these three genes in the experimental group (0.35±0.04, 0.36±0.09, 0.31±0.04) were significantly higher than those in the control group (0.19±0.01, 0.13±0.02, 0.14±0.04), with statistically significant differences (t=7.05, 4.61, 5.93, P<0.05). Conclusion: EGFL7, FLT1, and TEK in EC may play crucial roles in the occurrence and invasion of VMs.

Cytotoxic Effect of Escitalopram/Etoposide Combination on Etoposide-Resistant Lung Cancer

Background: Antidepressants are a class of pharmaceuticals utilized for the management of many psychiatric disorders, including depression. A considerable number of antidepressants, particularly selective serotonin reuptake inhibitors (SSRIs), have been documented to demonstrate significant anticancer properties in various cancer cell lines. Objectives: The aim of this study was to evaluate the selective cytotoxic and apoptotic effects of escitalopram oxalate (ES) alone and in combination with etoposide (ET) on ET-resistant A549 (A549/90E) lung cancer cells. Methods: The cytotoxic effects of the drugs were determined by CCK-8, trypan blue, and neutral red assays. Apoptosis was observed by Annexin V fluorescein isothiocyanate (FITC)/PI and mitochondrial membrane potential (ΔΨm) assays. Moreover, the effects of the drugs, alone and in combination, on apoptosis-related proteins, caspase-3, PTEN, and resistance-related P-gP were determined by ELISA. The relationship between drugs and lung cancer was determined with protein–protein interaction (PPI) network analysis. Results: Our results revealed that ES significantly exerted cytotoxic effects on both wild-type and A549/90E cells compared with BEAS-2B cells. The IC50 values of 48.67 and 51.6 μg/mL obtained for ET and ES, respectively, at the end of 24 h of incubation for A549 cells were applied reciprocally for each cell by including BEAS-2B together with the 2xIC50 and ½ IC50 values. The results of each combination were statistically evaluated with combination indices (CIs) obtained using the Compusyn synergistic effect analysis program. Combination doses with a synergistic effect in A549 and A549/90E cells and an antagonistic effect in BEAS-2B cells have been determined as ½ IC50 for ET and ½ IC50 for ES. ET ½ IC50, ES ½ IC50, and an ET ½ IC50 + ES ½ IC50 combination caused 18.37%, 55.19%, and 57.55% death in A549 cells, whereas they caused 44.9%, 22.4%, and 51.94% death in A549/90E cells, respectively. In A549 cells, the combination of ES ½ IC50 and ET ½ IC50 caused increased levels of caspase-3 (p &lt; 0.01) and P-gP (p &lt; 0.001), while PTEN levels remained unchanged. The combination resulted in an increase in caspase-3 (p &lt; 0.001) and PTEN (p &lt; 0.001) amounts, alongside a decrease in P-gP (p &lt; 0.01) levels in A549/90E cells. The death mechanism induced by the combination was found to be apoptotic by Annexin V-FITC and ΔΨm assays. Conclusions: Based on our findings, ES was observed to induce cytotoxic and apoptotic activities in A549/90E cells in vitro. ES in combination therapy is considered to be effective to overcome ET resistance by reducing the amount of P-gP in A549/90E cells.

Screening and identification analysis of core markers for leukemia and cervical cancer: Calmodulin 3 as a core target.

Leukemia is a type of malignant tumor affecting hematopoietic system. Cervical cancer is a malignant tumor of female reproductive tract. The relationship between Calmodulin 3 (CALM3) and leukemia, cervical cancer remains unclear. Leukemia dataset GSE26294 and cervical cancer dataset GSE173097 profiles were downloaded from gene expression omnibus. Principal component analysis, differentially expressed genes (DEGs) screening, weighted gene co-expression network analysis (WGCNA), functional enrichment analysis, gene set enrichment analysis, immune infiltration analysis, protein-protein interaction network construction and analysis, survival analysis were performed. Gene expression heatmaps were plotted. Comparative Toxicogenomics Database (CTD) was used to find diseases most related to core genes. 77 DEGs were identified. According to gene ontology, in biological process category, they were mainly enriched in cell proliferation, immune response, and apoptotic process. In cellular component category, they were mainly enriched in nucleus and Golgi apparatus. In molecular function category, they were mainly enriched in DNA binding, protein binding, transcription factor activity. In Kyoto encyclopedia of gene and genome analysis, they were mainly enriched in cell adhesion molecules, Wnt signaling pathway, cAMP signaling pathway, cGMP-PKG signaling pathway, and basal cell carcinoma. The soft-threshold power in WGCNA was set to 1, generating 6 modules. Finally identifying 3 core genes (CALM3, secreted frizzled-related protein 4, plasminogen). CTD analysis revealed that core genes were related to leukemia, coagulation disorders, vaginal tumors, cervical tumors, autoimmune diseases, and inflammation. CALM3 is lowly expressed in leukemia samples and highly expressed in cervical cancer samples.