Kyoto Encyclopedia Of Genes And Genomes Pathway Analysis Research Articles

Identification and Verification of Endoplasmic Reticulum Stress-Related Genes as Novel Signatures for Osteoarthritis Diagnosis and Therapy: A Bioinformatics Analysis-Oriented Pilot Study.

Endoplasmic reticulum stress (ERS) has been reported to be closely associated with the development of osteoarthritis (OA), but the underlying mechanisms are not fully delineated. The present study was designed to investigate the involvement of ERS-related genes in regulating OA progression. The expression profiles of OA patients and normal people were downloaded from the gene expression omnibus (GEO) database. The differentially expressed genes (DEGs) in datasets GSE55457 and GSE55235 were screened and identified by R software with the construction of the protein-protein interaction (PPI) networks. Through the STRING and Venn diagram analysis, hub ERS-related genes were obtained. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses were performed. Biomarkers with high diagnostic values of osteoarthritis (OA) were studied. The hematoxylin and eosin (H&E) staining and micro-CT were applied to evaluate the establishment of the OA model. The expression levels of biomarkers were validated with the use of reverse transcription‑quantitative polymerase chain reaction (RT-qPCR) and western blot. Finally, we evaluated the correlations of hub ERS-related genes with the immune infiltration cells via the CIBERSORT algorithm. A total of 60 downregulated and 52 upregulated DEGs were identified, and the following GO and KEGG pathway analyses verified that those DEGs were mainly enriched in biological process (BP), cellular component (CC), molecular function (MF), and inflammation-associated signal pathways. Interestingly, among all the DEGs, six ER stress-associated genes, including activating transcription factor 3 (ATF3), DEAD-Box Helicase 3 X-Linked (DDX3X), AP-1 transcription factor subunit (JUN), eukaryotic initiation factor 4 (EIF4A1), KDEL endoplasmic reticulum protein retention receptor 3 (KDELR3), and vascular endothelial growth factor A (VEGFA), were found to be closely associated with OA progression, and the following RT-qPCR and Western Blot analysis confirmed that DDX3X, JUN, and VEGFA were upregulated, whereas KDELR3, EIF4A1, and ATF3 were downregulated in OA rats tissues compared to the normal tissues, which were in accordance with our bioinformatics findings. Furthermore, our receiver operating characteristic (ROC) curve analysis verified that the above six ER stress-associated genes could be used as ideal biomarkers for OA diagnosis and those genes also potentially regulated immune responses by influencing the biological functions of mast cells and macrophages. Collectively, the present study firstly identified six ER stress-associated genes (ATF3, DDX3X, JUN, EIF4A1, KDELR3, and VEGFA) that may play critical role in regulating the progression of OA.

Identification and coregulation pattern analysis of long noncoding RNAs in the mouse brain after Angiostrongylus cantonensis infection

BackgroundAngiostrongyliasis is a highly dangerous infectious disease. Angiostrongylus cantonensis larvae migrate to the mouse brain and cause symptoms, such as brain swelling and bleeding. Noncoding RNAs (ncRNAs) are novel targets for the control of parasitic infections. However, the role of these molecules in A. cantonensis infection has not been fully clarified.MethodsIn total, 32 BALB/c mice were randomly divided into four groups, and the infection groups were inoculated with 40 A. cantonensis larvae by gavage. Hematoxylin and eosin (H&E) staining and RNA library construction were performed on brain tissues from infected mice. Differential expression of long noncoding RNAs (lncRNAs) and mRNAs in brain tissues was identified by high-throughput sequencing. The pathways and functions of the differentially expressed lncRNAs were determined by Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses. The functions of the differentially expressed lncRNAs were further characterized by lncRNA‒microRNA (miRNA) target interactions. The potential host lncRNAs involved in larval infection of the brain were validated by quantitative real-time polymerase chain reaction (qRT‒PCR).ResultsThe pathological results showed that the degree of brain tissue damage increased with the duration of infection. The transcriptome results showed that 859 lncRNAs and 1895 mRNAs were differentially expressed compared with those in the control group, and several lncRNAs were highly expressed in the middle–late stages of mouse infection. GO and KEGG pathway analyses revealed that the differentially expressed target genes were enriched mainly in immune system processes and inflammatory response, among others, and several potential regulatory networks were constructed.ConclusionsThis study revealed the expression profiles of lncRNAs in the brains of mice after infection with A. cantonensis. The lncRNAs H19, F630028O10Rik, Lockd, AI662270, AU020206, and Mexis were shown to play important roles in the infection of mice with A. cantonensis infection.Graphical

Integrating Bulk RNA and Single-Cell Sequencing Data Unveils Efferocytosis Patterns and ceRNA Network in Ischemic Stroke.

Excessive inflammatory response following ischemic stroke (IS) injury is a key factor affecting the functional recovery of patients. The efferocytic clearance of apoptotic cells within ischemic brain tissue is a critical mechanism for mitigating inflammation, presenting a promising avenue for the treatment of ischemic stroke. However, the cellular and molecular mechanisms underlying efferocytosis in the brain after IS and its impact on brain injury and recovery are poorly understood. This study explored the roles of inflammation and efferocytosis in IS with bioinformatics. Three Gene Expression Omnibus Series (GSE) (GSE137482-3m, GSE137482-18m, and GSE30655) were obtained from NCBI (National Center for Biotechnology Information) and GEO (Gene Expression Omnibus). Differentially expressed genes (DEGs) were processed for GSEA (Gene Set Enrichment Analysis), GO (Gene Ontology Functional Enrichment Analysis), and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analyses. Efferocytosis-related genes were identified from the existing literature, following which the relationship between Differentially Expressed Genes (DEGs) and efferocytosis-related genes was examined. The single-cell dataset GSE174574 was employed to investigate the distinct expression profiles of efferocytosis-related genes. The identified hub genes were verified using the dataset of human brain and peripheral blood sample datasets GSE56267 and GSE122709. The dataset GSE215212 was used to predict competing endogenous RNA (ceRNA) network, and GSE231431 was applied to verify the expression of differential miRNAs. At last, the middle cerebral artery (MCAO) model was established to validate the efferocytosis process and the expression of hub genes. DEGs in two datasets were significantly enriched in pathways involved in inflammatory response and immunoregulation. Based on the least absolute shrinkage and selection operator (LASSO) analyses, we identified hub efferocytosis-related genes (Abca1, C1qc, Ptx3, Irf5, and Pros1) and key transcription factors (Stat5). The scRNA-seq analysis showed that these hub genes were mainly expressed in microglia and macrophages which are the main cells with efferocytosis function in the brain. We then identified miR-125b-5p as a therapeutic target of IS based on the ceRNA network. Finally, we validated the phagocytosis and clearance of dead cells by efferocytosis and the expression of hub gene Abca1 in MCAO mice models.

Lipoic acid alters the microRNA signature in breast cancer cells

BackgroundBreast cancer, the deadliest disease affecting women globally, exhibits heterogeneity with distinct molecular subtypes. Despite advances in cancer therapy, the persistence of high mortality rates due to chemotherapy resistance remains a major challenge. Lipoic acid (LA), a natural antioxidant, has proven potent anticancer properties. Yet, the impact of LA on microRNA (miRNA) expression profile in breast cancer remains unexplored. AimThe aim of this study was to unravel the effect of LA on miRNA expression profiles in different breast cancer cell lines. MethodsThe MiRCURY LNA miRNA miRNome qPCR Panel was used to compare the miRNA signature in MDA-MB-231 and MCF-7 cells treated or not with LA. ResultsWe identified six upregulated and six downregulated miRNAs in LA-treated MDA-MB-231 cells and 14 upregulated and four downregulated miRNAs in LA-treated MCF-7 cells compared to control cells. KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis revealed that the deregulated miRNAs could alter different signaling cascades including FoxO, P53 and Hippo pathways. ConclusionThe outcome of this study provides further insights into the molecular mechanisms underlying the therapeutic benefit of LA. This in turn could assist the amelioration of LA-based anticancer therapies.

Research on the Mechanism of Traditional Chinese Medicine Treatment for Diseases caused by Human Coronavirus COVID-19

Background: Human coronaviruses are a large group of viruses that exist widely in nature and multiply through self-replication. Due to its suddenness and variability, it poses a great threat to global human health and is a major problem currently faced by the medical and health fields. background: Human coronaviruses are a large group of viruses that exist widely in nature and multiply through self-replication. Due to its suddenness and variability, it poses a great threat to global human health and is a major problem currently faced by the medical and health fields. Objective: COVID-19 is the seventh known coronavirus that can infect humans. The main purpose of this paper is to analyze the effective components and action targets of the Longyi Zhengqi formula and Lianhua Qingwen formula, study their mechanism of action in the treatment of new coronavirus pneumonia (new coronavirus pneumonia), compare the similarities and differences of their pharmacological effects, and obtain the pharmacodynamic mechanism of the two traditional Chinese medicine compounds. Method: Obtain the effective ingredients and targets of Longyi-Zhengqi Formula and Lianhua- Qingwen Formula from ETCM (Encyclopedia of Traditional Chinese Medicine) and other traditional Chinese medicine databases, use GeneCards database to obtain the relevant targets of COVID-19, and use Cytoscape software to build the component COVID-19 target network of Longyi-Zhengqi Formula and the component COVID-19 target network of Lianhua-Qingwen Formula. STRING was used to construct a protein interaction network and screen key targets. GO (Gene Ontology) was used for enrichment analysis and KEGG (Kyoto Encyclopedia of Genes and Genomes) was used for pathways to find out the targets and pathways related to the treatment of COVID-19. Results: In the GO enrichment analysis results, there are 106 biological processes, 31 cell localization and 28 molecular functions of the intersection PPI network targets of Longyi-Zhengqi Formula- COVID-19, 224 biological processes, 51 cell localization and 55 molecular functions of the intersection PPI network targets of Lianhua-Qingwen Formula-COVID-19. In the KEGG pathway analysis results, the number of targets of Longyi-Zhengqi Formula on the COVID-19 pathway is 7, and the number of targets of Lianhua-Qingwen Formula on the COVID-19 pathway is 19; In the regulation analysis results, Longyi-Zhengqi Formula achieves the effect of treating COVID-19 by regulating IL-6, and Lianhua-Qingwen Formula achieves the effect of treating pneumonia by regulating TLR4. Conclusion: This paper explores the mechanism of action of Longyi-Zhengqi Formula and Lianhua-Qingwen Formula in treating COVID-19 based on the method of network pharmacology, and provides a theoretical basis for traditional Chinese medicine to treat sudden diseases caused by human coronavirus in terms of drug targets and disease interactions. It has certain practical significance.

Construction of an immune-related gene signature for overall survival prediction and immune infiltration in gastric cancer.

Treatment options for patients with gastric cancer (GC) continue to improve, but the overall prognosis is poor. The use of PD-1 inhibitors has also brought benefits to patients with advanced GC and has gradually become the new standard treatment option at present, and there is an urgent need to identify valuable biomarkers to classify patients with different characteristics into subgroups. To determined the effects of differentially expressed immune-related genes (DEIRGs) on the development, prognosis, tumor microenvironment (TME), and treatment response among GC patients with the expectation of providing new biomarkers for personalized treatment of GC populations. Gene expression data and clinical pathologic information were downloaded from The Cancer Genome Atlas (TCGA), and immune-related genes (IRGs) were searched from ImmPort. DEIRGs were extracted from the intersection of the differentially-expressed genes (DEGs) and IRGs lists. The enrichment pathways of key genes were obtained by analyzing the Kyoto Encyclopedia of Genes and Genomes (KEGGs) and Gene Ontology (GO) databases. To identify genes associated with prognosis, a tumor risk score model based on DEIRGs was constructed using Least Absolute Shrinkage and Selection Operator and multivariate Cox regression. The tumor risk score was divided into high- and low-risk groups. The entire cohort was randomly divided into a 2:1 training cohort and a test cohort for internal validation to assess the feasibility of the risk model. The infiltration of immune cells was obtained using 'CIBERSORT,' and the infiltration of immune subgroups in high- and low-risk groups was analyzed. The GC immune score data were obtained and the difference in immune scores between the two groups was analyzed. We collected 412 GC and 36 adjacent tissue samples, and identified 3627 DEGs and 1311 IRGs. A total of 482 DEIRGs were obtained. GO analysis showed that DEIRGs were mainly distributed in immunoglobulin complexes, receptor ligand activity, and signaling receptor activators. KEGG pathway analysis showed that the top three DEIRGs enrichment types were cytokine-cytokine receptors, neuroactive ligand receptor interactions, and viral protein interactions. We ultimately obtained an immune-related signature based on 10 genes, including 9 risk genes (LCN1, LEAP2, TMSB15A mRNA, DEFB126, PI15, IGHD3-16, IGLV3-22, CGB5, and GLP2R) and 1 protective gene (LGR6). Kaplan-Meier survival analysis, receiver operating characteristic curve analysis, and risk curves confirmed that the risk model had good predictive ability. Multivariate COX analysis showed that age, stage, and risk score were independent prognostic factors for patients with GC. Meanwhile, patients in the low-risk group had higher tumor mutation burden and immunophenotype, which can be used to predict the immune checkpoint inhibitor response. Both cytotoxic T lymphocyte antigen4+ and programmed death 1+ patients with lower risk scores were more sensitive to immunotherapy. In this study a new prognostic model consisting of 10 DEIRGs was constructed based on the TME. By providing risk factor analysis and prognostic information, our risk model can provide new directions for immunotherapy in GC patients.

Molecular network mechanism in cerebral ischemia-reperfusion rats treated with human urine stem cells

ObjectiveTo explore the effect of human urine-derived stem cells (husc) in improving the neurological function of rats with cerebral ischemia-reperfusion (CIR), and report new molecular network by bioinformatics, combined with experiment validation. MethodsAfter CIR model was established, and husc were transplanted into the lateral ventricle of rats，neurological severe score (NSS) andgene network analysis were performed. Firstly, we input the keywords “Cerebral reperfusion” and “human urine stem cells” into Genecard database and merged data with findings from PubMed so as to get their targets genes, and downloaded them to make Venny intersection plot. Then, Gene ontology (GO) analysis, kyoto encyclopedia of genes and genomes (KEGG) pathway analysis and protein-protein interaction (PPI) were performed to construct molecular network of core genes. Lastly, the expressional level of core genes was validated via quantitative real-time polymerase chain reaction (qRT-PCR), and localized by immunofluorescence. ResultsCompared with the Sham group, the neurological function of CIR rats was significantly improved after the injection of husc into the lateral ventricle; at 14 days, P = 0.028, which was statistically significant. There were 258 overlapping genes between CIR and husc, and integrated with 252 genes screened from PubMed and CNKI. GO enrichment analysis were mainly involved neutrophil degranulation, neutrophil activation in immune response and platelet positive regulation of degranulation, Hemostasis, blood coagulation, coagulation, etc. KEGG pathway analysis was mainly involved in complement and coagulation cascades, ECM-receptor. Hub genes screened by Cytoscape consist ofCD44, ACTB, FN1, ITGB1, PLG, CASP3, ALB, HSP90AA1, EGF, GAPDH. Lastly, qRT-PCR results showed statistic significance (P < 0.05) in ALB, CD44 and EGF before and after treatment, and EGF immunostaining was localized in neuron of cortex. Conclusionhusc transplantation showed a positive effect in improving neural function of CIR rats, and underlying mechanism is involved in CD44, ALB, and EGF network.

Identifying critical genes and pathways of doxorubicin-induced cardiomyopathy via bioinformatics analysis.

The pathogenesis of doxorubicin (DOX) induced cardiomyopathy (DCM) is still uncertain. We aimed to identify the critical genes and pathways involved in DCM based on bioinformatics analysis. The GSE59672 and GSE23598 mice heart tissue microarray data were obtained from Gene Expression Omnibus (GEO) database. The "limma" package of R software was used to screen the differently expressed genes (DEGs). GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses were performed on DEGs by using "clusterProfiler" package in R software. The PPI (Protein - Protein Interaction) network of DEGs constructed by STRING online database and thereby the top 15 hub genes selected by cytoHubba in Cytoscape software. The hub genes interaction was performed by GeneMANIA online database. The "Corrplot" R package was employed to assess hub genes correlation. Finally, a total of 492 and 501 DEGs were screened in GSE59672 and GSE23598 datasets, respectively. GO analyses revealed that DEGs were mainly involved in the regulation of extracellular matrix organization, metabolic process, regulation of collagen-containing extracellular matrix. KEGG pathway analyses indicated that DEGs were mainly involved in protein digestion and absorption, ECM-receptor interaction, phagosome, and p53 signaling pathway. Finally, the 8 hub genes were identified, including Col1a1, Col3a1, Col1a2, Col6a1, Ptprc, Tyrobp, Itgb2, and Ctss. The present study identified a series of key genes, including Col1a1, Col3a1, Col1a2, Col6a1, Ptprc, Tyrobp, Itgb2, and Ctss. In addition, important pathways were also discovered. The results of this study may provide a novel molecular mechanism and potential therapeutic targets for DCM.

Molecular mechanisms of quetiapine bidirectional regulation of bipolar depression and mania based on network pharmacology and molecular docking: Evidence from computational biology

BackgroundQuetiapine monotherapy is recommended as the first-line option for acute mania and acute bipolar depression. However, the mechanism of action of quetiapine is unclear. Network pharmacology and molecular docking were employed to determine the molecular mechanisms of quetiapine bidirectional regulation of bipolar depression and mania. MethodsPutative target genes for quetiapine were collected from the GeneCard, SwissTargetPrediction, and DrugBank databases. Targets for bipolar depression and bipolar mania were identified from the DisGeNET and GeneCards databases. A protein-protein interaction (PPI) network was generated using the String database and imported into Cytoscape. DAVID and the Bioinformatics platform were employed to perform the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of the top 15 core targets. The drug-pathway-target-disease network was constructed using Cytoscape. Finally, molecular docking was performed to evaluate the interactions between quetiapine and potential targets. ResultsTargets for quetiapine actions against bipolar depression (126 targets) and bipolar mania (81 targets) were identified. Based on PPI and KEGG pathway analyses, quetiapine may affect bipolar depression by targeting the MAPK and PI3K/AKT insulin signaling pathways via BDNF, INS, EGFR, IGF1, and NGF, and it may affect bipolar mania by targeting the neuroactive ligand-receptor interaction signaling pathway via HTR1A, HTR1B, HTR2A, DRD2, and GRIN2B. Molecular docking revealed good binding affinity between quetiapine and potential targets. LimitationsPharmacological experiments should be conducted to verify and further explore these results. ConclusionsOur findings suggest that quetiapine affects bipolar depression and bipolar mania through distinct biological core targets, and thus through different mechanisms. Furthermore, our results provide a theoretical basis for the clinical use of quetiapine and possible directions for new drug development.

Impact of Protein Phosphatase Expressions on the Prognosis of Hepatocellular Carcinoma Patients.

The study was conducted to unveil the significance of protein phosphatases in the prognosis of hepatocellular carcinoma (HCC) patients and its related molecular biological attributes as well as to discover novel potential biomarkers for therapeutic significance and diagnostic purposes that may benefit clinical practice. Analyzing a data set from 159 HCC patients using high-throughput phosphoproteomics, we examined the dysregulated expression of protein phosphatases. Employing bioinformatic and pathway analyses, we explored differentially expressed genes linked to protein phosphatases. A protein-protein interaction network was constructed using the search tool for the retrieval of interacting genes/proteins database. We quantified a total of 11,547 phosphorylation sites associated with 4043 phosphoproteins from HCC patients. Within this data set, we identified 105 identified phosphorylation sites associated with protein phosphatases; 28 genes were upregulated and 3 were downregulated in HCC. Enriched pathways using Gene Set Enrichment Analysis encompassed oocyte meiosis, proteoglycans in cancer, the oxytocin signaling pathway, the cGMP-PKG signaling pathway, the vascular smooth muscle, and the cAMP signaling pathway. The Kyoto encyclopedia of genes and genomes (KEGG) analysis highlighted pathways like mitogen-activated protein kinase, AMPK, and PI3K-Akt, indicating potential involvement in HCC progression. Notably, the PPI network identified hub genes, emphasizing their interconnections and potential roles in HCC. In our study, we found significantly upregulated levels of CDC25C, PPP1R13L, and PPP1CA, which emerge as promising avenues. This significant expression could serve as potent diagnostic and prognostic markers to enhance the effectiveness of HCC cancer treatment, offering efficiency and accuracy in patient assessment. The findings regarding protein phosphatases reveal their elevated expression in HCC, correlating with unfavorable prognosis. Moreover, the outcomes of gene ontology and KEGG pathway analyses suggest that protein phosphatases may influence liver cancer by engaging diverse targets and pathways, ultimately fostering the progression of HCC. These results underscore the substantial potential of protein phosphatases as key contributors to HCC's development and advancement. This insight holds promise for identifying therapeutic targets and charting research avenues to enhance the comprehension of the intricate molecular mechanisms underpinning HCC.

The potential role of differentially expressed tRNA-derived fragments in high glucose-induced podocytes

The prevalence of diabetic kidney disease (DKD) is increasing annually. Damage to and loss of podocytes occur early in DKD. tRNA-derived fragments (tRFs), originating from tRNA precursors or mature tRNAs, are associated with various illnesses. In this study, tRFs were identified, and their roles in podocyte injury induced by high-glucose (HG) treatment were explored. High-throughput sequencing of podocytes treated with HG was performed to identify differentially expressed tRFs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. The expression levels of nephrin, podocin, and desmin were measured in podocytes after overexpression of tRF-1:24-Glu-CTC-1-M2 (tRF-1:24) and concomitant HG treatment. A total of 647 tRFs were identified, and 89 differentially expressed tRFs (|log2FC| ≥ 0.585; p ≤ .05) were identified in the HG group, of which 53 tRFs were downregulated and 36 tRFs were upregulated. The 10 tRFs with the highest differential expression were detected by real-time quantitative polymerase chain reaction (RT-qPCR), and these results were consistent with the sequencing results. GO analysis revealed that the biological process, cellular component, and molecular function terms in which the tRFs were the most enriched were cellular processes, cellular anatomical entities, and binding. KEGG pathway analysis revealed that tRFs may be involved in signaling pathways related to growth hormones, phospholipase D, the regulation of stem cell pluripotency, and T-/B-cell receptors. Overexpression of tRF-1:24, one of the most differentially expressed tRFs, attenuated podocyte injury induced by HG. Thus, tRFs might be potential biomarkers for podocyte injury in DKD.

Introducing Pain-Related Molecular Pathways in Painful Diabetic Neuropathy Via Protein Interaction Networks

Background: Painful diabetic neuropathy (PDN) is one of the most drastic complications of diabetes. Patients with PDN always reveal spontaneous and stimulus‑evoked pain. However, the pathogenesis mechanisms of PDN are not entirely distinct. Objectives: In the present study protein-protein interaction (PPI) network for PDN was constructed and analyzed to identify key proteins as potential biomarker candidates. Methods: The transcriptomic (genes) and proteomic (proteins) data in articles that focused on PDN with differential expressions were collected. Protein networks were constructed and analyzed using STRING and Cytoscape software, respectively. Further PPI network analysis, gene ontology, and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis were performed using MCODE and DAVID tools. Results: A total of 147 differentially regulated proteins/genes were identified in painful diabetic neuropathy, including 91 up-regulated and 56 down-regulated proteins/genes. A network analysis of genes/proteins related to PDN identified COX4I1, NDUFS8, UQCRC1, COX7C, and some other NADH dehydrogenases, including NDUFB7, NDUFS7, NDUFS3, NDUFB5, NDUFA2, and NDUFB4 as hub-bottleneck proteins. With functional enrichment analysis of network clustering, COX7C, HP, RPS12, KCNIP2, and CoL4A1 were established as distinct seed proteins in the obtained modules, which could lead to the discovery of biomarker candidates. Conclusions: These results could provide new insights into pathology and molecular mechanisms, as well as the identification of pathways and proteins/genes involved in causing PDN in diabetic patients. COX7C, HP, RPS12, KCNIP2, and CoL4A1 are the top 5 seed nodes (hub proteins) and can serve as potential biomarker candidates and targets for PDN management. However, further investigations are needed to evaluate these proteins in detail.

Exploring the mechanism of action of Sparganii Rhizoma-Curcumae Rhizoma for in treating castration-resistant prostate cancer: a network-based pharmacology and experimental validation study

Sparganii Rhizoma-Curcumae Rhizoma (SR-CR) is a classic drug pair for the treatment of castration-resistant prostate cancer (CRPC), but its mechanism has not been clarified. The study aims to elucidate the potential mechanism of SR-CR in the management of CRPC. The present study employed the TCMSP as well as the SwissTargetPrediction platform to retrieve the chemical composition and targets of SR-CR. The therapeutic targets of CRPC were identified through screening the GeneCards, Disgenet, and OMIM databases. Subsequently, the Venny online platform was utilized to identify the shared targets between the SR-CR and CRPC. The shared targets were enrichment analysis using the Bioconductor and Kyoto encyclopedia of genes and genomes (KEGG) databases. The active ingredients and core targets were verified through molecular docking and were validated using PC3 cells in the experimental validation phase. A total of 7 active ingredients and 1126 disease targets were screened from SR-CR, leading to a total of 59 shared targets. Gene Ontology (GO) analysis resulted in 1309 GO entries. KEGG pathways analysis yielded 121 pathways, primarily involving cancer-related signaling pathways. The results from molecular docking revealed stable binding interactions between the core ingredients and the core targets. In vitro cellular assays further demonstrated that SR-CR effectively suppressed the activation of the Prostate cancer signaling pathway in PC3 cells, leading to the inhibition of cell proliferation and promotion of apoptosis. The SR-CR exert therapeutic effects on CRPC by inhibiting cell proliferation and promoting apoptosis through the Prostate cancer signaling pathway.

Underlying Mechanism of Traditional Herbal Formula Chuang-Ling-Ye in the Treatment of Diabetic Foot Ulcer through Network Pharmacology and Molecular Docking.

Chuang-Ling-Ye (CLY) has been clinically proven to be an effective Chinese medicine for the treatment of diabetic foot ulcers (DFU). This study aimed to investigate the possible mechanism of CLY in relation to DFU using network pharmacology and molecular docking. Firstly, relevant targets of CLY against DFU were obtained from TCMSP, Swiss Target Prediction database and GEO database. Then, topological analysis was employed by Cytoscape to screen the top 6 core active ingredients and the top 8 hub targets. Furthermore, the OmicShare Tools were applied for gene ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis. Finally, the results of network pharmacology were verified by molecular docking method. CLY has 61 active compounds and 361 targets after de-duplication, and the top 8 hub targets were EGFR, TP53, CCND1, IL-1B, CREBBP, AR, PTGS2 and PGR. GO enrichment analysis is mainly related to signal transducer activity, receptor activity, and molecular transducer activity. KEGG pathway analysis indicated that these shared targets were primarily focused on AGE-RAGE signaling pathway in diabetic complications, HIF-1 signaling pathway, IL-17 signaling pathway, and JAK-STAT signaling pathway. Molecular docking results showed that physciondiglucoside, 2-cinnamoyl-glucose and kinobeon A were well bound with EGFR, IL-1B, AR and PTGS2. This study demonstrated that CLY has anti-oxidative stress and anti-inflammatory effects in the treatment of DFU through various constituents, multiple targets, and multiple pathways, which provides a valuable point of reference for future investigations on CLY.

USP39 Promotes the Viability and Migration of Head and Neck Squamous Cell Carcinoma Cell by Regulating STAT1.

Objective: Ubiquitin-specific peptidase 39 (USP39) plays a carcinogenic role in many cancers, but little research has been conducted examining whether it is involved in head and neck squamous cell carcinoma (HNSCC). Therefore, this study explored the functional role of USP39 in HNSCC. Method: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to identify differentially expressed proteins (DEPs) between the HNSCC tumor and adjacent healthy tissues. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were used to assess the functional enrichment of DEPs. Immunohistochemistry was used to detect protein expression. The viability and migration of two HNSCC cell lines, namely CAL27 and SCC25, were detected using the cell counting kit-8 assay and a wound healing assay, respectively. Quantitative real-time PCR was used to detect the expression level of signal transducer and activator of transcription 1 (STAT1) mRNA. Results: LC-MS/MS results identified 590 DEPs between HNSCC and adjacent tissues collected from 4 patients. Through GO and KEGG pathway analyses, 34 different proteins were found to be enriched in the spliceosome pathway. The expression levels of USP39 and STAT1 were significantly higher in HNSCC tumor tissue than in adjacent healthy tissue as assessed by LC-MS/MS analysis, and the increased expression of USP39 and STAT1 protein was confirmed by immunohistochemistry in clinical samples collected from 7 additional patients with HNSCC. Knockdown of USP39 or STAT1 inhibited the viability and migration of CAL27 and SCC25 cells. In addition, USP39 knockdown inhibited the expression of STAT1 mRNA in these cells. Conclusion: Our findings indicated that USP39 knockdown may inhibit HNSCC viability and migration by suppressing STAT1 expression. The results of this study suggest that USP39 may be a potential new target for HNSCC clinical therapy or a new biomarker for HNSCC.

Periostin is associated with prognosis and immune cell infiltration in pancreatic adenocarcinoma based on integrated bioinformatics analysis.

Pancreatic cancer is one of the most aggressive human malignancies. Previous research has shown that periostin (POSTN) promotes pancreatic cancer cell proliferation, migration, and invasion. Further, POSTN is involved in tumor microenvironment remodeling during tumor progression. However, the relationship between POSTN expression, immune cell infiltration, and the efficacy of immunotherapy in pancreatic cancer is unclear. We conducted a comprehensive evaluation of POSTN differential expression, examining mRNA and protein levels. To gather data, we utilized various databases including gene expression profiling interactive analysis 2 (GEPIA2), gene expression omnibus (GEO), and the human protein atlas (HPA). To investigate the correlation between POSTN expression and clinical characteristics, we analyzed data from the Kaplan-Meier plotter database and clinical data sourced from the cancer genome atlas (TCGA). Furthermore, we performed gene ontology (GO) analysis, Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis, and gene set enrichment analysis (GSEA). Additionally, we explored the relationship between POSTN expression and immune cell infiltration, as well as the immunophenoscore (IPS), by leveraging the cancer immunome atlas (TCIA) database. Lastly, we examined the tumor mutational burden (TMB) in pancreatic cancer in relation to POSTN expression. When compared with healthy pancreatic tissues, pancreatic cancer tissues displayed significantly higher levels of POSTN, which was indicative of a worse prognosis. POSTN expression was closely associated with extracellular matrix (ECM) organization, ECM-receptor interaction, and focal adhesion by GO, KEGG pathway, and GSEA analyses. Higher expression of POSTN was associated with increased infiltration of M2 macrophages. Additionally, increased IPS was linked to lower POSTN expression. IPS scores for CTLA4, PD-1/PDL1, and CTLA4/PD-1/PDL1 immune checkpoint inhibitors were also higher in the POSTN-low expression group, suggesting that lower expression of POSTN is associated with a better outcome with checkpoint inhibitor treatment. POSTN is related to pancreatic cancer prognosis, and may influence immune cell infiltration. High expression of POSTN is predicted to correlate with lower sensitivity to immunotherapy with checkpoint inhibitors in pancreatic cancer.

Exploring lncRNA Expression Patterns in Patients With Hypertrophied Ligamentum Flavum.

Hypertrophy ligamentum flavum (LFH) is a common cause of lumbar spinal stenosis, resulting in significant disability and morbidity. Although long noncoding RNAs (lncRNAs) have been associated with various biological processes and disorders, their involvement in LFH remains not fully understood. Human ligamentum flavum samples were analyzed using lncRNA sequencing followed by validation through quantitative real-time polymerase chain reaction. To explore the potential biological functions of differentially expressed lncRNA-associated genes, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed. We also studied the impact of lncRNA PARD3-AS1 on the progression of LFH in vitro. In the LFH tissues when compared to that in the nonhypertrophic ligamentum flavum (LFN) tissues, a total of 1,091 lncRNAs exhibited differential expression, with 645 upregulated and 446 downregulated. Based on GO analysis, the differentially expressed transcripts primarily participated in metabolic processes, organelles, nuclear lumen, cytoplasm, protein binding, nucleic acid binding, and transcription factor activity. Moreover, KEGG pathway analysis indicated that the differentially expressed lncRNAs were associated with the hippo signaling pathway, nucleotide excision repair, and nuclear factor-kappa B signaling pathway. The expression of PARD3-AS1, RP11-430G17.3, RP1-193H18.3, and H19 was confirmed to be consistent with the sequencing analysis. Inhibition of PARD3-AS1 resulted in the suppression of fibrosis in LFH cells, whereas the overexpression of PARD3-AS1 promoted fibrosis in LFH cells in vitro. This study identified distinct expression patterns of lncRNAs that are linked to LFH, providing insights into its underlying mechanisms and potential prognostic and therapeutic interventions. Notably, PARD3-AS1 appears to play a significant role in the pathophysiology of LFH.

Differential analysis of transcriptome of psychrophilic bacteria under different culture temperatures.

Psychrophilic bacteria can survive in a unique living environment. To explore the mechanism of low temperature adaptation and the physiological function of thermophilic metabolic genes. Serratia marcescens strain F13 stored in microbial laboratory was cultured at 5∘C, 10∘C and 25∘C respectively, and the obtained strains were sequenced by high-throughput transcriptome. Serratia marcescens strain CAV1761 was used as the reference strain. The data produced by transcriptome sequencing were statistically analyzed by biostatistics software such as soapnuke, soap and edger. The differentially expressed genes were found based on the gene expression, and analyzed by Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The results showed that there were 718 differential genes in F13-10 vs F13-5 comparison group, 1614 differential genes in F13-25 vs F13-5 comparison group and 1636 differential genes in F13-25 vs F13-10 comparison group. GO function enrichment analysis showed that the GO term mainly enriched by different genes in the three comparison groups was mostly related to the migration and transport of cellular or subcellular components, cell localization and transmembrane transporter activity, as well as cilia or flagella dependent cell movement. In the enrichment analysis of KEGG pathway, the three comparison groups all enriched the largest number of differential genes in the branch pathway of KEGG metabolism, followed by the branch pathway of environmental information processing. In F13-10 vs F13-5, the differential genes were mainly concentrated in 20 pathways such as ATP-binding cassette transport (ABC) transporters, thiamine metabolism and flagella assembly; In F13-25 vs F13-5, the differential genes are mainly concentrated in 20 pathways, such as (ABC) transporters, arginine and proline metabolism, two-component system and so on; In F13-25 vs F13-10, the differential genes are mainly concentrated in 20 pathways such as various types of glycan synthesis, two-component system and arginine metabolism.

Major histocompatibility complex genes exhibit a potential immunological role in mixed Eimeria-infected broiler cecum analyzed using RNA sequencing.

This study was conducted to investigate the differential expression of the major histocompatibility complex (MHC) gene region in Eimeria-infected broiler. We profiled gene expression of Eimeria-infected and uninfected ceca of broilers sampled at 4, 7, and 21 days post-infection (dpi) using RNA sequencing. Differentially expressed genes (DEGs) between two sample groups were identified at each time point. DEGs located on chicken chromosome 16 were used for further analysis. Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis was conducted for the functional annotation of DEGs. Fourteen significant (false discovery rate <0.1) DEGs were identified at 4 and 7 dpi and categorized into three groups: MHC-Y class I genes, MHC-B region genes, and non-MHC genes. In Eimeria-infected broilers, MHC-Y class I genes were upregulated at 4 dpi but downregulated at 7 dpi. This result implies that MHC-Y class I genes initially activated an immune response, which was then suppressed by Eimeria. Of the MHC-B region genes, the DMB1 gene was upregulated, and TAP-related genes significantly implemented antigen processing for MHC class I at 4 dpi, which was supported by KEGG pathway analysis. This study is the first to investigate MHC gene responses to coccidia infection in chickens using RNA sequencing. MHC-B and MHC-Y genes showed their immune responses in reaction to Eimeria infection. These findings are valuable for understanding chicken MHC gene function.

Mendelian randomization study highlights hypothyroidism as a causal determinant of alopecia areata.

Although observational studies have found an association between hypothyroidism and alopecia areata, the causality of this relationship remains unclear. This study aimed to investigate the genetic variants associated with hypothyroidism and their potential impact on the risk of developing alopecia areata. genome-wide association study summary statistics for hypothyroidism (30,155 cases and 379,986 controls) and alopecia areata (289 cases and 211,139 controls) were obtained from the IEU OpenGwas project. The inverse variance-weighted method was used as the primary analysis method to evaluate the causality between hypothyroidism and alopecia areata, supplemented by the weighted median, MR-Egger, simple mode and weighted mode. Furthermore, the function of causal SNPs was evaluated by gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction networks. Utilizing two-sample Mendelian randomization analysis, we found that the single-nucleotide polymorphisms (SNPs) of hypothyroidism (OR = 1.40, 95% CI: 1.12-1.75, p = 3.03×10-3) significantly increased the risk of alopecia areata ( 289 cases and 211,139 controls ). KEGG pathway analysis showed that the candidate genes were mainly enriched in virion-herpesvirus, Th1 and Th2 cell differentiation, Th17 cell differentiation, T-cell receptor signaling pathway, PD-L1/PD-1 checkpoint pathway in cancer and Toll-like receptor signaling pathway. Protein-protein interaction networks results showed that CTLA4, STAT4, IL2RA, TYK2, IRF7, SH2B3, BACH2, TLR3, NOD2, and FLT3. This study provided compelling genetic evidence supporting a causative association between hypothyroidism and alopecia areata, which could potentially inform the development of more efficacious treatment strategies for patients afflicted by alopecia areata.