Results Of Enrichment Analysis Research Articles

Exploration of Potential Biomarkers and Immune Landscape for Hepatoblastoma: Evidence from Machine Learning Algorithm.

This study aimed to investigate the immune landscape in hepatoblastoma (HB) based on deconvolution methods and identify a biomarkers panel for diagnosis based on a machine learning algorithm. Firstly, we identified 277 differentially expressed genes (DEGs) and differentiated and functionally identified the modules in DEGs. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and GO (gene ontology) were used to annotate these DEGs, and the results suggested that the occurrence of HB was related to DNA adducts, bile secretion, and metabolism of xenobiotics by cytochrome P450. We selected the top 10 genes for our final diagnostic panel based on the random forest tree method. Interestingly, TNFRSF19 and TOP2A were significantly down-regulated in normal samples, while other genes (TRIB1, MAT1A, SAA2-SAA4, NAT2, HABP2, CYP2CB, APOF, and CFHR3) were significantly down-regulated in HB samples. Finally, we constructed a neural network model based on the above hub genes for diagnosis. After cross-validation, the area under the ROC curve was close to 1 (AUC = 0.972), and the AUC of the validation set was 0.870. In addition, the results of single-sample gene-set enrichment analysis (ssGSEA) and deconvolution methods revealed a more active immune responses in the HB tissue. In conclusion, we have developed a robust biomarkers panel for HB patients.

A Cross-Tissue Transcriptome-Wide Association Study Identifies Novel Susceptibility Genes for Juvenile Idiopathic Arthritis in Asia and Europe.

BackgroundJuvenile idiopathic arthritis (JIA) is the most common rheumatic disease in children, and its pathogenesis is still unclear. Genome-wide association studies (GWASs) of JIA have identified hundreds of risk factors, but few of them implicated specific biological mechanisms.MethodsA cross-tissue transcriptome-wide association study (TWAS) was performed with the functional summary-based imputation software (FUSION) tool based on GWAS summary datasets (898 JIA patients and 346,102 controls from BioBank Japan (BBJ)/FinnGen). The gene expression reference weights of skeletal muscle and the whole blood were obtained from the Genotype-Tissue Expression (GTExv8) project. JIA-related genes identified by TWAS findings genes were further compared with the differentially expressed genes (DEGs) identified by the mRNA expression profile of JIA from the Gene Expression Omnibus (GEO) database (accession number: GSE1402). Last, candidate genes were analyzed using functional enrichment and annotation analysis by Metascape to examine JIA-related gene sets.ResultsThe TWAS identified 535 significant genes with P < 0.05 and contains 350 for Asian and 195 for European (including 10 genes both expressed in Asian and European), such as CDC16 (P = 1.72E-03) and PSMD5-AS1 (P = 3.65E-02). Eight overlapping genes were identified based on TWAS results and DEGs of JIA patients, such as SIRPB1 (P TWAS = 4.21E-03, P DEG = 1.50E-04) and FRAT2 (P TWAS = 2.82E-02, P DEG = 1.43E-02). Pathway enrichment analysis of TWAS identified 183 pathways such as cytokine signaling in the immune system and cell adhesion molecules. By integrating the results of DEGs pathway and process enrichment analyses, 19 terms were identified such as positive regulation of T-cell activation.ConclusionBy conducting two populations TWAS, we identified a group of JIA-associated genes and pathways, which may provide novel clues to uncover the pathogenesis of JIA.

DNA damage repair-related gene signature predicts prognosis and indicates immune cell infiltration landscape in skin cutaneous melanoma

BackgroundDNA damage repair plays an important role in the onset and progression of cancers and its resistance to treatment therapy. This study aims to assess the prognostic potential of DNA damage repair markers in skin cutaneous melanoma (SKCM).MethodIn this study, we have analyzed the gene expression profiles being downloaded from TCGA, GTEx, and GEO databases. We sequentially used univariate and LASSO Cox regression analyses to screen DNA repair genes associated with prognosis. Then, we have conducted a multivariate regression analysis to construct the prognostic profile of DNA repair-related genes (DRRGs). The risk coefficient is used to calculate the risk scores and divide the patients into two cohorts. Additionally, we validated our prognosis model on an external cohort as well as evaluated the link between immune response and the DRRGs prognostic profiles. The risk signature is compared to immune cell infiltration, chemotherapy, and immune checkpoint inhibitors (ICIs) treatment.ResultsAn analysis using LASSO-Cox stepwise regression established a prognostic signature consisting of twelve DRRGs with strong predictive ability. Disease-specific survival (DSS) is found to be lower among high-risk patients group as compared to low-risk patients. The signature may be employed as an independent prognostic predictor after controlling for clinicopathological factors, as demonstrated by validation on one external GSE65904 cohort. A strong correlation is also found between the risk score and the immune microenvironment, along with the infiltrating immune cells, and ICIs key molecules. The gene enrichment analysis results indicate a wide range of biological activities and pathways to be exhibited by high-risk groups. Furthermore, Cisplatin exhibited a considerable response sensitivity in low-risk groups as opposed to the high-risk incidents, while docetaxel exhibited a considerable response sensitivity in high-risk groups.ConclusionsOur findings provide a thorough investigation of DRRGs to develop an DSS-related prognostic indicator which may be useful in forecasting SKCM progression and enabling more enhanced clinical benefits from immunotherapy.

Pyroptotic Patterns in Blood Leukocytes Predict Disease Severity and Outcome in COVID-19 Patients.

The global coronavirus disease 2019 (COVID-19) pandemic has lasted for over 2 years now and has already caused millions of deaths. In COVID-19, leukocyte pyroptosis has been previously associated with both beneficial and detrimental effects, so its role in the development of this disease remains controversial. Using transcriptomic data (GSE157103) of blood leukocytes from 126 acute respiratory distress syndrome patients (ARDS) with or without COVID-19, we found that COVID-19 patients present with enhanced leukocyte pyroptosis. Based on unsupervised clustering, we divided 100 COVID-19 patients into two clusters (PYRcluster1 and PYRcluster2) according to the expression of 35 pyroptosis-related genes. The results revealed distinct pyroptotic patterns associated with different leukocytes in these PYRclusters. PYRcluster1 patients were in a hyperinflammatory state and had a worse prognosis than PYRcluster2 patients. The hyperinflammation of PYRcluster1 was validated by the results of gene set enrichment analysis (GSEA) of proteomic data (MSV000085703). These differences in pyroptosis between the two PYRclusters were confirmed by the PYRscore. To improve the clinical treatment of COVID-19 patients, we used least absolute shrinkage and selection operator (LASSO) regression to construct a prognostic model based on differentially expressed genes between PYRclusters (PYRsafescore), which can be applied as an effective prognosis tool. Lastly, we explored the upstream transcription factors of different pyroptotic patterns, thereby identifying 112 compounds with potential therapeutic value in public databases.

Mechanism of Astragali Radix for the treatment of osteoarthritis: A study based on network pharmacology and molecular docking.

Osteoarthritis (OA) is a degenerative joint disease caused by many factors. Astragali Radix (Huangqi), a traditional Chinese medicine (TCM), is widely used to treat OA. Although it can inhibit the progression of OA, its pharmacological mechanism is unclear. In this study, we used a network pharmacological approach to determine the mechanism by which Huangqi inhibits the progression of OA. We obtained the active ingredients of Huangqi from the Traditional Chinese Systems Pharmacology database and identified potential targets of these ingredients. Next, we identified the OA-related targets by using the GeneCards and Online Mendelian Inheritance in Man databases. Then, a protein-protein interaction (PPI) network was established based on the overlapping genes between the Huangqi targets and the OA targets, and the interactions were analyzed. Subsequently, the Metascape database was used to perform the Gene Ontology biological functions and Kyoto Encyclopedia of Genes and Genomes pathways enrichment analysis. Furthermore, selected active ingredients and corresponding targets were investigated through molecular docking. In total, 20 active ingredients and 206 related targets were identified. The results of Gene Ontology enrichment analysis showed that the intersection targets were mainly involved in immune inflammation, proliferation, and apoptosis. The Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that Huangqi might exert antiosteoarthritis effect mainly through the PI3K-Akt signaling pathway, apoptosis, the mitogen-activated protein kinases signaling pathway, and the p53 signaling pathway. Moreover, the molecular docking results indicated that quercetin and kaempferol exhibited the good binding capacity to transcription factor JUN, tumor necrosis factor, and protein kinase B. In summary, we investigated the therapeutic effects of Huangqi from a systemic perspective. These key targets and pathways provide promising directions for future studies to reveal the exact regulating mechanism of Huangqi against OA.

Effects of Agricultural Organic Waste Incorporation on the Metabolic Capacity of Microbial Carbon Sources of Dissolved Organic Matter in Paddy Soil

A long-term fertilization experiment with a system of rice-wheat rotation was conducted in Chengdu Plain. Three fertilization treatments including conventional fertilization (T1), pig manure substituting for 50% nitrogen fertilizer (T2), and T2 plus straw (T3) were set up to study the characteristics of microbial carbon source utilization of soil and dissolved organic matter (DOM). The results showed that T3 improved the soil microbial carbon source metabolism in comparison with those of the T1 and T2 treatments; the average color change rate (AWCD) increased by 16% and 48%, respectively. Meanwhile, T3 improved the soil DOM microbial carbon source metabolism, and the AWCD value was 0.43. The highest Shannon, Simpson, and McIntosh indexes of soil and DOM were all found in the T3 treatment, and the Shannon, Simpson, and McIntosh indexes of DOM were 2.73, 0.91, and 3.75, respectively. The results of principal component analysis and enrichment analysis showed that the main carbon sources used by microorganisms of soil and DOM were different under different fertilization treatments. For DOM, the main carbon source used by microorganisms in the T1 and T2 treatments was sugar, whereas T3 increased the utilization of amino acids, carboxylic acids, polymers, and amines. The changes in soil pH and texture were the main factors that caused the difference in soil DOM microbial carbon source metabolism. In conclusion, the application of organic fertilizer (pig manure plus straw) significantly increased the microbial community diversity and carbon source metabolic capacity of soil and DOM and promoted the diversification of microbial carbon source preference.

Identification of key genes and biological regulatory mechanisms in diabetic nephropathy: Meta-analysis of gene expression datasets

BackgroundDiabetic nephropathy (DN) which refers to the cases with biopsy proven kidney lesions, is one of the main complications of diabetes all around the world; however, the underlying biological changes causing DN remain to be understood. Studying the alterations in gene expression profiles could give a holistic view of the molecular pathogenicity of DN and aid to discover key molecules as potential therapeutic targets. Here, we performed a meta-analysis study that included microarray gene expression profiles coming from glomerular samples of DN patients in order to acquire a list of consensus Differentially Expressed Genes (meta-DEGs) correlated with DN. MethodsAfter quality control and normalization steps, five gene expression datasets (GES1009, GSE30528, GSE47183, GSE104948, and GSE93804) were entered into the meta-analysis. The meta-analysis was performed by random effect size method and the meta-DEGs were put through network analysis and different pathway enrichment analyses steps. MiRTarBase and TRRUST databases were utilized to predict the meta-DEGs related miRNAs and transcription factors. A co-regulatory network including DEGs, transcription factors and miRNAs was constructed by Cytoscape, and top molecules were identified based on centrality scores in the network. ResultsThe identified meta-DEGs were 1364 DEGs including 665 downregulated and 669 upregulated DEGs. The results of pathway enrichment analysis showed, “immune system”, “extracellular matrix organization”, “hemostasis”, “signal transduction”, and “platelet activation” to be the top enriched terms with involvement of the meta-DEGs. After construction of the multilayer regulatory network, several top DEGs (TP53, MYC, BTG2, VEGFA, PTEN, etc.), as well as top miRNAs (miR-335, miR-16, miR-17, miR-20a, and miR-93), and transcription factors (SP1, STAT3, NF-KB1, RELA, E2F1), were introduced as potential therapeutic targets in DN. Among the regulatory molecules, miR-335-5p and SP1 were the most interactive miRNA and transcription factor molecules with the highest degree scores in the constructed network. ConclusionBy performing a meta-analysis of available DN-related transcriptomics datasets, we reached a consensus list of DEGs for this complicated disorder. Further enrichment and network analyses steps revealed the involved pathways in the DN pathogenesis and marked the most potential therapeutic targets in this disease.

Differential Gene Analysis of Trastuzumab in Breast Cancer Based on Network Pharmacology and Medical Images.

The purpose of this study was to use network pharmacology, biomedical images and molecular docking technology in the treatment of breast cancer to investigate the feasible therapeutic targets and mechanisms of trastuzumab. In the first place, we applied pubchem swisstarget (http://www.swisstargetprediction.ch/), (https://pubchem.ncbi.nlm.nih.gov/) pharmmapper (http://lilab-ecust.cn/pharmmapper/), and the batman-tcm (http://bionet.ncpsb.org.cn/batman-tcm/) database to collect the trastuzumab targets. Then, in NCBI-GEO, breast cancer target genes were chosen (https://www.ncbi.nlm.nih.gov/geo/). The intersection regions of drug and disease target genes were used to draw a Venn diagram. Through Cytoscape 3.7.2 software, and the STRING database, we then formed a protein-protein interaction (PPI) network. Besides, we concluded KEGG pathway analysis and Geen Ontology analysis by using ClueGO in Cytospace. Finally, the top 5 target proteins in the PPI network to dock with trastuzumab were selected. After screening trastuzumab and breast cancer in databases separately, we got 521 target genes of the drug and 1,464 target genes of breast cancer. The number of overlapping genes was 54. PPI network core genes include GAPDH, MMP9, CCNA2, RRM2, CHEK1, etc. GO analysis indicated that trastuzumab treats breast cancer through abundant biological processes, especially positive regulation of phospholipase activity, linoleic acid metabolic process, and negative regulation of endothelial cell proliferation. The molecular function is NADP binding and the cellular component is tertiary granule lumen. The results of KEGG enrichment analysis exhibited four pathways related to the formation and cure of breast cancer, containing Drug metabolism, Glutathione metabolism, Pyrimidine metabolism and PPAR signaling pathway. Molecular docking showed that trastuzumab has good binding abilities with five core target proteins (GAPDH, MMP9, CCNA2, RRM2, CHEK1). This study, through network pharmacology and molecular docking, provides new pieces of evidence and ideas to understand how trastuzumab treats breast cancer at the gene level.

Investigation of Molecular Mechanism of Banxia Xiexin Decoction in Colon Cancer via Network Pharmacology and In Vivo Studies.

Objective Banxia Xiexin decoction (BXD) is widely used in the treatment of gastrointestinal and other digestive diseases. This study is based on network pharmacology to explore the molecular mechanism of BXD in the treatment of colon cancer. Methods The bioactive components and potential targets of BXD were obtained from public database. The protein-protein interaction (PPI) network of the potential targets of BXD for colon cancer was constructed based on the STRING database, cytoscape software, gene ontology (GO), and kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis of the PPI network. Finally, we established a xenograft nude mouse model to verify the effect of BXD in colon cancer treatment. Results We have acquired a total of 55 bioactive components and 136 cross-targets of BXD. The results of enrichment analysis suggested that the oxidate stress and diet were the key factors of colon cancer occurrence, and AGE-RAGE signaling pathway plays an essential role in the treatment of colon cancer with BXD. Animal experiments revealed that BXD could suppress tumor growth and induce tumor cell apoptosis in the xenograft nude mouse model with HCT116 cells. Conclusion This study uncovered that BXD inhibits the malignant progression of colon cancer that may be related to multiple compounds (berberine, quercetin, baicalein, etc.), multiple targets (Bcl2, Bax, IL6, TNFα, CASP3, etc.), and multiple pathways (human cytomegalovirus infection, AGE-RAGE signaling pathway in diabetic complications, etc.).

P-397 How do extracellular vesicles secreted by human embryos impact decidualized endometrial stromal cells?

Abstract Study question What is the transcriptomic response of decidualized endometrial stromal cells (DESCs) to the uptake of extracellular vesicles (EVs) secreted by human embryos? Summary answer Human embryo derived EVs can impact DESCs transcriptomic profile via a cargo that can induce a positive effect on the expression of some decidualization-related genes. What is known already The establishment of an appropriate embryo–endometrial communication is essential for the implantation process and a successful pregnancy. Embryo-released factors are able to elicit biological effects on the endometrium. Among these, EVs secreted by embryos carry molecules potentially able to modulate endometrial function and favour the implantation process. However, most results come from animal species as few studies were performed using EVs derived from human embryos, due to difficulty in sample collection or ethical reasons. Study design, size, duration EVs were isolated from one pool of IVF media where embryos were cultured between day 3 and 5 of development (blastocyst). Initially, DESCs(n = 4) were treated with different concentrations of EVs at different time points and RNA-sequencing was performed to define optimal conditions.Subsequently, EVs were isolated from one pool of IVF media where blastocysts diagnosed as euploid were cultured (EVe). To increase the reliability of the results, DESCs(n = 5) were treated with EVe using the optimal conditions. Participants/materials, setting, methods EVs were isolated by differential ultracentrifugation from spent media of in vitro cultured human blastocyst stage embryos and from an equal volume of control medium (not exposed to embryos). DESCs were in vitro decidualized (E2:10nM+ P4:1uM+cAMP:0.5mM) and treated with different concentrations of EVs (10µg,50µg,100µg) for 24hours and 48hours. RNA-sequencing analysis was then performed. Once established the conditions that allow to better detect differences in trascriptomic profile, RNA-sequencing analysis on DESCs treated specifically with EVe was performed. Main results and the role of chance The best response of DESCs to EVs uptake was induced by treatment with 10µg of EVs for 48hours. Using this condition, differential gene expression analysis allowed the identification of 166 upregulated and 124 downregulated genes in DESCs treated with EVe, when compared to DESCs treated with control. Based on Over-Representation analysis, DESCs treated with EVe were found to be enriched in transcripts of genes involved in signalling and cell communication. Moreover, based on Gene Set Enrichment Analysis results, EVe may regulate decidualization and the implantation process by targeting cholesterol biosynthesis and metabolism pathways, being among the most enriched pathways. The depletion of transcripts related to inflammatory and IL1R pathways in DESCs treated with EVe was also observed, suggesting a role of EVe in the fine regulation of inflammatory/immunomodulatory events occurring during implantation. At the intersection of genes whose expression was modified by EVe-treatment and those modified by the decidualization treatment, thirty-one transcripts exhibited the same trend, demonstrating that EVe exerted a positive effect on decidualization-related genes expression in DESCs. Specifically, expression of genes involved in the implantation process (PTGER2, IL15, WNT4) increased after decidualization and were further up-regulated after EVe-treatment, confirming the crucial role of EVs in the embryo-endometrium cross-talk. Limitations, reasons for caution Larger studies are needed to validate these findings. Wider implications of the findings EVs derived from human euploid embryos can evoke a specific transcriptional response in DESCs. Moreover, we speculate that these EVs may exert favourable effects on the endometrial tissue, increasing its receptivity for embryo implantation by modulating decidualization-related genes expression. Trial registration number not applicable

Genes and Diseases: Insights from Transcriptomics Studies.

Results of expression studies can be useful to clarify the genotype-phenotype relationship. However, according to data from recent literature, there is a large group of genes that are revealed as differentially expressed (DE) in many studies, regardless of the biological context. Additional analyses could shed more light on the relationships between genes, their differential expression, and diseases. We generated a set of 9972 disease genes from five gene-phenotype databases (OMIM, ORPHANET, DDG2P, DisGeNet and MalaCards) and a report of the International Union of Immunological Societies. To study transcriptomics of disease and non-disease genes in healthy tissues, we obtained data from the Human Protein Atlas (HPA) website. We analyzed the dependency between expression in healthy tissues and gene occurrence in Gene Expression Omnibus series using tools within the Enrichr libraries. The results of expression studies were annotated with Gene Ontology (GO) and Human Phenotype Ontology (HPO) terms. Using transcriptomics analysis of healthy tissues, we validated the previous findings of higher expression levels of disease genes in pathologically linked tissues compared to other tissues. Preferentially DE genes were generally highly expressed in one or multiple tissues and were enriched for disease genes. According to the results of GO enrichment analyses, both down- and up-regulated DE genes most often took part in immune response, translation and tissue-specific processes. A connection between DE-related pathology and the diversity of HPO terms was found. Investigating a link between expression and phenotype contributes to understanding the mode of development and progression of human diseases.

Whole transcriptome expression array analysis of human colon fibroblasts culture treated with Helichrysum italicum supports its use in traditional medicine

Ethnopharmacological relevanceHelichrysum italicum (HI) is a Mediterranean plant with well-reported use in traditional medicine for a wide range of applications, including digestive and liver disorders, intestinal parasitic infections, wound healing, stomach ache and asthma. However, little is known about the global mechanism behind its pleiotropic activity. Aim of the studyThe aim of this study was to explain the mechanism behind the previously demonstrated effects of HI and to justify its use in traditional medicine. Materials and methodsA microarray-based transcriptome analysis was used to discover the global transcriptional alterations in primary colon fibroblasts after exposure to HI infusion for 6 h and 24 h. In addition, quantitative real-time PCR was used to verify the microarray results. ResultsAltogether we identified 217 differentially expressed genes compared to non-treated cells, and only 8 were common to both treatments. Gene ontology analysis revealed that 24 h treatment with HI infusion altered the expression of genes involved in cytoskeletal rearrangement and cell growth, whereas pathway analysis further showed the importance of interleukin signaling and transcriptional regulation by TP53. For the 6 h treatment only the process of hemostasis appeared in the results of both enrichment analyses. In functional assays, HI infusion increased cell migration and decreased blood clotting and prothrombin time. ConclusionsWith the careful evaluation of the role of individual genes, especially SERPING1, ARHGAP1, IL33 and CDKN1A, represented in the enriched pathways and processes, we propose the main mode of HI action, which is wound healing. In addition to its indirect prevention of diseases resulting from the impaired barrier integrity, HI also effects inflammation and metabolic processes directly, as it regulates genes such as LRPPRC, LIPA, ABCA12, PRKAR1A and ANXA6.

Identify Functional lncRNAs in Nonalcoholic Fatty Liver Disease by Constructing a ceRNA Network.

Aim: To identify functional long noncoding RNAs (lncRNAs) by constructing a NAFLD-related lncRNA–miRNA–mRNA network (NLMMN) based on the hypothesis that lncRNAs, as competitive endogenous RNAs (ceRNAs), are able to regulate mRNA functions by competitive binding to shared miRNAs. Methods: The “Limma R package” was used to identify differentially expressed lncRNAs and mRNAs (DElncRNAs and DEmRNAs). The “miRcode online tool” was used to predict the potential interactions between DElncRNAs or DEmRNAs using Perl, and “multiMiR R package” was used to predict the potential interactions between DElncRNAs and miRNAs. The NLMMN was viewed by Cytoscape. The DEmRNAs were further analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The real-time quantitative reverse transcription polymerase chain reaction (qRT–PCR) was used to identify functional lncRNAs in human liver tissue and FFAs-induced fat-overloading HepG2 cells. The role of functional lncRNA was explored in the HepG2 cell line. Results: A total of 336 DElncRNAs (154 upregulated and 182 downregulated, |log 2 (fold change) |>0.655 and P < 0.05) and 399 DEmRNAs (152 upregulated and 247 downregulated, |log 2 (fold change) |>0.608 and P < 0.05) were identified. A total of 142 DElncRNA-miRNA interaction pairs and 643 miRNA–DEmRNA interaction pairs were retained to construct the NLMMN, which contained 19 lncRNAs, 47 miRNAs, and 228 mRNAs. The results of GO and KEGG enrichment analyses were related to an extracellular matrix (ECM). Two upregulated lncRNAs (LINC00240 and RBMS3-AS3) and one downregulated lncRNA (ALG9-IT1) were identified by qRT–PCR in liver tissues. But only LINC00240 was significantly upregulated in fat-overloading HepG2 cells. Overexpression of LINC00240 did not affect lipid accumulation but increased the reactive oxygen species (ROS) content in HepG2 cells. Conclusion: LINC00240, RBMS3-AS3, and ALG9-IT1 might be novel functional lncRNAs that attenuate liver fibrosis in NAFLD by influencing the ECM through the ceRNA network. Among them, LINC00240 might have a key role.

Candidate Drugs Screening for Behcet's Disease Based on Bioinformatics Analysis and Mouse Experiments.

BackgroundBehcet’s disease (BD) is a chronic immune disease that involves multiple systems. As the pathogenesis of BD is not clear, and new treatments are needed, we used bioinformatics to identify potential drugs and validated them in mouse models.MethodsBehcet’s disease-related target genes and proteins were screened in the PubMed and UVEOGENE databases. The biological functions and pathways of the target genes were analyzed in detail by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. A protein-protein interaction (PPI) network was constructed by the STRING database, and hub genes were identified by the Cytoscape plug-in CytoHubba. Gene-drug interactions were identified from the DGIdb database. Experimental autoimmune uveitis (EAU) mice were used as an animal model for drug validation.ResultsA total of 249 target genes and proteins with significant differences in BD were screened, and the results of functional enrichment analysis suggested that these genes and proteins were more located on the cell membrane, involved in regulating the production of cytokines and affecting the activity of cytokines. They mainly regulated “Cytokine- Cytokine receptor interaction”, “Inflammatory bowel disease (IBD)” and “IL-17 signaling Pathway”. In addition, 10 hub genes were obtained through PPI network construction and CytoHubba analysis, among which the top 3 hub genes were closely related to BD. The DGIdb analysis enriched seven drugs acting together on the top 3 hub genes, four of which were confirmed for the treatment of BD or its complications. There is no evidence in the research to support the results in omeprazole, rabeprazole, and celastrol. However, animal experiments showed that rabeprazole and celastrol reduced anterior chamber inflammation and retinal inflammation in EAU mice.ConclusionsThe functional analysis of genes and proteins related to BD, identification of hub genes, and validation of potential drugs provide new insights into the disease mechanism and potential for the treatment of BD.

NTF2 Upregulation in HNSCC: a Predictive Marker and Potential Therapeutic Target Associated With Immune Infiltration.

BackgroundHead and neck squamous cell carcinoma (HNSCC) is a type of malignant tumor with an increasing incidence worldwide and a meager 5-year survival rate. It is known that nuclear transporter factor 2 (NTF2) transports related proteins into the nucleus physiologically. However, the role of NTF2 in HNSCC remains unclear.MethodsIn this study, RNA-Seq data of HNSCC samples with corresponding clinical information were obtained from The Cancer Genome Atlas (TCGA) database. In addition, other expression profiling data were downloaded from the Gene Expression Omnibus (GEO) database. The differential expressions of NTF2, along with the overall survival (OS) rates were identified and analyzed. Then, the clinical features and expression levels of NTF2 were utilized to develop a prognostic model. The study also utilized the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) methods to determine the related pathways of NTF2. Furthermore, the Tumor Immune Estimation Resource (TIMER) database was referenced to discover the immune correlation of NTF2. In this research investigation, RT-qPCR, western blotting, Cell Counting Kit-8 (CCK-8) assay, wound-healing assay, and immunohistochemical (IHC) staining methods were adopted to perform experimental verifications.ResultsThis study’s results confirmed that the NTF2 expressions were significantly increased in HNSCC tissue when compared with normal tissue. In addition, the high expression levels of NTF2 were found to be associated with poor prognoses, which was confirmed via the IHC validations of HNSCC samples with survival data. The results of functional enrichment analysis showed that the NTF2 was associated with epithelial cell growth, skin differentiation, keratosis, and estrogen metabolism. Furthermore, the expressions of NTF2 were determined to be negatively involved with immune infiltrations and correlated with immune checkpoint blockade (ICB) responses following various ICB therapy strategies. The results of the CCK-8 assay and wound-healing assay confirmed the NTF2’s promoting effects on the proliferation and migration of tumor cells.ConclusionsThis study defined a novel prognostic model associated with the expressions of NTF2, which was shown to be independently related to the OS of HNSCC. It was concluded in this study that NTF2 might be a potential diagnostic and prognostic biomarker for HNSCC.

Comprehensive analysis of novel prognosis-related proteomic signature effectively improve risk stratification and precision treatment for patients with cervical cancer.

Cervical cancer (CC) is one of the most common types of malignant female cancer, and its incidence and mortality are not optimistic. Protein panels can be a powerful prognostic factor for many types of cancer. The purpose of our study was to investigate a proteomic panel to predict the survival of patients with common CC. The protein expression and clinicopathological data of CC were downloaded from The Cancer Proteome Atlas and The Cancer Genome Atlas database, respectively. We selected the prognosis-related proteins (PRPs) by univariate Cox regression analysis and found that the results of functional enrichment analysis were mainly related to apoptosis. We used Kaplan-Meier analysis and multivariable Cox regression analysis further to screen PRPs to establish a prognostic model, including BCL2, SMAD3, and 4EBP1-pT70. The signature was verified to be independent predictors of OS by Cox regression analysis and the area under curves. Nomogram and subgroup classification were established based on the signature to verify its clinical application. Furthermore, we looked for the co-expressed proteins of three-protein panel as potential prognostic proteins. A proteomic signature independently predicted OS of CC patients, and the predictive ability was better than the clinicopathological characteristics. This signature can help improve prediction for clinical outcome and provides new targets for CC treatment.

Mechanistic insight of the potential of geraniol against Alzheimer’s disease

BackgroundAlzheimer’s disease (AD) as a neurodegenerative disease occupies 3/5–4/5 cases among patients with dementia, yet its pathogenetic mechanism remains unclear. Geraniol, on the other hand, is a well-known extract from essential oils of aromatic plants and has been proven that it has outstanding neuroprotective effects as well as ameliorating influence in memory impairment. Therefore, the present study aims to elucidate the potential of geraniol against AD by network pharmacology-based approach combined with molecular modeling study.Materials and methodsFirstly, we evaluated the druggability of geraniol by ADME method. Then, we obtained the geraniol targets and AD-related targets from multiple open data sources. Afterward, we calculated the intersection through a Venn diagram to find common targets, and via Panther classification system to categorize them. In order to gain a macroscopic understanding of these common targets, we carried out GO terms and KEGG pathways enrichment analyses, according to which we constructed a compound–target–pathway–disease network. In addition, we built a preliminary PPI network which was further analyzed both functionally and topologically. Consequently, five hub targets were sorted out. Finally, we conducted molecular docking and molecular dynamic simulation to validate our findings.ResultsIn the present study, the pharmacological properties of geraniol were assessed according to ADME and Lipinski’s rule, which demonstrate promising druggability. Then, from 10,972 AD-related targets and 33 geraniol targets, 29 common targets were identified, among which 38.1% of them are metabolite interconversion enzymes, 23.8% are protein modifying enzymes, 33.3% are transmembrane receptors, and the rest are transporters. Enrichment analyses hint that geraniol is involved in cholinergic synapse, serotonergic synapse, and neuroactive ligand–receptor interaction. We also built a preliminary PPI network to investigate the interplay between these targets and their extensive interactions. Then, by functionally clustering the preliminary PPI network, we gained a cluster of proteins which formed a subnetwork with score of 8.476, and 22 nodes. Its results of GO terms and KEGG pathways enrichment analyses once again suggests that geraniol actively participates in cholinergic synapse, serotonergic synapse, and neuroactive ligand–receptor interaction, which are believed to be strongly associated with AD pathogenesis. Besides, topological analyses of the preliminary PPI network helped find 5 hub targets (i.e., CHRM3, PRKCA, PRKCD, JAK1, JAK2). To verify their interaction with geraniol molecule, we conducted molecular docking, and found that CHRM3 possesses the highest affinity in binding, indicating that geraniol molecules are closely bound to each hub target, and CHRM3 may serve as a key target of geraniol against AD. It was then further confirmed by molecular dynamic simulation, the result of which supports our hypothesis.ConclusionThe present study shares a mechanistic insight of the potential of geraniol against AD, giving a reference to future experimental studies.

Pharmacological mechanisms of sodium-glucose co-transporter 2 inhibitors in heart failure with preserved ejection fraction

BackgroundMore and more evidence indicates sodium-glucose co-transporter 2 inhibitors (SGLT2is) may display clinical benefits for heart failure with preserved ejection fraction (HFpEF). However, the mechanisms of the action remain unclear.MethodsA systematic pharmacology-based strategy was applied for predicting the potential molecular mechanisms of SGLT2is in HFpEF. The potential targets of SGLT2is and HFpEF were contained from diverse databases. After networks were constructed, Metascape was applied to functional enrichment. Moreover, the key findings were validated through molecular docking.ResultsWe obtained 487 SGLT2is related targets and 1505 HFpEF related targets. The networks showed the complex relationship of HFpEF-target-HFpEF. The results of functional enrichment analysis suggested that several biological processes, including muscle system process, inflammatory response, vasculature development, heart development, regulation of MAPK cascade, positive regulation of ion transport, negative regulation of cell population proliferation, cellular response to nitrogen compound, apoptotic signaling pathway, multicellular organismal homeostasis, response to oxidative stress, regulation of cell adhesion, positive regulation of cell death, response to growth factor, and cellular response to lipid, and signaling pathways, such as cardiomyopathy, cAMP signaling pathway, cytokine-cytokine receptor interaction, apoptosis, MAPK signaling pathway, HIF-1 signaling pathway, calcium signaling pathway, and NF-kappa B signaling pathway. Finally, we validated the interactions and combinations of SGLT2is and core targets.ConclusionSGLT2is play the potential role of anti-HFpEF through the direct or indirect synergy of multiple targets and pathways. Our study promotes the explanation of the molecular mechanisms of SGLT2is in HFpEF.

The Crosstalk Between Immune Infiltration, Circulating Tumor Cells, and Metastasis in Pancreatic Cancer: Identification of HMGB3 From a Multiple Omics Analysis.

Metastasis is the major cause of death in patients with pancreatic ductal adenocarcinoma (PDAC), and circulating tumor cells (CTCs) play an important role in the development of metastasis. However, few studies have uncovered the metastasis mechanism of PDAC based on CTCs. In this study, the existing bulk RNA-sequencing (bulk RNA-seq) and single-cell sequencing (scRNA-seq) data for CTCs in pancreatic cancer were obtained from the Gene Expression Omnibus (GEO) database. Analysis of tumor-infiltrating immune cells (TIICs) by CIBERSORT showed that the CTCs enriched from the peripheral blood of metastatic PDAC were found to contain a high proportion of T cell regulators (Tregs) and macrophages, while the proportion of dendritic cells (DCs) was lower than that enriched from localized PDAC. Through weighted gene co-expression network analysis (WGCNA) and the result of scRNA-seq, we identified the hub module (265 genes) and 87 marker genes, respectively, which were highly associated with metastasis. The results of functional enrichment analysis indicated that the two gene sets mentioned above are mainly involved in cell adhesion and cytoskeleton and epithelial–mesenchymal transition (EMT). Finally, we found that HMGB3 was the hub gene according to the Venn diagram. The expression of HMGB3 in PDAC was significantly higher than that in normal tissues (protein and mRNA levels). HMGB3 expression was significantly positively correlated with both EMT-related molecules and CTC cluster–related markers. Furthermore, it was also found that HMGB3 mutations were favorably related to tumor-associated immune cells through the TIMER2.0 online tool. We further demonstrated that PDAC patients with higher HMGB3 expression had significantly worse overall survival (OS) in multiple datasets. In summary, our study suggests that HMGB3 is a hub gene associated with EMT in CTCs, the formation of CTC clusters, and infiltration patterns of immune cells favorable for tumor progression and metastasis to distant organs.

NOTCH4 mutation as a potential predictive biomarker for immunotherapy in NRAS wildtype melanoma.

e21594 Background: NRAS wildtype melanoma account for 80-85% melanoma patients and have been reported had a better response for immunotherapy. Although PD-L1 expression and tumor mutation burden (TMB) have been considered as important biomarkers for immunotherapy in many types of tumors, the predictive efficacy of them in melanoma is controversial. Since evidences showed NOTCH pathway mutation was a potential predictive biomarker for immune checkpoint inhibitors in some types of tumors. Here we explored the relationship between NOTCH family genes mutations and efficacy of NRAS wildtype melanoma immunotherapy. Methods: 265 NRAS wildtype ICI-pretreatment melanomas from cBioPortal (https://www.cbioportal.org), which is divided to discovery (N = 76) and validation (N = 189) cohort to analyze the association between NOTCH family genes (NOTCH1-4) mutation and efficacy of ICIs therapy. All nonsynonymous somatic mutations, including nonsense, missense, nonstop, frameshift deletion and insertion, in-frame deletion and insertion, and splice site mutations were considered for inclusion in our study. The potential mechanism was subsequently explored through RNA expression in immunotherapy treated population. Results: Patients with NOTCH4-Mut were identified to be associated with prolonged overall survival (OS) in discovery (HR: 0.30, 95%CI: 0.11-0.83, P = 0.01) and validation cohort (HR: 0.21, 95%CI: 0.07-0.68, P = 0.003). Further exploration found that NOTCH4-Mut tumors had higher tumor mutation burden (TMB) and tumor neoantigen burden (TNB) (P &lt; 0.05). RNA data revealed that enhanced anti-tumor immunity was observed in NOTCH4-Mut tumors. Activated CD4 memory T cell, CD8 T cell, follicular helper T cell (Tfh) and Neutrophils were more abundant in NOTCH4-Mut tumors. In addition, the results of enrichment analysis showed that several immune-related pathways varied significantly between NOTCH4-Mut and NOTCH4-Wt tumors, including Interferon γ response, DNA repair, epithelial mesenchymal transition (EMT), angiogenesis. Conclusions: NOTCH4 mutation may promote tumor immunity and serve as a biomarker to predict good immune response in NRAS wildtype melanoma and guiding immunotherapeutic responsiveness.