Signaling Pathway Enrichment Analysis Research Articles

Network pharmacology-based and molecular docking forecast mechanism of Shan Zhuyu-ShanYao for treatment in Alzheimer’s disease

The effective components and key targets of Shan Zhuyu (Cornus officinalis Sieb.et Zucc, SZY)-ShanYao (Dioscorea opposita Thunb, SY) (SS) in the treatment of Alzheimer’s disease (AD, neurodegenerative disease) were screened by network pharmacology (NP) and molecular docking (MD) technology in this study. We obtained 25 potential bioactive ingredients, 88 putative targets of SS and 4893 related-AD targets. Traditional Chinese Medicine of SS has 77 common targets with AD disease.The network of drug-disease was fabricated 7 key pharmacodynamic components. Interaction network construction and topological analysis yielded, 8 anti-AD targets of SS were filtered. MD investigations showed that bioactive compounds (Hydroxygenkwanin and hancinone C) could stably bind to the key target proteins. 13 pathways related to AD were revealed signaling pathway and functional enrichment analysis. Among them, identified a statistically high significance of the calcium signaling pathway and a variety of calcium channels have been shown to be altered in AD. Our studies confirmed multiple active ingredients, potential targets about pathways of SS, by regulating the active components combined with relevant target proteins in the calcium signaling pathway, which are crucial in the accumulation of neurofbrillary tangles (NFTs) and amyloid-β (Aβ) plaques. Thereby, this furnishes a robust foundation for subsequent experimental studies.

Identification of Key Genes and Signaling Pathways in Entrectinibresistant Non-small Cell Lung Cancer Using Bioinformatic Analysis and Experimental Verification.

Entrectinib, a ROS1 inhibitor, is effective in patients with ROS1-positive non-small-cell lung cancer (NSCLC). However, entrectinib resistance remains a challenge worldwide. The biomarkers of entrectinib resistance and molecular mechanisms have not been clarified based on the Gene Expression Omnibus (GEO) database. The aim of this study is to identify key genes and signaling pathways involved in the development of entrectinib-resistant NSCLC through bioinformatics analysis and experimental validation. Differentially expressed genes (DEGs) were screened between entrectinib resistant and parental human NSCLC cell lines of the GSE214715 dataset, lung adenocarcinoma (LUAD) and non-tumor adjacent tissues of the GSE75037 dataset, and NSCLC and non-tumor adjacent tissues of the GSE18842 dataset. Functional enrichment analyses were performed, including Gene Ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Overlapped DEGs among those three datasets were identified using the Venn diagram package. The transcriptional levels of key genes were investigated using the University of ALabama at Birmingham CANcer data analysis Portal (UALCAN). The association between transcriptional levels of key genes and survival was analyzed using Kaplan-Meier Plotter (https://www.kmplot.com/analysis/). The correlations between hub genes and immune cell infiltration were investigated using the Tumor Immune Estimation Resource (TIMER) database. Specific signaling pathway enrichment analysis was performed using Gene Set Enrichment Analysis (GSEA) of LinkedOmics. Competitive endogenous RNA (ceRNA) networks, genome-wide association studies (GWAS), and drug sensitivity analyses of key genes were further investigated. The expression of ZEB2 was subsequently confirmed in both parental HCC78 cells and entrectinib-resistant HCC78 cells using real-time quantitative polymerase chain reaction (qRT-PCR). 708 DEGs were identified between entrectinib-resistant CUTO28 (CUTO28-ER) and parental CUTO28 cell lines in the GSE214715 dataset. One thousand three hundred and ninety-five DEGs were identified between entrectinib resistant (CUTO37-ER) and parental CUTO37 cell lines in the GSE214715 dataset. Eight hundred and forty-nine DEGs were identified between LUAD and non-tumor adjacent tissues in the GSE75037 dataset. Seven hundred and sevety-three DEGs were identified between NSCLC and non-tumor adjacent tissues in the GSE18842 dataset. Among these three datasets, seven overlapped DEGs were identified, including ZBED2, CHI3L2, CELF2, SEMA5A, ZEB2, S100A12, and PDK4. Among these seven overlapped DEGs, the expression levels of CHI3L2, ZEB2, and S100A12 were downregulated in those three datasets. The results of analysis using the UALCAN database showed that these three genes were significantly downregulated in LUAD and LUSC patients compared with the normal population. However, only the lower transcriptional level of ZEB2 was linked to worse survival in patients with lung cancer. GSEA analysis revealed that ZEB2 was significantly negatively correlated with nucleotide excision repair (NER) in LUAD, and homologous recombination (HR) and NER in LUSC, which were linked to drug resistance. A ceRNA network of THRB-AS1/ has-miR-1293/ ZEB2 in LUAD was established. We have identified core genes associated with non-small cell resistance to entrectinib, including CHI3L2, ZEB2, and S100A12. ZEB2 is a core gene associated with acquired resistance to entetinib in NSCLC.

An integrated bioinformatics analysis to identify the shared biomarkers in patients with obstructive sleep apnea syndrome and nonalcoholic fatty liver disease.

Obstructive sleep apnea (OSA) syndrome and nonalcoholic fatty liver disease (NAFLD) have been shown to have a close association in previous studies, but their pathogeneses are unclear. This study explores the molecular mechanisms associated with the pathogenesis of OSA and NAFLD and identifies key predictive genes. Using the Gene Expression Omnibus (GEO) database, we obtained gene expression profiles GSE38792 for OSA and GSE89632 for NAFLD and related clinical characteristics. Mitochondrial unfolded protein response-related genes (UPRmtRGs) were acquired by collating and collecting UPRmtRGs from the GeneCards database and relevant literature from PubMed. The differentially expressed genes (DEGs) associated with OSA and NAFLD were identified using differential expression analysis. Gene Set Enrichment Analysis (GSEA) was conducted for signaling pathway enrichment analysis of related disease genes. Based on the STRING database, protein-protein interaction (PPI) analysis was performed on differentially co-expressed genes (Co-DEGs), and the Cytoscape software (version 3.9.1) was used to visualize the PPI network model. In addition, the GeneMANIA website was used to predict and construct the functional similar genes of the selected Co-DEGs. Key predictor genes were analyzed using the receiver operating characteristic (ROC) curve. The intersection of differentially expressed genes shared between OSA and NAFLD-related gene expression profiles with UPRmtRGs yielded four Co-DEGs: ASS1, HDAC2, SIRT3, and VEGFA. GSEA obtained the relevant enrichment signaling pathways for OSA and NAFLD. PPI network results showed that all four Co-DEGs interacted (except for ASS1 and HDAC2). Ultimately, key predictor genes were selected in the ROC curve, including HDAC2 (OSA: AUC = 0.812; NAFLD: AUC = 0.729), SIRT3 (OSA: AUC = 0.775; NAFLD: AUC = 0.750), and VEGFA (OSA: AUC = 0.812; NAFLD: AUC = 0.861) (they have a high degree of accuracy in predicting whether a subject will develop two diseases). In this study, four co-expression differential genes for OSA and NAFLD were obtained, and they can predict the occurrence of both diseases. Transcriptional mechanisms involved in OSA and NAFLD interactions may be better understood by exploring these key genes. Simultaneously, this study provides potential diagnostic and therapeutic markers for patients with OSA and NAFLD.

Single-cell landscape of the immune microenvironment of leptomeningeal metastases in non-small cell lung cancer treated with pemetrexed sheath injection.

e20026 Background: The incidence of leptomeningeal metastasis (LM) is increasing in non-small cell lung cancer (NSCLC) and pemetrexed injection is an important treatment for LM. Here, we used single-cell RNA sequencing (scRNA-seq) to define the immune landscape of LM in NSCLC treated with pemetrexed sheath injection. Methods: scRNA-seq was utilized on 27 cerebrospinal fluid (CSF) samples from 20 patients, including 7 pairs of pre- and post-treatment samples. Detailed immune landscapes were mapped, and key results were confirmed by flow cytometry and IHC. Biomarkers for the efficacy of pemetrexed sheath injection was analyzed. Results: The LM microenvironment was characterized by macrophages and cancer cells with decreased significantly after pemetrexed injection. The cancer cells in LM was highly expressed CEACAM6, SFTPB and NAPSA, and chemokines liked CXCL16 in macrophages decreased significantly after receiving pemetrexed sheath treatment than pre- treatment, which was validated by flow cytometry and IHC. In the signal pathway enrichment analysis, significant changes of metabolism and cell cycle genes occurred before and after pemetrexed injection. Moreover, the analysis of tumor cells and immune cells interaction showed that CSF1-CSF1R, AREG/HBEGF-EGFR, FD1-Intergrin_a2B1_complex, CCL5-CCR1, CD55_ADGRE play a key role in tumor cells recruiting monocytes and inhibiting macrophages. Gene set based on the efficacy of pemetrexed sheath injection was enriched, including C15orf48, CCL5, DUSP6, FLNA, TXNIP, TNNT1, was confirmed associating with increased overall survival. Conclusions: Our study characterizes the immune cell landscape of LM from NSCLC, and provided the biomarkers for the efficacy of pemetrexed injection.

Diagnostic, prognostic, and immunological roles of CDSN in ovarian cancer

Globally, ovarian cancer (OC) ranks as a principal cause of cancer-related mortality in females. Immunotherapy has revolutionized the treatment of OC, but the efficacy of immunotherapy is often limited by different immune microenvironments. The objective of this research was to pinpoint and validate candidate genes with potential value as diagnostic and prognostic biomarkers and therapeutic targets in OC. Data on genes associated with gene mutation, prognostic survival, and immune infiltration in OC were procured from the Cancer Genome Atlas (TCGA). Gene differential analysis, mutation site analysis, prognosis and survival analysis, and functional and signaling pathway enrichment analysis were conducted to identify and evaluate key genes. The genes were further investigated using immune infiltration analysis, receiver operating characteristic curves, and immunohistochemistry. The impact of CDSN on OC cell proliferation was investigated utilizing CCK-8, colony formation, and apoptosis detection assays. We identified a set of genes (CDSN, WARS, and CD38) that were highly expressed in OC and significantly associated with mutations and prognosis. Immune infiltration analysis and immunohistochemistry results indicated a correlation with immune infiltration in the tumor microenvironment, particularly in antigen-presenting cells. Receiver operating characteristic curve analysis demonstrated the diagnostic potential of these three genes in OC, with all three genes showing the area under the curve (AUC) above 0.8. In vitro studies suggested that knocked down CDSN expression resulted in a marked lower in the proliferative capacity of OC cells. The candidate gene CDSN identified through bioinformatics analysis and in vitro experiments is associated with mutation and immune infiltration, showing promise as a diagnostic and prognostic biomarker, as well as a therapeutic objective in OC.

Single-cell and bulk sequencing analysis to evaluate the oncogenic role of PDE3A in pan-cancer and validation in breast cancer.

e15128 Background: PDE3A is involved in critical physiological processes through the hydrolysis of cycle AMP (cAMP) and GMP (cGMP). Its role in the occurrence and progression of cancer has recently attracted attention, but carcinogenic mechanism in pan-cancer has not been fully elucidated. Methods: We explored the expression, prognostic and diagnostic value, mutation, methylation, immune infiltration, and signaling pathway enrichment analysis of PDE3A in pan-cancer by combining multiple bioinformatics databases and single-cell sequencing analysis. Furthermore, we verified the protein and mRNA expression levels of PDE3A and investigated its oncogenic role in the progression of breast cancer (BRCA). Results: PDE3A was expressed at lower levels than normal tissues in most cancers and showed a wonderful prognostic value. PDE3A was strongly correlated with immune cells, especially cancer-associated fibroblast (CAF), and was involved in various vital signaling pathways. Furthermore, PDE3A could facilitate BRCA progression by promoting cells invasion and migration, and it may be associated with the efficacy of endocrine therapy in ER+ BRCA. Conclusions: We provided new insights into the carcinogenic effect of PDE3A in pan-cancer. PDE3A may be a potential biomarker for cancer diagnosis and prognosis, and it is also a promising target for cancer immunotherapy.

Informational Analysis and Prediction of Obsessive-Compulsive Disorder Pathogenesis.

We aimed to predict the possible mechanism of obsessive-compulsive disorder (OCD) by integrating and analyzing mRNA sequencing results from two datasets and to provide direction for future studies into the pathogenesis of OCD. Two OCD datasets, GSE78104 and GSE60190, were obtained, and the intersection of the two gene sets with differential expression in OCD samples was selected. Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathway enrichment and Gene Ontology (GO) analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) online analysis website for the genes at the intersection, and the data were mapped using http://www.bioinformatics.com.cn. After genes with p≤0.05 had been screened out, protein-protein interaction (PPI) interaction analysis was conducted using Metascape to screen the key Molecular Complex Detection (MCODE) genes. MCODE genes were then enriched using the KEGG signaling pathway and GO classification. A total of 3,449 differentially expressed genes (DEGs) were obtained from the GSE78104 and GSE60190 datasets. KEGG, GO, and Gene Set Enrichment Analysis analyses of DEGs showed that the onset of OCD was related to oxidative phosphorylation and other metabolic processes, which may have a similar pathogenesis to other neurodegenerative diseases. Single-gene PPI analysis of SAPAP3 revealed that the mechanism by which SAPAP3 knockout induces OCD may also be caused by affecting oxidative phosphorylation. The mechanism of SAPAP3 knockout-induced OCD in mice may be due to the oxidative phosphorylation process in the body. Future studies on the neural circuit mechanism of OCD should be conducted.

The influence of knocking down the expression of low-density lipoprotein receptor associated proteins on the vascular abnormalities in hepatocellular carcinoma and its mechanisms

Objectives: To investigate the effect of the expression of low-density lipoprotein receptor associated protein (LDLR) on the vascular abnormalities in hepatocellular carcinoma (HCC) and its mechanisms. Methods: Based on the information of Oncomine Cancer GeneChip database, we analyzed the correlation between the expression level of LDLR and the expression level of carcinoembryonic antigen (CEA) and CD31 in hepatocellular carcinoma tissues. Lentiviral transfection of short hairpin RNA target genes was used to construct LDLR-knockdown MHCC-97H and HLE hepatocellular carcinoma cells. The differential genes and their expression level changes in LDLR-knockdown hepatocellular carcinoma cells were detected by transcriptome sequencing, real-time fluorescence quantitative polymerase chain reaction, and protein immunoblotting. The gene-related signaling pathways that involve LDLR were clarified by enrichment analysis. The effect of LDLR on CEA was assessed by the detection of CEA content in conditioned medium of hepatocellular carcinoma cells. Angiogenesis assay was used to detect the effect of LDLR on the angiogenic capacity of human umbilical vein endothelial cells, as well as the role of CEA in the regulation of angiogenesis by LDLR. Immunohistochemical staining was used to detect the expression levels of LDLR in 176 hepatocellular carcinoma tissues, and CEA and CD31 in 146 hepatocellular carcinoma tissues, and analyze the correlations between the expression levels of LDLR, CEA, and CD31 in the tissues, serum CEA, and alanine transaminase (ALT). Results: Oncomine database analysis showed that the expressions of LDLR and CEA in the tissues of hepatocellular carcinoma patients with portal vein metastasis were negatively correlated (r=-0.64, P=0.001), whereas the expressions of CEA and CD31 in these tissues were positively correlated ( r=0.46, P=0.010). The transcriptome sequencing results showed that there were a total of 1 032 differentially expressed genes in the LDLR-knockdown group and the control group of MHCC-97H cells, of which 517 genes were up-regulated and 515 genes were down-regulated. The transcript expression level of CEACAM5 was significantly up-regulated in the cells of the LDLR-knockdown group. The Gene Ontology (GO) function enrichment analysis showed that the differential genes were most obviously enriched in the angiogenesis function. The Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis showed that the relevant pathways involved mainly included the cellular adhesion patch, the extracellular matrix receptor interactions, and the interactions with the extracellular matrix receptors. The CEA content in the conditioned medium of the LDLR-knockdown group was 43.75±8.43, which was higher than that of the control group (1.15±0.14, P＜0.001). The results of angiogenesis experiments showed that at 5 h, the number of main junctions, the number of main segments, and the total area of the lattice formed by HUVEC cells cultured with the conditioned medium of MHCC-97H cells in the LDLR-knockdown group were 295.3±26.4, 552.5±63.8, and 2 239 781.0±13 8211.9 square pixels, which were higher than those of the control group (113.3±23.5, 194.8±36.5, and 660 621.0±280 328.3 square pixels, respectively, all P＜0.01).The number of vascular major junctions, the number of major segments, and the total area of the lattice formed by HUVEC cells cultured in conditioned medium with HLE cells in the LDLR-knockdown group were 245.3±42.4, 257.5±20.4, and 2 535 754.5±249 094.2 square pixels, respectively, which were all higher than those of the control group (113.3±23.5, 114.3±12.2, and 1 565 456.5±219 259.7 square pixels, respectively, all P＜0.01). In the conditioned medium for the control group of MHCC-97H cells,the number of main junctions, the number of main segments, and the total area of the lattice formed by the addition of CEA to cultured HUVEC cells were 178.9±12.0, 286.9±12.3, and 1 966 990.0±126 249.5 spixels, which were higher than those in the control group (119.7±22.1, 202.7±33.7, and 1 421 191.0±189 837.8 square pixels, respectively). The expression of LDLR in hepatocellular carcinoma tissues was not correlated with the expression of CEA, but was negatively correlated with the expression of CD31 (r=-0.167, P=0.044), the level of serum CEA (r=-0.061, P=0.032), and the level of serum ALT(r=-0.147,P=0.05). The expression of CEA in hepatocellular carcinoma tissues was positively correlated with the expression of CD31 (r=0.192, P=0.020). The level of serum CEA was positively correlated with the level of serum ALT (r=0.164, P=0.029). Conclusion: Knocking down LDLR can promote vascular abnormalities in HCC by releasing CEA.

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.

Identification of Differentially Expressed mRNAs and miRNAs and Related Regulatory Networks in Cumulus Oophorus Complexes Associated with Fertilization.

Cumulus oophorus complexes (COCs) are the first extracellular barriers that sperm must pass through to fuse with oocytes, which have an important role in oocyte maturation and fertilization. However, little is known about the molecular mechanisms of COCs involved in fertilization. In this study, COCs were collected and then randomly divided into a test group that interacted with sperm and a control group that did not interact with sperm. Then, the total RNA was extracted; RNA transcriptome and small RNA libraries were prepared, sequenced, and analyzed. The results showed that 1283 differentially expressed genes (DEGs), including 560 upregulated and 723 downregulated genes. In addition, 57 differentially expressed miRNAs (DEMIs) with 35 upregulated and 22 downregulated were also detected. After the RNA-seq results were verified by RT-qPCR, 86 effective DEGs and 40 DEMIs were finally screened and a DEMI-DEG regulatory network was constructed. From this, the top ten hub target genes were HNF4A, SPN, WSCD1, TMEM239, SLC2A4, E2F2, SIAH3, ADORA3, PIK3R2, and GDNF, and they were all downregulated. The top ten hub DEMIs were miR-6876-5p, miR-877-3p, miR-6818-5p, miR-4690-3p, miR-6789-3p, miR-6837-5p, miR-6861-5p, miR-4421, miR-6501-5p, and miR-6875-3p, all of which were upregulated. The KEGG signaling pathway enrichment analysis showed that the effective DEGs were significantly enriched in the calcium, AMPK, and phospholipase D signaling pathways. Our study identified several DEGs and DEMIs and potential miRNA-mRNA regulatory pathways in COCs and these may contribute to fertilization. This study may provide novel insights into potential biomarkers for fertilization failure.

Study on the Anti-Periodontitis Mechanism of Eucommia ulmoides Based on Network Pharmacology

Periodontitis is a chronic inflammation of periodontal support tissue caused by local factors. Eucommia ulmoides, a traditional Chinese medicinal herb, has a significant therapeutic effect on periodontitis, but its mechanism of action is still unclear. In this study network pharmacology method was used to deeply elucidate the pharmacological substance basis and mechanism of Eucommia ulmoides in treating periodontitis. The protein interaction network (PPI) was constructed using the STRING database. The GO and KEGG signal pathway enrichment analyses of the intersected targets were performed using the DAVID database to predict the mechanism of action. The results indicate that Eucommia ulmoides exerted its therapeutic effect on periodontitis through a synergistic mechanism of multiple components, targets, and pathways. The top 8 therapeutic targets were identified, including EGFR, HIF1A, MMP9, ESR1, JUN, PPARG, AKT1, and SRC. Prolactin and HIF-1 signaling pathway may be the key mechanism of Eucommia ulmoides in treating periodontitis.

Umbilical Cord Blood-Derived Cells Can Reconstruct Hematopoiesis in an Aplastic Anemia Animal Model.

To explore the efficacy and the mechanism of the umbilical cord-derived cells combined with cyclosporine A (CsA) in treating aplastic anemia (AA) in mice. Immune-mediated AA model mice were treated with CsA + UC mesenchymal stem cells (UC-MSC), CsA + umbilical cord blood regulatory T cells (UCB-Treg), UC-MSC, UCB-Treg, CsA alone, or blank control, respectively (n = 9 mice/group). CsA and the cell infusion was administered on d0. Routine peripheral blood testing was performed once weekly; bone marrow colony culture, bone marrow cell flow cytometry, peripheral blood T cell subsets, and serum inflammatory cytokines tests were performed on d14. Transcriptome sequencing was performed for cells from CsA + UC-MSC, CsA + UCB-Treg, and CsA groups to detect the possible related genes. Gene function cluster and signal pathway enrichment analysis were also performed. Blank control mice died due to pancytopenia within 21 days, whereas mice in other groups survived for >28 days. On d14, the CsA + UC-MSC and CsA + UCB-Treg groups had higher white blood cell (WBC) counts than the other groups (p < 0.05), along with higher burst-forming unit (BFU) and colony-forming unit-granulocyte, macrophage (CFU-GM) counts (p < 0.01). The CsA + UC-MSC group had the highest BFU count (p < 0.01). The CsA + UC-MSC and CsA + UCB-Treg groups exhibited the highest bone marrow CD34+ cell proportion (9.68% ± 1.35% and 8.17% ± 0.53%, respectively; p < 0.01). Tumor necrosis factor (TNF)-α and interleukin (IL)-2 levels in the CsA + UC-MSC group (p < 0.05) and TNF-α, interleukin-2, and interferon (INF)-γ levels in the CsA + UC-Treg group (p < 0.01) were lower than those in the CsA group. Compared with CsA treatment, CsA + UC-MSC significantly downregulated the histone methylation pathway (p < 0.05), whereas CsA + UCB-Treg significantly upregulated energy metabolism processes (p < 0.05). Treatment with CsA + UC-MSC upregulated superoxide dismutase activity compared with CsA + UCB-Treg treatment. Adding UC-MSC or UCB-Treg to CsA markedly enhanced the reconstruction of hematopoiesis in AA mice, with UC-MSC eliciting greater efficiency than UCB-Treg. Accordingly, the addition of these cells could further improve immune abnormalities.

Network pharmacology and molecular docking of endogenous active metabolites in diabetic kidney disease

Objectives Network pharmacology and molecular docking were used to predict endogenous active metabolites with protective effects in diabetic kidney disease (DKD). Methods We utilized metabolomics to screen differentially expressed metabolites in kidney tissues of mice with type 2 DKD and predicted potential targets using relevant databases. The interaction network between endogenous active metabolites and target proteins was established by integrating differentially expressed metabolites and proteins associated with DKD identified through proteomics. Gene ontology (GO) and signaling pathway enrichment analysis were performed. The biological functions of the active candidate metabolites and their effects on downstream pathways were also verified. Results Metabolomics revealed 130 differentially expressed metabolites. Through co-expression network analysis coupled with the investigation of differentially expressed proteins in proteomics, 2-hydroxyphenylpropionylglycine (2-HPG) emerged as a key regulator of DKD. 2-HPG was found to modulate the progression of DKD by regulating the conformation and activity of synaptophysin 1 (SYNJ1), with a correlation coefficient of 0.974. In vivo experiments revealed that SYNJ1 expression was significantly downregulated in the Macroalbuminuria Group compared to the Control Group and negatively correlated with proteinuria (r = −0.7137), indicating its important role in DKD progression. Immunofluorescence demonstrated that treatment with 2-HPG restores the expression of the foot process marker protein Wilms tumor-1 (WT-1) in podocytes injured by high glucose levels. Western blot and polymerase chain reaction support the involvement of SYNJ1 in this process. Conclusions This study demonstrated the significance of the 2-HPG/SYNJ1 signaling axis in safeguarding the foot process of podocytes in DKD.

Expression of interleukin-34 in tongue squamous cell carcinoma and its clinical implications

To investigate the expression of interleukin- 34 (IL-34) in tongue squamous cell carcinoma (TSCC) and its clinical implications. Serum IL-34 level was detected in 36 patients with TSCC and 36 healthy individuals using enzymelinked immunosorbent assay (ELISA). The expressions of IL-34 mRNA and protein levels in TSCC and adjacent tissues were examined in 41 patients using real-time fluorescence quantitative PCR (qRT-PCR) and immunohistochemistry (IHC), and their correlation with the clinicopathological features of the patients was further analyzed. Informatic analysis of the differentially expressed genes related with IL-34 in TSCC was carried out based on String database, LinkedOmics database and GEO database, and GO functional analysis and KEGG signaling pathway enrichment analysis were performed using Webgestalt database. The serum level of IL-34 was significantly lower in TSCC patients than in the healthy individuals (P < 0.001), and its expression level was also significantly lower in the tumor tissues than in the adjacent tissues (P < 0.001). The expression level of IL-34 in TSCC tissues was related with lymph node metastasis and TNM staging (P < 0.05), but not with age, gender, smoking, drinking, or tumor size (P > 0.05). Informatic analysis suggested that IL-34 had the strongest correlation with CSF1R and PTPRJ. IL-34 and its related genes in TSCC were enriched mainly in bone marrow cell differentiation, collagen-containing extracellular matrix, and cytokine binding and signal receptor activator activity. KEGG signaling pathway enrichment showed that IL-34 and the related differentially expressed genes were involved mainly in osteoclast differentiation, protein polysaccharide in cancer, and the MAPK signaling pathway. IL-34 is lowly expressed in TSCC and participates in the occurrence and progression of TSCC, and can be potentially used as a new diagnostic biomarker and therapeutic target for TSCC.

Comprehensive analysis of thirteen-gene panel with prognosis value in Multiple Myeloma.

Although there are many treatments for Multiple myeloma (MM), patients with MM still unable to escape the recurrence and aggravation of the disease. We constructed a risk model based on genes closely associated with MM prognosis to predict its prognostic value. Gene function enrichment and signal pathway enrichment analysis, Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, univariate and multivariate Cox regression analysis, Kaplan-Meier (KM) survival analysis and Receiver Operating Characteristic (ROC) analysis were used to identify the prognostic gene signature for MM. Finally, the prognostic gene signature was validated using the Gene Expression Omnibus (GEO) database. Thirteen prognostic genes were screened by univariate Cox analysis and LASSO regression analysis. Multivariate Cox analysis revealed risk score to be an independent prognostic factor for patients with MM [Hazard Ratio (HR) = 2.564, 95% Confidence Interval (CI) = 2.223-2.958, P< 0.001]. The risk score had a high level of predictive value according to ROC analysis, with an area under the curve (AUC) of 0.744. The potential prognostic signature of thirteen genes were assessed and a risk model was constructed that significantly correlated with prognosis in MM patients.

Combining Network Pharmacology, Molecular Docking and Preliminary Experiments to Explore the Mechanism of Action of FZKA Formula on Non-small Cell Lung Cancer.

Clinically, Fuzhengkangai formulation (FZKA) has been proven to have significant therapeutic effects on non-small lung cancer (NSCLC), although the mechanism is unknown. We aimed to explore the potential mechanism of FZKA in the treatment of NSCLC in this study. We obtained the active components and targets of FZKA by TCMSP. The target genes of NSCLC were searched from OMIM, GEO (GSE18842), and GeneCards database. Cytoscape (3.7.2) software was used to construct a "drug-compound-cross-target interaction" interaction network, and the STING database was used to analyze previous cross-target interactions. Meanwhile, the results were visualized and processed by performing GO enrichment analysis and KEGG signaling pathway enrichment analysis at the target site. The core targets were docked with active components through AutoDockTools-1.5.6 software. Finally, we used cellular experiments to validate the bioinformatics predictions. There were 40 active and 465 potential genes from the TCMSP database. Key active chemicals, namely Quercetin, Kaempferol, Luteolin, and Tanshinone IIA, and 176 targets were deemed as targets of FZKA against NSCLC by PPI network analysis. GO and KEGG enrichment analyses suggest that FZKA acts primarily through the PI3K-AKT and MAPK signaling pathways in the treatment of NSCLC. Moreover, cellular assays showed that Quercetin, Kaempferol, Luteolin, and Tanshinone IIA not only reduced the viability of A549 cells and promoted apoptosis but also significantly decreased the p-AKT/AKT and p-ERK1/2/ERK1/2 ratios. Our data suggested that FZKA can be involved in the treatment of NSCLC through multiple components, targets and pathways.

OSM May Serve as a Biomarker of Poor Prognosis in Clear Cell Renal Cell Carcinoma and Promote Tumor Cell Invasion and Migration.

Currently, the role of oncostatin M (OSM) in clear cell renal cell carcinoma (ccRCC) has not been investigated. This study will explore the impact of OSM on ccRCC expression, prognosis, and cell function. In this study, we used The Cancer Genome Atlas (TCGA) database to evaluate OSM expression characteristics, pathogenic factor distribution, and prognostic aspects in ccRCC. We also combined this analysis with qRT-PCR to verify OSM mRNA expression levels at the tissue level. Then, the effects of OSM on the proliferation, invasion, and migration abilities of ccRCC cells were explored through CCK8, Transwell, Western blotting, and immunofluorescence experiments. Finally, the oncogenic mechanisms associated with OSM in ccRCC were explored through signaling pathway enrichment and single-cell analysis. The results demonstrated that OSM was significantly more expressed in ccRCC than in normal tissues. According to the survival analysis, OSM in ccRCC was considerably worse in the group with high expression than in the group with low expression. Also, the univariate and multivariate Cox analyses of clinical characteristics show that OSM in ccRCC may be able to predict a poor prognosis on its own as a biomarker. In vitro cellular experiments demonstrated that high OSM expression had no discernible impact on ccRCC cell proliferation compared to the control group, but it did promote tumor cell invasion and migration. Signaling pathways and single-cell analysis revealed that OSM might promote ccRCC invasion and migration through M2 macrophages. In conclusion, OSM may serve as an independent poor prognostic biomarker in ccRCC and promote tumor cell invasion and migration. This discovery is expected to provide a new therapeutic target for patients with recurrent and metastatic ccRCC.

Validation of a Novel Cuproptosis-Related Prognostic Gene Marker and Differential Expression Associated with Lung Adenocarcinoma.

Cuproptosis induction is seen as a promising alternative for immunotherapies and targeted therapies in breast cancer. The objective of this research was to examine the prognostic and biological importance of cuproptosis-related genes (CRGs) in lung adenocarcinoma (LUAD). The following methods were used: GSE10072 dataset and TCGA database analysis, differential expression analysis of CRGs, and biological function (BP) and signaling pathway enrichment analysis, prognostic analysis and clinical analysis of CRGs, construction of the prognostic signature and RNA modified genes and miRNA analysis of CRGs in LUAD, immunoinfiltration analysis and immunohistochemical staining of DβH, UBE2D3, SOD1, UBE2D1 and LOXL2. AOC1, ATOX1, CCL8, CCS, COX11, CP, LOXL2, MAP2K2, PDK1, SCO2, SOD1, UBE2D1, UBE2D3 and VEGFA showed significantly higher expression, while ATP7B, DβH, PDE3B, SLC31A2, UBE2D2, UBE2D4 and ULK2 showed lower expression in LUAD tissues than normal tissues. We also found that ATP7B (4%), AOC1 (3%) PDE3B (2%), DβH (2%), CP (1%), ULK2 (1%), PDK1 (1%), LOXL2 (1%) and UBE2D3 (1%) showed higher mutation frequencies. The univariate Cox analysis was used to identify CRGs that have prognostic value. It identified 21 genes that showed significant prognostic value, containing DβH, UBE2D3, SOD1, UBE2D1 and LOXL2. Patients with DβH up-expression have a longer survival time and patients with UBE2D3, SOD1, UBE2D1 and LOXL2 down-expression also have a longer survival time. hsa-miR-29c-3p, hsa-miR-29a-3p, hsa-miR-181c-5p, hsa-miR-1245a, etc., play an important role in the miRNA regulatory network, and in LUAD, miR-29a, miR-29c and miR-181c high expression survival was longer, and miR-1245a low expression survival was longer. We also performed an analysis to examine the relationships between DβH, LOXL2, SOD1, UBE2D1 and UBE2D3 and immune infiltration in LUAD, including B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils and DCs. DβH, UBE2D3, SOD1, UBE2D1, and LOXL2 are potential candidates implicated in LUAD and can be further explored for their application as diagnostic, prognostic, and therapeutic biomarkers for LUAD.

Effect and molecular mechanism of Sulforaphane alleviates brain damage caused by acute carbon monoxide poisoning:Network pharmacology analysis, molecular docking, and experimental evidence.

Sulforaphane (SFN) has attracted much attention due to its ability on antioxidant, anti-inflammatory, and anti-apoptotic properties, while its functional targets and underlying mechanism of action on brain injury caused by acute carbon monoxide poisoning (ACOP) have not been fully elucidated. Herein, we used a systematic network pharmacology approach to explore the mechanism of SFN in the treatment of brain damage after ACOP. In this study, the results of network pharmacology demonstrated that there were a total of 81 effective target genes of SFN and 36 drug-disease targets, which were strongly in connection with autophagy-animal signaling pathway, drug metabolism, and transcription disorders in cancer. Upon the further biological function and KEGG signaling pathway enrichment analysis, a large number of them were involved in neuronal death, reactive oxygen metabolic processes and immune functions. Moreover, based on the results of bioinformatics prediction associated with multiple potential targets and pathways, the AMP-activated protein kinase (AMPK) signaling pathway was selected to elucidate the molecular mechanism of SFN in the treatment of brain injury caused by ACOP. The following molecular docking analysis also confirmed that SFN can bind to AMPKα well through chemical bonds. In addition, an animal model of ACOP was established by exposure to carbon monoxide in a hyperbaric oxygen chamber to verify the predicted results of network pharmacology. We found that the mitochondrial ultrastructure of neurons in rats with ACOP was seriously damaged, and apoptotic cells increased significantly. The histopathological changes were obviously alleviated, apoptosis of cortical neurons was inhibited, and the number of Nissl bodies was increased in the SFN group as compared with the ACOP group (p < .05). Besides, the administration of SFN could increase the expressions of phosphorylated P-AMPK and MFN2 proteins and decrease the levels of DRP1, Caspase3, and Casapase9 proteins in the brain tissue of ACOP rats. These findings suggest that network pharmacology is a useful tool for traditional Chinese medicine (TCM) research, SFN can effectively inhibit apoptosis, protect cortical neurons from the toxicity of carbon monoxide through activating the AMPK pathway and may become a potential therapeutic strategy for brain injury after ACOP.

Exploring the mechanism and experimental validation of Fuzi Lizhong Tang in treating gastric cancer based on network pharmacology and molecular docking.

This study aimed to explore the mechanism of Fuzi Lizhong Tang (FZLZT) in treating gastric cancer using network pharmacology and molecular docking, and to validate the results through in vitro experiments. Active ingredients and target genes of FZLZT were obtained from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, while disease targets of gastric cancer were collected from GeneCards, OMIM, and DrugBank databases. The "herb-active ingredient-target gene" network was constructed using Cytoscape software, and core active ingredients were obtained through topological analysis. Protein-protein interaction analysis was performed using the STRING database, and core targets were obtained through topological analysis. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis were performed using the DAVID database. Molecular docking was conducted using AutoDock Vina software to verify the interaction between core ingredients and core targets. Cholecystokinin octapeptide (CCK-8) assay was used to determine the proliferation inhibition effect of FZLZT on AGS, BGC823, HGC-27, MGC-803, and SGC-7901 gastric cancer cell lines, and ANNEXIN V-FITC/PI double staining combined with flow cytometry was used to measure the cell apoptosis rate. Network pharmacology analysis revealed 117 active ingredients and 261 target genes of FZLZT, and 211 overlapping targets with gastric cancer. Ten core active ingredients were identified through topological analysis, including quercetin, 7-methoxy-2-methyl isoflavone, kaempferol, luteolin, naringenin, isorhamnetin, quercetagetin, glycyrrhizic acid A, β-sitosterol, and medioresinol. GO and KEGG enrichment analysis showed that the mechanism of FZLZT in treating gastric cancer mainly involves cancer, inflammation, metabolism, and blood rheology-related pathways, and may act through 7 core targets (CDKN1A, MYC, MAPK1, MAPK14, RB1, RELA, and STAT3). Molecular docking results further confirmed the prediction of network pharmacology. In vitro experiments showed that FZLZT inhibited the proliferation of all five gastric cancer cell lines, with the strongest effect on SGC-7901 cells, and induced apoptosis in SGC-7901 cells. FZLZT has a multi-component, multi-target, and multi-pathway characteristic in treating gastric cancer. Its active ingredients may regulate the expression of proteins such as CDKN1A, MYC, MAPK1, MAPK14, RB1, RELA, and STAT3 to activate cancer-related signaling pathways to achieve its therapeutic effect.