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2022 ◽  
Yu Sun ◽  
Jun Zhao

Abstract Background: Cancer is the leading cause of death in the world. The mechanism is not fully elucidated and the therapeutic effect is also unsatisfactory. In our study, we aim to find new target gene in pan-cancer.Methods: Differentially expressed genes (DEGs) was screened out in various types of cancers from GEO database. The expression of DEG (TCEAL2) in tumor cell lines, normal tissues and tumor tissues was calculated. Then the clinical characteristics, DNA methylation, tumor infiltration and gene enrichment of TCEAL2 was studied. Results: TCEAL2 expressions were down-regulated in most cancers. Its expression and methylation were positively or negatively associated with prognosis in different cancers. The tumor infiltration results revealed that TCEAL2 was significantly related with many immune cells especially NK cells and immune-related genes in majority cancers. Furthermore, tau protein and tubulin binding were involved in the molecular function mechanisms of TCEAL2. Conclusion: TCEAL2 may be a novel prognostic marker in different cancers and may affect tumor through immune infiltration.

2022 ◽  
Vol 2022 ◽  
pp. 1-8
Benzhuo Zhang ◽  
Wei Huang ◽  
Mingquan Yi ◽  
Chunxu Xing

Atherosclerotic cerebral infarction (ACI) seriously threatens the health of the senile patients, and the strategies are urgent for the diagnosis and treatment of ACI. This study investigated the mRNA profiling of the patients with ischemic stroke and atherosclerosis via excavating the datasets in the GEO database and attempted to reveal the biomarkers and molecular mechanism of ACI. In this study, GES16561 and GES100927 were obtained from Gene Expression Omnibus (GEO) database, and the related differentially expressed genes (DEGs) were analyzed with R language. Furthermore, the DEGs were analyzed with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Besides, the protein-protein interaction (PPI) network of DEGs was analyzed by STRING database and Cytoscape. The results showed that 133 downregulated DEGs and 234 upregulated DEGs were found in GES16561, 25 downregulated DEGs and 104 upregulated DEGs were found in GSE100927, and 6 common genes were found in GES16561 and GES100927. GO enrichment analysis showed that the functional models of the common genes were involved in neutrophil activation, neutrophil degranulation, neutrophil activation, and immune response. KEGG enrichment analysis showed that the DEGs in both GSE100927 and GSE16561 were connected with the pathways including Cell adhesion molecules (CAMs), Cytokine-cytokine receptor interaction, Phagosome, Antigen processing and presentation, and Staphylococcus aureus infection. The PPI network analysis showed that 9 common DEGs were found in GSE100927 and GSE16561, and a cluster with 6 nodes and 12 edges was also identified by PPI network analysis. In conclusion, this study suggested that FCGR3A and MAPK pathways were connected with ACI.

2022 ◽  
Jiaxin Fan ◽  
Chaowei Liang ◽  
Jiajia Wang ◽  
Chaojie Liang ◽  
Jiansheng Guo

Abstract Background:Neuromedin B(NMB) is associated with the occurrence and development of a variety of cancers, However, the role of NMB in colorectal cancer is lacking in further studies.Methods:Transcriptome data and clinical data of CRC were downloaded and analyzed from the TCGA database and GEO database to study the differential expression of NMB. We analyzed the relationship between NMB expression and survival in patients with colorectal cancer using 8 public datasets from the Gene Expression Integration (GEO) database and the TCGA database. Meta-analysis was performed on the analysis results of TCGA and GEO data to determine the role of NMB in CRC. The receiver operating characteristic (ROC) curve was used to evaluate the accuracy of NMB in predicting survival rate in CRC patients. Wilcox. Test and Kruskal. Tests were used to study the relationship between clinicopathological features and the expression of NMB. Cox regression analysis was used to analyze the effect of NMB expression on survival. Gene collection enrichment analysis (GSEA) was performed using the TCGA database to screen the signaling pathway regulated by NMB. The Linkedomics platform was used to identify NMB co-expressed genes and explore the potential mechanisms of NMB mediation. Tumor Immune Estimation Resource (TIMER) site database was used to analyze the relationship between NMB expression level and immune infiltration. Related genes were identified by co-expression analysis, and four genes (NDUFB10, SERF2, DPP7, and NAPRT) were screened out as a prognostic signature. The relationship between risk score and OS were studied to explore the predictive value of risk score for CRC. Nomogram was constructed to predict 1 - and 3-year survival in colorectal cancer patients.Results:NMB was highly expressed in colorectal cancer, suggested a poor prognosis. The ROC curve proved that NMB had a high accuracy in predicting the survival rate of CRC patients. Multivariate regression analysis demonstrated that NMB was an independent predictor of survival in patients with CRC.GSEA identified the pathways involved in NMB regulation, including the P53 Signaling pathway, VEGF Signaling pathway, JAK-STAT Signaling pathway, MAPK Signaling pathway,mTOR Signaling pathway, TGF-BETA Signaling pathway, and WNT Signaling pathway, etc. Then,6512 co-expressed genes were identified through the Linkedomics Platform to investigate the potential mechanisms of NMB regulation, including Hepatocellular carcinoma cell cycle, EGF/EGFR Signaling Pathway, VEGFA-VEGFR2 Signaling Pathway, etc. We also conclude that NMB is correlated with T cells CD8, T cells CD4 memory resting, Macrophages M0. Different mutational forms of NMB were associated with the immune infiltration of 6 leukocytes. We determined the relationship between NMB and immune marker sets in colorectal cancer, such as CCR7, CD3E, CTLA4, HAVCR2, HLA-DPB1. The predictive ability of the risk score was significantly better than that of T, N, and M stages. A new nomogram for predicting the 1-year and 3-year OS of CRC patients was constructed, showing good reliability and accuracy for improved treatment decisions. In addition, NMB may contribute to drug resistance in CRC.Conclusion:NMB is highly expressed in CRC and provides a potential biomarker for the diagnosis and prognosis of CRC.

2022 ◽  
Xin Tan ◽  
Wei Xian ◽  
Xiaorong Li ◽  
Yongfeng Chen ◽  
Jiayi Geng ◽  

Abstract Atrial fibrillation (AF) is a common atrial arrhythmia for which there is no specific therapeutic drug. Quercetin (Que) has been used to treat cardiovascular diseases such as arrhythmias. In this study, we explored the mechanism of action of Que in AF using network pharmacology and molecular docking. The chemical structure of Que was obtained from Pubchem. TCMSP, Swiss Target Prediction, Drugbank, STITCH, Binding DB, Pharmmapper, CTD, GeneCards, DISGENET and TTD were used to obtain drug component targets and AF-related genes, and extract AF and normal tissue by GEO database differentially expressed genes by GEO database. The top targets were IL6, VEGFA, JUN, MMP9 and EGFR, and Que for AF treatment might involve the lipid and atherosclerosis pathway, the role of AGE-RAGE signaling pathway in diabetic complications, MAPK signaling pathway and IL-17 signaling pathway. In addition, molecular docking showed that Que binds strongly to key targets and is differentially expressed in AF. This study systematically elucidated the key targets of Que treatment for AF and the specific mechanisms, providing a new direction for further basic experimental exploration and clinical treatment.

All Life ◽  
2022 ◽  
Vol 15 (1) ◽  
pp. 74-87
Xu He ◽  
Nanding Wang ◽  
Zhe Li ◽  
Sha Zhang ◽  
Zhen Yao ◽  

2022 ◽  
Vol 12 ◽  
Kaidi Zhao ◽  
Zhou Ma ◽  
Wei Zhang

Background:SPP1, secreted phosphoprotein 1, is a member of the small integrin-binding ligand N-linked glycoprotein (SIBLING) family. Previous studies have proven SPP1 overexpressed in a variety of cancers and can be identified as a prognostic factor, while no study has explored the function and carcinogenic mechanism of SPP1 in cervical cancer.Methods: We aimed to demonstrate the relationship between SPP1 expression and pan-cancer using The Cancer Genome Atlas (TCGA) database. Next, we validated SPP1 expression of cervical cancer in the Gene Expression Omnibus (GEO) database, including GSE7803, GSE63514, and GSE9750. The receiver operating characteristic (ROC) curve was used to evaluate the feasibility of SPP1 as a differentiating factor by the area under curve (AUC) score. Cox regression and logistic regression were performed to evaluate factors associated with prognosis. The SPP1-binding protein network was built by the STRING tool. Enrichment analysis by the R package clusterProfiler was used to explore potential function of SPP1. The single-sample GSEA (ssGSEA) method from the R package GSVA and TIMER database were used to investigate the association between the immune infiltration level and SPP1 expression in cervical cancer.Results: Pan-cancer data analysis showed that SPP1 expression was higher in most cancer types, including cervical cancer, and we got the same result in the GEO database. The ROC curve suggested that SPP1 could be a potential diagnostic biomarker (AUC = 0.877). High SPP1 expression was associated with poorer overall survival (OS) (P = 0.032). Further enrichment and immune infiltration analysis revealed that high SPP1 expression was correlated with regulating the infiltration level of neutrophil cells and some immune cell types, including macrophage and DC.Conclusion:SPP1 expression was higher in cervical cancer tissues than in normal cervical epithelial tissues. It was significantly associated with poor prognosis and immune cell infiltration. Thus, SPP1 may become a promising prognostic biomarker for cervical cancer patients.

2022 ◽  
Vol 12 ◽  
Kaidi Zhao ◽  
Yuexiong Yi ◽  
Zhou Ma ◽  
Wei Zhang

Background: Inhibin A (INHBA), a member of the TGF-β superfamily, has been shown to be differentially expressed in various cancer types and is associated with prognosis. However, its role in cervical cancer remains unclear.Methods: We aimed to demonstrate the relationship between INHBA expression and pan-cancer using The Cancer Genome Atlas (TCGA) database. Next, we validated INHBA expression in cervical cancer using the Gene Expression Omnibus (GEO) database, including GSE7803, GSE63514, and GSE9750 datasets. Enrichment analysis of INHBA was performed using the R package “clusterProfiler.” We analyzed the association between immune infiltration level and INHBA expression in cervical cancer using the single-sample gene set enrichment analysis (ssGSEA) method by the R package GSVA. We explored the association between INHBA expression and prognosis using the R package “survival”.Results: Pan-cancer data analysis showed that INHBA expression was elevated in 19 tumor types, including cervical cancer. We further confirmed that INHBA expression was higher in cervical cancer samples from GEO database and cervical cancer cell lines than in normal cervical cells. Survival prognosis analysis indicated that higher INHBA expression was significantly associated with reduced Overall Survival (p = 0.001), disease Specific Survival (p = 0.006), and Progression Free Interval (p = 0.001) in cervical cancer and poorer prognosis in other tumors. GSEA and infiltration analysis showed that INHBA expression was significantly associated with tumor progression and some types of immune infiltrating cells.Conclusion:INHBA was highly expressed in cervical cancer and was significantly associated with poor prognosis. Meanwhile, it was correlated with immune cell infiltration and could be used as a promising prognostic target for cervical cancer.

Adipocyte ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 56-68
Zhicong Zhao ◽  
Chenxi Wang ◽  
Jue Jia ◽  
Zhaoxiang Wang ◽  
Lian Li ◽  

Open Medicine ◽  
2022 ◽  
Vol 17 (1) ◽  
pp. 124-134
Yin-yin Peng ◽  
Hong-bin Zhang ◽  
Xin Wang ◽  
Qing Xiao ◽  
Shu-liang Guo

Abstract Gene expression profiling studies have shown the pathogenetic role of oncogenic pathways in extranodal natural killer/T-cell lymphoma (ENKL). In this study, we aimed to identify the microRNAs (miRNAs) playing potential roles in ENKL, and to evaluate the genes and biological pathways associated to them. Gene expression profiles of ENKL patients were acquired from the gene expression omnibus (GEO) database. Most differentially expressed (DE)-miRNAs were identified in ENKL patients using limma package. Gene targets of the DE-miRNAs were collected from online databases (miRDB, miRWalk, miRDIP, and TargetScan), and used in Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses on Database for annotation, visualization, and integrated discovery database, and then used in protein–protein interaction (PPI) analysis on STRING database. Hub genes of the PPI network were identified in cytoHubba, and were evaluated in Biological networks gene ontology. According to the series GSE31377 and GSE43958 from GEO database, four DE-miRNAs were screened out: hsa-miR-363-3p, hsa-miR-296-5p, hsa-miR-155-5p, and hsa-miR-221-3p. Totally 164 gene targets were collected from the online databases, and used in the GO and KEGG pathway analyses and PPI network analysis. Ten hub genes of the PPI network were identified: AURKA, TP53, CDK1, CDK2, CCNB1, PLK1, CUL1, ESR1, CDC20, and PIK3CA. Those hub genes, as well as their correlative pathways, may be of diagnostic or therapeutic potential for ENKL, but further clinical evidence is still expected.

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Yucong Shi ◽  
Dan Chen ◽  
Shengsuo Ma ◽  
Huachong Xu ◽  
Li Deng

Background. To explore the potential target of depression and the mechanism of related traditional Chinese medicine in the treatment of depression. Method. Differential gene expression in depression patients and controls was analyzed in the GEO database. Key genes for depression were obtained by searching the disease databases. The COREMINE Medical database was used to search for Chinese medicines corresponding to the key genes in the treatment of depression, and the network pharmacological analysis was performed on these Chinese medicines. Then, protein-protein interaction analysis was conducted. Prediction of gene phenotypes was based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment scores. Results. The total number of differentially expressed genes in the GEO database was 147. Combined with the GEO dataset and disease database, a total of 3533 depression-related genes were analyzed. After screening in COREMINE Medical, it was found that the top 4 traditional Chinese medicines with the highest frequency for depression were Paeonia lactiflora Pall., Crocus sativus L., Bupleurum chinense DC., and Cannabis sativa L. The compound target network consisted of 24 compounds and 138 corresponding targets, and the key targets involved PRKACA, NCOA2, PPARA, and so on. GO and KEGG analysis revealed that the most commonly used Chinese medicine could regulate multiple aspects of depression through these targets, related to metabolism, neuroendocrine function, and neuroimmunity. Prediction and analysis of protein-protein interactions resulted in the selection of nine hub genes (ESR1, HSP90AA1, JUN, MAPK1, MAPK14, MAPK8, RB1, RELA, and TP53). In addition, a total of four ingredients (petunidin, isorhamnetin, quercetin, and luteolin) from this Chinese medicine could act on these hub genes. Conclusions. Our research revealed the complicated antidepressant mechanism of the most commonly used Chinese medicines and also provided a rational strategy for revealing the complex composition and function of Chinese herbal formulas.

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