scholarly journals An Integrative Prognostic and Immune Analysis of PTPRD in Pan-Cancer

2021 ◽  
Author(s):  
Chunpei Ou ◽  
Qin Peng ◽  
Changchun Zeng
Keyword(s):  
Protein Interaction ◽  
Protein Interaction Network ◽  
Interaction Network ◽  
Cancer Therapeutics ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Biological Processes ◽  
Immune Infiltration ◽  
The Relationship ◽  
Pan Cancer

Abstract Background: PTPRD plays an indispensable role in the occurrence of multiple tumors. However, pan-cancer analysis is unavailable. The purpose of this research was to investigate the relationship between PTPRD and immunity and describe its prognostic landscape across various tumors. Methods: We explored expression profile, survival analysis, and genomic alterations of PTPRD based on the TIMER, GEPIA, UALCAN, PrognoScan, and cBioPortal database. The frequency of PTPRD mutation and its correlation with response to immunotherapy were evaluated using the cBioPortal database. The relationship between PTPRD and immune-cell infiltration was analyzed by the TIMER and TISIDB databases. A protein interaction network was constructed by the STRING database. GO and KEGG enrichment analysis was executed by the Metascape database.Results: A significant correlation between PTPRD expression and prognosis was found in various cancers. Aberrant PRPRD expression was closely related to immune infiltration. Importantly, the patients who harbored PTPRD mutation and received immune checkpoint inhibitors had worse overall survival, especially in non-small cell lung cancer and melanoma, and had a higher TMB score. Moreover, PTPRD mutation was involved in numerous biological processes, including immunological signaling pathways. Additionally, a PTPRD protein interaction network was constructed, and genes that interacted with PTPRD were identified. Functional enrichment analysis demonstrated that a variety of GO biological processes and KEGG pathways of PTPRD were primarily involved in the therapeutic mechanisms. Conclusions: These results revealed that PRPRD might function as a biomarker for prognosis and immune infiltration in cancers, throwing new light on cancer therapeutics.

scholarly journals Studies on the Mechanism of Gegen Qinlian Decoction in Treating Diabetes Mellitus Based on Network Pharmacology

2021 ◽  
Vol 16 (1) ◽  
pp. 1934578X2098213
Author(s):  
Xiaodong Deng ◽  
Yuhua Liang ◽  
Jianmei Hu ◽  
Yuhui Yang
Keyword(s):  
Diabetes Mellitus ◽  
Molecular Docking ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Network Pharmacology ◽  
Hub Genes ◽  
Topological Parameters

Diabetes mellitus (DM) is a chronic disease that is very common and seriously threatens patient health. Gegen Qinlian decoction (GQD) has long been applied clinically, but its mechanism in pharmacology has not been extensively and systematically studied. A GQD protein interaction network and diabetes protein interaction network were constructed based on the methods of system biology. Functional module analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and Gene Ontology (GO) enrichment analysis were carried out on the 2 networks. The hub nodes were filtered by comparative analysis. The topological parameters, interactions, and biological functions of the 2 networks were analyzed in multiple ways. By applying GEO-based external datasets to verify the results of our analysis that the Gene Set Enrichment Analysis (GSEA) displayed metabolic pathways in which hub genes played roles in regulating different expression states. Molecular docking is used to verify the effective components that can be combined with hub nodes. By comparing the 2 networks, 24 hub targets were filtered. There were 7 complex relationships between the networks. The results showed 4 topological parameters of the 24 selected hub targets that were much higher than the median values, suggesting that these hub targets show specific involvement in the network. The hub genes were verified in the GEO database, and these genes were closely related to the biological processes involved in glucose metabolism. Molecular docking results showed that 5,7,2', 6'-tetrahydroxyflavone, magnograndiolide, gancaonin I, isoglycyrol, gancaonin A, worenine, and glyzaglabrin produced the strongest binding effect with 10 hub nodes. This compound–target mode of interaction may be the main mechanism of action of GQD. This study reflected the synergistic characteristics of multiple targets and multiple pathways of traditional Chinese medicine and discussed the mechanism of GQD in the treatment of DM at the molecular pharmacological level.

scholarly journals Network Pharmacology study of Curcuma longa L.: Potential Target Proteins and their Functional Enrichment Analysis.

2020 ◽  
Author(s):  
SANGEETA KUMARI
Keyword(s):  
Signaling Pathway ◽  
Mechanism Of Action ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Curcuma Longa ◽  
Interaction Network ◽  
Functional Enrichment ◽  
Target Proteins ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Network

Abstract Objective This study’s primary goal is unraveling the mechanism of action of bioactives of Curcuma longa L. at the molecular level using protein-protein interaction network.Results We used target proteins to create protein-protein interaction network (PPIN) and identified significant node and edge attributes of PPIN. We identified the cluster of proteins in the PPIN, which were used to identify enriched pathways. . We identified closeness centrality and jaccard score as most important node and edge attribute of the PPIN respectively. The enriched pathways of various clusters were overlapped suggesting synergistic mechanism of action. The three pathways found to be common among three clusters were Gonadotropin-releasing hormone receptor pathway, Endothelin signaling pathway, and Inflammation mediated by chemokine and cytokine signaling pathway.

scholarly journals Prognostic and immunological value of LTB4R in pan-cancer

2021 ◽  
Vol 18 (6) ◽  
pp. 9336-9356
Author(s):  
Sidan Long ◽  
◽  
Shuangshuang Ji ◽  
Kunmin Xiao ◽  
Peng Xue ◽  
...  
Keyword(s):  
Immune Cells ◽  
Prognostic Significance ◽  
Enrichment Analysis ◽  
Negative Influence ◽  
Leukotriene B4 ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Immune Infiltration ◽  
Significant Difference ◽  
Pan Cancer

<abstract> <sec><title>Background</title><p>LTB4 receptor 1 (LTB4R), as the high affinity leukotriene B4 receptor, is rapidly revealing its function in malignancies. However, it is still uncertain.</p> </sec> <sec><title>Methods</title><p>We investigated the expression pattern and prognostic significance of LTB4R in pan-cancer across different databases, including ONCOMINE, PrognoScan, GEPIA, and Kaplan-Meier Plotter, in this study. Meanwhile, we explored the significance of LTB4R in tumor metastasis by HCMDB. Then functional enrichment analysis of related genes was performed using GeneMANIA and DAVID. Lastly, utilizing the TIMER datasets, we looked into the links between LTB4R expression and immune infiltration in malignancies.</p> </sec> <sec><title>Results</title><p>In general, tumor tissue displayed higher levels of LTB4R expression than normal tissue. Although LTB4R had a negative influence on pan-cancer, a high expression level of LTB4R was protective of LIHC (liver hepatocellular carcinoma) patients' survival. There was no significant difference in the distribution of LTB4R between non-metastatic and metastatic tumors. Based on Gene Set Enrichment Analysis, LTB4R was implicated in pathways involved in inflammation, immunity, metabolism, and cancer diseases. The correlation between immune cells and LTB4R was found to be distinct across cancer types. Furthermore, markers of infiltrating immune cells, such as Treg, T cell exhaustion and T helper cells, exhibited different LTB4R-related immune infiltration patterns.</p> </sec> <sec><title>Conclusion</title><p>The LTB4R is associated with immune infiltrates and can be used as a prognostic biomarker in pan-cancer.</p> </sec> </abstract>

scholarly journals Network Pharmacology and Molecular Docking Suggest the Mechanism for Biological Activity of Rosmarinic Acid

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Minglong Guan ◽  
Lan Guo ◽  
Hengli Ma ◽  
Huimei Wu ◽  
Xiaoyun Fan
Keyword(s):  
Biological Activity ◽  
Molecular Docking ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Rosmarinic Acid ◽  
Target Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis

Rosmarinic acid (RosA) is a natural phenolic acid compound, which is mainly extracted from Labiatae and Arnebia. At present, there is no systematic analysis of its mechanism. Therefore, we used the method of network pharmacology to analyze the mechanism of RosA. In our study, PubChem database was used to search for the chemical formula and the Chemical Abstracts Service (CAS) number of RosA. Then, the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was used to evaluate the pharmacodynamics of RosA, and the Comparative Toxicogenomics Database (CTD) was used to identify the potential target genes of RosA. In addition, the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of target genes were carried out by using the web-based gene set analysis toolkit (WebGestalt). At the same time, we uploaded the targets to the STRING database to obtain the protein interaction network. Then, we carried out a molecular docking about targets and RosA. Finally, we used Cytoscape to establish a visual protein-protein interaction network and drug-target-pathway network and analyze these networks. Our data showed that RosA has good biological activity and drug utilization. There are 55 target genes that have been identified. Then, the bioinformatics analysis and network analysis found that these target genes are closely related to inflammatory response, tumor occurrence and development, and other biological processes. These results demonstrated that RosA can act on a variety of proteins and pathways to form a systematic pharmacological network, which has good value in drug development and utilization.

scholarly journals Microarray analysis of novel genes involved in HSV-2 infection

2021 ◽  
Author(s):  
Hao Zhang ◽  
Tao Liu
Keyword(s):  
Immune System ◽  
Network Analysis ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Experimental Studies ◽  
Interaction Network ◽  
The Body ◽  
Gene Analysis ◽  
Functional Enrichment ◽  
Skin Immune System

Abstract Background: Herpes simplex virus type 2 infects the body and becomes an incurable and recurring disease. The pathogenesis of HSV-2 infection is not completely clear.Methods: We analyze the GSE18527 dataset in the GEO database in this paper to obtain distinctively displayed genes(DDGs)in the total sequential RNA of the biopsies of normal and lesioned skin groups, healed skin and lesioned skin groups of genital herpes patients, respectively.The related data of 3 cases of normal skin group, 4 cases of lesioned group and 6 cases of healed group were analyzed.The histospecific gene analysis , functional enrichment and protein interaction network analysis of the differential genes were also performed, and the critical components were selected.Results: 40 up-regulated genes and 43 down-regulated genes were isolated by differential performance assay.Histospecific gene analysis of DDGs suggested that the most abundant system for gene expression was the skin, immune system and the nervous system.Through the construction of core gene combinations, protein interaction network analysis and selection of histospecific distribution genes, 17 associated genes were selected：CXCL10,MX1,ISG15,IFIT1,IFIT3,IFIT2,OASL,ISG20,RSAD2,GBP1,IFI44L,DDX58,USP18,CXCL11,GBP5,GBP4 and CXCL9.The above genes are mainly located in the skin, immune system, nervous system and reproductive system.Conclusion:This paper elucidates an effective approach for a new mechanism of HSV-2 infection, and the molecular mechanism of the selected core genes in the process of HSV-2 infection requires future experimental studies.

scholarly journals ITGA5 Is a Prognostic Biomarker and Correlated with Immune Infiltration In Gastrointestinal Cancers

2020 ◽  
Author(s):  
Hai Zhu ◽  
Gang Wang ◽  
Haixing Zhu ◽  
Aman Xu
Keyword(s):  
Gastric Cancer ◽  
Immune Cell ◽  
Prognostic Biomarker ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Th2 Cells ◽  
Integrin Subunit ◽  
Expression Levels ◽  
Immune Infiltration

Abstract Background: Integrin Subunit Alpha 5 (ITGA5) belongs to the integrin alpha chain family, is vital for promoting cancer cell invasion, metastasis. However, the correlation between ITGA5 expression and immune infiltration in gastrointestinal (GI) tumors remain unclear.Methods: The expression levels of ITGA5 were detected by Oncomine and Tumor Immune Estimation Resource (TIMER). The association between ITGA5 and prognosis of patients was identified by Kaplan–Meier plotter, Gene Expression Profiling Interactive Analysis 2(GEPIA2) and PrognoScan. We evaluated the correlation between ITGA5 expression and immune infiltrating level via TIMER. Besides, TIMER and immunohistochemistry (IHC) staining were used to explore correlations between ITGA5 expression and markers of immune infiltrates cells. Furthermore, we constructed protein-protein interaction (PPI) network and performed functional enrichment by GeneMANIA and Metascape.Results: ITGA5 was generally overexpressed and correlated with worse prognosis in multiple types of GI tumors. In addition, ITGA5 expression levels was significantly associated with tumor purity and immune infiltration levels of different immune cells in GI tumors. Interestingly, Immune markers for monocytes, tumor - associated macrophages (TAMs), macrophages 2 (M2) cells and T-helper 2 (Th2) cells were found to be significantly and positively correlated with ITGA5 expression levels in colon and gastric cancer. Results from IHC staining further proved that markers of Th2 and M2 cell were significantly increased in gastric cancer patients with high ITGA5 expression levels. Lastly, interaction network and function enrichment analysis revealed ITGA5 were mainly involved in “integrin mediated signaling pathway”, “leukocyte migration”, “cell-substrate adhesion”.Conclutions: our study demonstrated that ITGA5 may act as an essential regulator of tumor immune cell infiltration and a valuable prognostic biomarker in GI tumors. Additional work is needed to fully elucidate the underlying mechanisms behind these observations.

scholarly journals An Integrative Pan-Cancer Analysis Revealing LCN2 as an Oncogenic Immune Protein in Tumor Microenvironment

2020 ◽  
Vol 10 ◽  
Author(s):  
Wen-Xiu Xu ◽  
Jian Zhang ◽  
Yu-Ting Hua ◽  
Su-Jin Yang ◽  
Dan-Dan Wang ◽  
...  
Keyword(s):  
T Cells ◽  
Cytochrome P450 ◽  
Interaction Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Sterile Inflammation ◽  
Lipocalin 2 ◽  
Immune Infiltration ◽  
Pan Cancer

BackgroundLipocalin 2 (LCN2), an innate immune protein, plays a pivotal role in promoting sterile inflammation by regulating immune responses. However, the role of LCN2 in diverse cancers remains poorly defined. This research aimed to investigate the correlation between LCN2 expression and immunity and visualize its prognostic landscape in pan-cancer.MethodsRaw data in regard to LCN2 expression in cancer patients were acquired from TCGA and GTEx databases. Besides, we investigated the genomic alterations, expression pattern, and survival analysis of LCN2 in pan-cancer across numerous databases, including cBioPortal and GEPIA database. The correlation between LCN2 expression and tumor immune infiltration was explored via TIMER, and we utilized CIBERSORT and ESTIMATE computational methods to assess the proportion of tumor-infiltrating immune cells (TIICs) and the amount of stromal and immune components from TCGA database. Protein–Protein Interaction analysis was performed in GeneMANIA database, and gene functional enrichment was performed by Gene Set Enrichment Analysis (GSEA).ResultsOn balance, tumor tissue had a higher LCN2 expression level compared with that in normal tissue. Elevated expression of LCN2 was related to poor clinical regimen with OS and RFS. There were significant positive correlations between LCN2 expression and TIICs, including CD8+ T cells, CD4+ T cells, B cells, neutrophils, macrophages, and dendritic cells. Moreover, markers of TIICs exhibited different LCN2-related immune infiltration patterns. GSEA analysis showed that the expression of LCN2 was related to retinol metabolism, drug metabolism cytochrome P450 and metabolism of xenobiotics by cytochrome P450.ConclusionsThese findings suggested that LCN2 might serve as a biomarker for immune infiltration and poor prognosis in cancers, shedding new light on therapeutics of cancers.

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