Module-based functional pathway enrichment analysis of a protein-protein interaction network to study the effects of intestinal microbiota depletion in mice

Objective: To analyze the biological functions and its clinical significance of let-7b-5p target gene in cholangiocarcinoma utilizing bioinformatics. Methods: The paper focuses on the let-7b-5p target gene, and predicts its biological functions as well as related signal pathways through GO biological function and KEGG signal pathway enrichment analysis. The STRING database and Cytoscape are used to construct a protein-protein interaction network to screen core genes. Results: The results of GO analysis showed that let-7b-5p target gene was mainly enriched in biological processes such as Small GTPase binding, Rho GTPase binding, and Rac GTPase binding. The results of KEGG analysis showed that let-7b-5p target gene was significantly enriched in key signaling pathways including Focal adhesion and ECM-receptor interaction. Through protein-protein interaction network and module analysis, CXCL8 and SDC2 were screened as the core site. Conclusion: let-7b-5p can participate in the regulation of biological functions of tumor cells in cholangiocarcinoma, suggesting that it may play an important role as a tumor suppressor gene and biomarker in the occurrence and development of cholangiocarcinoma, which provides new ideas for its diagnosis and treatment.

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Network controllability enrichment analysis reveals that SARS-CoV-2 infection tends to target indispensable nodes of a directed human protein-protein interaction network

10.1101/2021.04.18.440358 ◽

2021 ◽

Author(s):

Ho-Joon Lee

Keyword(s):

Protein Interaction ◽

Protein Interaction Network ◽

Interaction Network ◽

Enrichment Analysis ◽

Protein Protein Interaction ◽

Genome Wide ◽

A Genome ◽

Human Proteins ◽

Protein Protein Interaction Network ◽

Network Controllability

The COVID-19 disease has been a global threat caused by the new coronavirus species, SARS-CoV-2, since early 2020 with an urgent need for therapeutic interventions. In order to provide insight into human proteins targeted by SARS-CoV-2, here we study a directed human protein-protein interaction network (dhPPIN) based on our previous work on network controllability of virus targets. We previously showed that human proteins targeted by viruses tend to be those whose removal in a dhPPIN requires more control of the network dynamics, which were classified as indispensable nodes. In this study we introduce a more comprehensive rank-based enrichment analysis of our previous dhPPIN for SARS-CoV-2 infection and show that SARS-CoV-2 also tends to target indispensable nodes in the dhPPIN using multiple proteomics datasets, supporting validity and generality of controllability analysis of viral infection in humans. Also, we find differential controllability among SARS-CoV-2, SARS-CoV-1, and MERS-CoV from a comparative proteomics study. Moreover, we show functional significance of indispensable nodes by analyzing heterogeneous datasets from a genome-wide CRISPR screening study, a time-course phosphoproteomics study, and a genome-wide association study. Specifically, we identify SARS-CoV-2 ORF3A as most frequently interacting with indispensable proteins in the dhPPIN, which are enriched in TGF-beta signaling and tend to be sources nodes and interact with each other. Finally, we built an integrated network model of ORF3A-interacting indispensable proteins with multiple functional supports to provide hypotheses for experimental validation as well as therapeutic opportunities. Therefore, a sub-network of indispensable proteins targeted by SARS-CoV-2 could serve as a prioritized network of drug targets and a basis for further functional and mechanistic studies from a network controllability perspective.

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Network Pharmacology Study of Curcuma Longa: Potential Target Proteins and their Functional Enrichment Analysis.

10.21203/rs.3.rs-31985/v1 ◽

2020 ◽

Author(s):

SANGEETA KUMARI

Keyword(s):

Signaling Pathway ◽

Mechanism Of Action ◽

Protein Interaction ◽

Protein Interaction Network ◽

Curcuma Longa ◽

Interaction Network ◽

Enrichment Analysis ◽

Protein Protein Interaction ◽

Function Module ◽

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 (PPI) and identified significant node and edge attributes of PPI. To find the function module, we identified the cluster of proteins which were further queried to GO enrichment analysis. Closeness centrality and jaccard score identified as most important node and edge attribute of the protein-protein interaction network respectively. The mapped pathways of various function module of the network were overlapped and showed synergistic mechanism of action. Three most important identified pathways were Gonadotropin-releasing hormone receptor pathway, Endothelin signaling pathway, and Inflammation mediated by chemokine and cytokine signaling pathway.

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Exploring The Molecular Mechanisms of Classical Hodgkin Lymphoma Through Bioinformatics Analysis

10.21203/rs.3.rs-586729/v1 ◽

2021 ◽

Author(s):

Zhu Lili ◽

Zhu YuKun ◽

Zhuangzhuang Tian ◽

Yongsheng Li ◽

Liyu Cao

Keyword(s):

Hodgkin Lymphoma ◽

Protein Interaction ◽

Protein Interaction Network ◽

Molecular Mechanisms ◽

Kegg Pathway ◽

Interaction Network ◽

Enrichment Analysis ◽

Hub Genes ◽

Protein Protein Interaction ◽

Protein Protein Interaction Network

Abstract Background Classic Hodgkin lymphoma (CHL) is the most common HL in the modern society. Although the treatment of cHL has made great progress, its molecular mechanisms have yet to be deciphered. Objectives The purpose of this study is to find out the crucial potential genes and pathways associated with cHL. Methods We downloaded the cHL microarray dataset (GSE12453) from Gene Expression Omnibus (GEO) database and to identify the differentially expressed genes (DEGs) between cHL samples and normal samples through the limma package in R. Then, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were carried out. Finally, we constructed the protein-protein interaction network to screen out the hub genes using Search Tool for the Retrieval of Interacting Genes (STRING) database. Results We screened out 788 DEGs in the cHL dataset, such as BATF3, IER3, RAB13 and FCRL2. GO functional enrichment analysis indicated that the DEGs were related with regulation of lymphocyte activation, secretory granule lumen and chemokine activity. KEGG pathway analysis showed that the genes enriched in Prion disease, Complement and coagulation cascades and Parkinson disease Coronavirus disease-COVID-19 pathway. Protein-protein interaction network construction identified 10 hub genes (IL6, ITGAM, CD86, FN1, MMP9, CXCL10, CCL5, CD19, IFNG, SELL, UBB) in the network. Conclusions In the present investigation, we identified several pathways and hub genes related to the occurrence and development of cHL, which may provide an important basis for further research and novel therapeutic targets and prognostic indicators for cHL.

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Exploring the sirtuin functionality in aging through the human protein interaction networks

10.7287/peerj.preprints.27671v1 ◽

2019 ◽

Author(s):

Jarmila Nahálková

Keyword(s):

Signaling Pathways ◽

Protein Interaction ◽

Protein Interaction Network ◽

Interaction Network ◽

Enrichment Analysis ◽

Primary Objective ◽

Protein Interaction Data ◽

Pathway Enrichment Analysis ◽

Pathway Enrichment ◽

Age Related

The sirtuin family contains seven proteins with the functions in multiple diseases of aging, which makes them an attractive subject for the development of therapies of age-related diseases and anti-aging treatments. The primary objective of the protein-interaction network analysis presented here is to identify the signaling pathways and protein nodes driving the functions of the sirtuins. For this purpose, the protein-protein interaction data were collected from the available public databases, which fulfilled the quality threshold and included at least one member of the sirtuin family. The databases provided 66 interactions validated by several experiments, which were further processed by the bioinformatic tools connected to the integrated genomic, proteomic, and pharmacologic data. The interactions were analyzed by the pathway enrichment, the gene function prediction analysis, and the protein node prioritization by use of Cytoscape applications GeneMania and Cytohubba. The constructed sirtuin protein interaction network (SPIN) contained after the extension 98 protein nodes. TGFβ, PTK2, CARM1, Notch signaling and the pathways regulating androgen and estrogen levels, significantly scored in the pathway enrichment analysis of SPIN. The enriched signaling pathways mediating the pleiotropic effects of the sirtuin family, play the roles in several age-related diseases probably. The Cytohubba application has highlighted the function of HDAC1, EP300, SMAD4, MYC, SIN3A, RBBP4, HDAC, SIN3B, RBBP7 and SMAD3 as the high priority protein nodes driving the molecular functions of SPIN. The presented protein interaction study provide new understandings of the sirtuin functions in the longevity and diseases of aging including cancer, neurodegenerative and metabolic disorders.

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miR-194 as predictive biomarker of responsiveness to neoadjuvant chemoradiotherapy in patients with locally advanced rectal adenocarcinoma

Journal of Clinical Pathology ◽

10.1136/jclinpath-2017-204690 ◽

2017 ◽

Vol 71 (4) ◽

pp. 344-350 ◽

Cited By ~ 14

Author(s):

Edoardo D’Angelo ◽

Carlo Zanon ◽

Francesca Sensi ◽

Maura Digito ◽

Massimo Rugge ◽

...

Keyword(s):

Locally Advanced ◽

Interaction Network ◽

Enrichment Analysis ◽

Chemical Compounds ◽

Predictive Biomarker ◽

P Value ◽

Pathway Enrichment Analysis ◽

Pathway Enrichment ◽

Protein Protein Interaction ◽

Protein Protein Interaction Network

AimsCurative surgery remains the primary form of treatment for locally advanced rectal cancer (LARC). Recent data support the use of preoperative chemoradiotherapy (pCRT) to improve the prognosis of LARC with a significant reduction of local relapse and an increase of overall survival. Unfortunately, only 20% of the patients with LARC present complete pathological response after pCRT, whereas in 20%–40%, the response is poor or absent.MethodsWe investigated the expression level of miR-194 in n=38 patients with LARC using our public microRNA (miRNA) expression dataset. miR-194 expression was further validated by real-time quantitative PCR (qRT-PCR) and in situ hybridisation (ISH). Protein–protein interaction network and pathway enrichment analysis were performed on miR-194 targets.Results and discussionUsing biopsy samples collected at diagnosis, mir-194 was significantly upregulated in patients responding to treatment (p value=0.016). The data was confirmed with qRT-PCR (p value=0.0587) and ISH (p value=0.026). Protein–protein interaction network and pathway enrichment analysis reveal a possible mechanism of susceptibility to pCRT involving Wnt pathway via its downstream mediator TRAF6. Finally, we interrogated the Comparative Toxicogenomics Database database in order to identify those chemical compounds able to mimic the biological effects of miR-194 as new possible therapeutic option in LARC treatment. The present study combining miRNA expression profiling with integrative computational biology identified miR-194 as predictive biomarker of response to pCRT. Using known and predicted drug mechanism of action, we then identified possible chemical compounds for further in vitro validation.

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pathfindR: An R Package for Pathway Enrichment Analysis Utilizing Active Subnetworks

10.1101/272450 ◽

2018 ◽

Cited By ~ 5

Author(s):

Ege Ulgen ◽

Ozan Ozisik ◽

Osman Ugur Sezerman

Keyword(s):

Interaction Network ◽

Enrichment Analysis ◽

R Package ◽

Pathway Enrichment Analysis ◽

Pathway Enrichment ◽

Protein Protein Interaction ◽

Gene Sets ◽

User Data ◽

Pathway Diagrams ◽

Protein Protein Interaction Network

AbstractSummaryPathfindR is a tool for pathway enrichment analysis utilizing active subnetworks. It identifies gene sets that form active subnetworks in a protein-protein interaction network using a list of genes provided by the user. It then performs pathway enrichment analyses on the identified gene sets. Further, using the R package pathview, it maps the user data on the enriched pathways and renders pathway diagrams with the mapped genes. Because many of the enriched pathways are usually biologically related, pathfindR also offers functionality to cluster these pathways and identify representative pathways in the clusters. PathfindR is built as a stand-alone package but it can easily be integrated with other tools, such as differential expression/methylation analysis tools, for building fully automated pipelines. In this article, an overview of pathfindR is provided and an example application on a rheumatoid arthritis dataset is presented and discussed.AvailabilityThe package is freely available under MIT license at: https://github.com/egeulgen/pathfindR

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Identification of Potential Biomarkers in Hepatocellular Carcinoma: A Network-Based Approach

10.21203/rs.3.rs-91501/v1 ◽

2020 ◽

Author(s):

Mehrdad Ameri ◽

Haniye Salimi ◽

Sedigheh Eskandari ◽

Navid Nezafat

Keyword(s):

Hepatocellular Carcinoma ◽

Protein Interaction ◽

Microarray Data ◽

Protein Interaction Network ◽

Interaction Network ◽

Enrichment Analysis ◽

Hub Genes ◽

Protein Protein Interaction ◽

Protein Protein Interaction Network ◽

Potential Biomarkers

Abstract Background: Hepatocellular carcinoma (HCC) is one of the leading causes of death worldwide. Identification of potential therapeutic and diagnostic biomarkers can be helpful to screen cancer progress. This study implemented with the aim of discovering potential biomarkers for HCC within a network-based approach integrated with microarray data. Methods: Through downloading a gene expression profile GSE62232 differentially expressed genes (DEGs) were identified. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis for DEGs were performed utilizing enrichr server. Following reconstruction of protein-protein interaction network of DEGs with STRING, network visualization, analyses, and clustering into structural modules carried out using Cytoscape. Considering degree centrality, 15 hub genes were selected as early biomarker candidates for final validation. In order to validate hub genes, GEPIA server was used to perform overall survival (OS) and disease-free survival (DFS). Results: In our approach 1996 DEGs were identified including 995 up-regulated genes and 1001 down-regulated genes. KEGG pathway enrichment analysis shown that DEGs are associated with Chemical carcinogenesis, and Cell cycle. GO term enrichment analysis indicated the relation of DEGs with epoxygenase P450 pathway, arachidonic acid monooxygenase activity, and secretory granule lumen. Following analysis of protein-protein interaction network of DEGs top three structural modules and 15 early hub genes were selected. Validation of hub genes performed using GEPIA. Consequently, CDK1, CCNB1, CCNA2, CDC20, AURKA, MAD2L1, TOP2A, KIF11, BUB1B, TYMS, EZH2, and BUB1 were considered as our final proposed biomarkers. Conclusion: using an integrated network-based approach with microarray data our results revealed 12 final candidates with potential to considered as biomarkers in hepatocellular carcinoma.

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Exploring the sirtuin functionality in aging through the human protein interaction networks

10.7287/peerj.preprints.27671 ◽

2019 ◽

Author(s):

Jarmila Nahálková

Keyword(s):

Signaling Pathways ◽

Protein Interaction ◽

Protein Interaction Network ◽

Interaction Network ◽

Enrichment Analysis ◽

Primary Objective ◽

Protein Interaction Data ◽

Pathway Enrichment Analysis ◽

Pathway Enrichment ◽

Age Related

The sirtuin family contains seven proteins with the functions in multiple diseases of aging, which makes them an attractive subject for the development of therapies of age-related diseases and anti-aging treatments. The primary objective of the protein-interaction network analysis presented here is to identify the signaling pathways and protein nodes driving the functions of the sirtuins. For this purpose, the protein-protein interaction data were collected from the available public databases, which fulfilled the quality threshold and included at least one member of the sirtuin family. The databases provided 66 interactions validated by several experiments, which were further processed by the bioinformatic tools connected to the integrated genomic, proteomic, and pharmacologic data. The interactions were analyzed by the pathway enrichment, the gene function prediction analysis, and the protein node prioritization by use of Cytoscape applications GeneMania and Cytohubba. The constructed sirtuin protein interaction network (SPIN) contained after the extension 98 protein nodes. TGFβ, PTK2, CARM1, Notch signaling and the pathways regulating androgen and estrogen levels, significantly scored in the pathway enrichment analysis of SPIN. The enriched signaling pathways mediating the pleiotropic effects of the sirtuin family, play the roles in several age-related diseases probably. The Cytohubba application has highlighted the function of HDAC1, EP300, SMAD4, MYC, SIN3A, RBBP4, HDAC, SIN3B, RBBP7 and SMAD3 as the high priority protein nodes driving the molecular functions of SPIN. The presented protein interaction study provide new understandings of the sirtuin functions in the longevity and diseases of aging including cancer, neurodegenerative and metabolic disorders.

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