Validation of the Functions and Prognostic Values of Synapse Associated Proteins in Lower-grade Glioma

Synapse and synapse associated proteins (SAPs) play critical roles in various neurodegeneration diseases and brain tumors. However, in lower-grade gliomas (LGG), SAPs have not been explored systematically. Herein, we are going to explore SAPs expression profile and its clinicopathological significance in LGG which can offer new insights to glioma therapy. In this study, we integrate a list of SAPs that covered 231 proteins with synaptogenesis activity and post synapse formation. The LGG RNA-seq data were downloaded from GEO, TCGA and CGGA database. The prognosis associated SAPs in key modules of PPI (protein-protein interaction networks) was regarded as hub SAPs. Western blot, quantitative reverse transcription PCR (qRT-PCR) and immunochemistry results from HPA database were used to verify the expression of hub SAPs. There were 68 upregulated SAPs and 44 downregulated SAPs in LGG tissue compared with normal brain tissue. Data from function enrichment analysis revealed functions of differentially expressed SAPs in synapse organization and glutamatergic receptor pathway in LGGs. Survival analysis revealed that four SAPs, GRIK2, GABRD, GRID2 and ARC were correlate with the prognosis of LGG patients. Interestingly, we found that GABRD were upregulated in LGG patients with seizures, indicating that SAPs may link to the pathogenesis of seizures in glioma patients. The four-SAPs signature was revealed as an independent prognostic factor in gliomas. Our study presented a novel strategy to assess the prognostic risks of LGGs, based on the expression of SAPs.

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Validation of the Functions and Prognostic Values of Synapse Associated Proteins in Lower-Grade Glioma

10.21203/rs.3.rs-80139/v1 ◽

2020 ◽

Author(s):

Han Lin ◽

Yong Yang ◽

Chongxian Hou ◽

Jiantao Zheng ◽

Guangzhao Lv ◽

...

Keyword(s):

Survival Analysis ◽

Prognostic Significance ◽

Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Differentially Expressed ◽

Prognostic Models ◽

Normal Brain ◽

Lower Grade ◽

Associated Proteins ◽

Genome Atlas

Abstract BackgroundSynapse and synapse associated proteins (SAPs) play critical roles in various neurodegeneration diseases and brain tumors. However, in lower-grade gliomas (LGG), SAPs have not been explored systematically. Herein, we are going to explore SAPs expression profile and its clinicopathological significance in LGG which can offer new insights to glioma therapy. MethodIn this study, we used five sources including, Venkatesh, Shen, Colón, Jüttner R, Gene Ontology (GO) project to integrate a list of SAPs that covered 231 proteins with synaptogenesis activity and post synapse formation. The LGG RNA-seq data were downloaded from gene expression omnibus (GEO) database, The Cancer Genome Atlas (TCGA), and Chinese Glioma Genome Atlas (CGGA). The differentially expressed SAPs were filtered out and constructed PPI to search for key modules and SAPs. Then, using Kaplan–Meier survival analysis, least absolute shrinkage and selection operator (LASSO), and multicox regression analysis, the prognostic significance of these key SAPs was evaluated. CGGA database, Human Protein Altas (HPA) and quantitative real-time PCR were used to verify our findings. ResultData from function enrichment analysis revealed functions of differentially expressed SAPs in synapse organization and glutamatergic receptor pathway in LGGs. Survival analysis revealed four SAPs, GRIK2, GABRD, GRID2, ARC that were correlate with the prognosis of LGG patients and used to construct the prognostic models. Among them, the expression of GABRD was lower in glioma tissue than normal brain tissue, but higher in seizure LGG patients than non-seizure patients. The four-SAPs signature was revealed as an independent prognostic factor in gliomas. ConclusionOur study presented a novel strategy to assess the prognostic risks of LGGs, based on the expression of SAPs. Also, we revealed that several SAPs upregulated in patients with seizures, indicating that they are linked to the pathogenesis of seizures in glioma patients.

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Validation of the Functions and Prognostic Values of Synapse Associated Proteins in Lower-Grade Glioma

10.21203/rs.3.rs-80139/v2 ◽

2020 ◽

Author(s):

Han Lin ◽

Yong Yang ◽

Chongxian Hou ◽

Jiantao Zheng ◽

Guangzhao Lv ◽

...

Keyword(s):

Survival Analysis ◽

Prognostic Significance ◽

Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Differentially Expressed ◽

Prognostic Models ◽

Normal Brain ◽

Lower Grade ◽

Associated Proteins ◽

Genome Atlas

Abstract Background: Synapse and synapse associated proteins (SAPs) play critical roles in various neurodegeneration diseases and brain tumors. However, in lower-grade gliomas (LGG), SAPs have not been explored systematically. Herein, we are going to explore SAPs expression profile and its clinicopathological significance in LGG which can offer new insights to glioma therapy. Method: In this study, we used five sources including, Venkatesh, Shen, Colón, Jüttner R, Gene Ontology (GO) project to integrate a list of SAPs that covered 231 proteins with synaptogenesis activity and post synapse formation. The LGG RNA-seq data were downloaded from gene expression omnibus (GEO) database, The Cancer Genome Atlas (TCGA), and Chinese Glioma Genome Atlas (CGGA). The differentially expressed SAPs were filtered out and constructed PPI to search for key modules and SAPs. Then, using Kaplan–Meier survival analysis, least absolute shrinkage and selection operator (LASSO), and multicox regression analysis, the prognostic significance of these key SAPs was evaluated. CGGA database, Human Protein Altas (HPA) and quantitative real-time PCR were used to verify our findings. Result: Data from function enrichment analysis revealed functions of differentially expressed SAPs in synapse organization and glutamatergic receptor pathway in LGGs. Survival analysis revealed four SAPs, GRIK2, GABRD, GRID2, ARC that were correlate with the prognosis of LGG patients and used to construct the prognostic models. Among them, the expression of GABRD was lower in glioma tissue than normal brain tissue, but higher in seizure LGG patients than non-seizure patients. The four-SAPs signature was revealed as an independent prognostic factor in gliomas.Conclusion: Our study presented a novel strategy to assess the prognostic risks of LGGs, based on the expression of SAPs. Also, we revealed that several SAPs upregulated in patients with seizures, indicating that they are linked to the pathogenesis of seizures in glioma patients.

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Integrative COVID-19 Biological Network Inference with Probabilistic Core Decomposition

10.1101/2021.06.23.449535 ◽

2021 ◽

Author(s):

Yang Guo ◽

Fatemeh Esfahani ◽

Xiaojian Shao ◽

Venkatesh Srinivasan ◽

Alex Thomo ◽

...

Keyword(s):

Protein Interactions ◽

Network Inference ◽

Drug Repurposing ◽

Enrichment Analysis ◽

Human Protein ◽

Ppi Network ◽

Network Nodes ◽

Protein Protein Interaction ◽

Function Enrichment Analysis ◽

Encoding Genes

The SARS-CoV-2 coronavirus is responsible for millions of deaths around the world. To help contribute to the understanding of crucial knowledge and to further generate new hypotheses relevant to SARS-CoV-2 and human protein interactions, we make use of the information abundant Biomine probabilistic database and extend the experimentally identified SARS-CoV-2-human protein-protein interaction (PPI) network in silico. We generate an extended network by integrating information from the Biomine database and the PPI network. To generate novel hypotheses, we focus on the high-connectivity sub-communities that overlap most with the PPI network in the extended network. Therefore, we propose a new data analysis pipeline that can efficiently compute core decomposition on the extended network and identify dense subgraphs. We then evaluate the identified dense subgraph and the generated hypotheses in three contexts: literature validation for uncovered virus targeting genes and proteins, gene function enrichment analysis on subgraphs, and literature support on drug repurposing for identified tissues and diseases related to COVID-19. The majority types of the generated hypotheses are proteins with their encoding genes and we rank them by sorting their connections to known PPI network nodes. In addition, we compile a comprehensive list of novel genes, and proteins potentially related to COVID-19, as well as novel diseases which might be comorbidities. Together with the generated hypotheses, our results provide novel knowledge relevant to COVID-19 for further validation.

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A Network-Based Approach to Explore the Mechanisms of Uncaria Alkaloids in Treating Hypertension and Alleviating Alzheimer’s Disease

International Journal of Molecular Sciences ◽

10.3390/ijms21051766 ◽

2020 ◽

Vol 21 (5) ◽

pp. 1766 ◽

Cited By ~ 4

Author(s):

Wenyong Wu ◽

Zijia Zhang ◽

Feifei Li ◽

Yanping Deng ◽

Min Lei ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Drug Targets ◽

Biological Activities ◽

Target Prediction ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Protein Protein Interaction ◽

Novel Strategy ◽

Underlying Mechanisms

Uncaria alkaloids are the major bioactive chemicals found in the Uncaria genus, which have a long history of clinical application in treating cardiovascular and mental diseases in traditional Chinese medicine (TCM). However, there are gaps in understanding the multiple targets, pathways, and biological activities of Uncaria alkaloids. By constructing the interactions among drug-targets-diseases, network pharmacology provides a systemic methodology and a novel perspective to present the intricate connections among drugs, potential targets, and related pathways. It is a valuable tool for studying TCM drugs with multiple indications, and how these multi-indication drugs are affected by complex interactions in the biological system. To better understand the mechanisms and targets of Uncaria alkaloids, we built an integrated analytical platform based on network pharmacology, including target prediction, protein–protein interaction (PPI) network, topology analysis, gene enrichment analysis, and molecular docking. Using this platform, we revealed the underlying mechanisms of Uncaria alkaloids’ anti-hypertensive effects and explored the possible application of Uncaria alkaloids in preventing Alzheimer’s disease. These results were further evaluated and refined using biological experiments. Our study provides a novel strategy for understanding the holistic pharmacology of TCM, as well as for exploring the multi-indication properties of TCM beyond its traditional applications.

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Identification of tumor antigens and immune subtypes in lower grade gliomas for mRNA vaccine development

Journal of Translational Medicine ◽

10.1186/s12967-021-03014-x ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Liguo Ye ◽

Long Wang ◽

Ji’an Yang ◽

Ping Hu ◽

Chunyu Zhang ◽

...

Keyword(s):

Tumor Antigens ◽

Vaccine Development ◽

Enrichment Analysis ◽

Normal Brain ◽

Lower Grade ◽

Tumor Vaccines ◽

Cancer Vaccination ◽

Differential Expression Gene ◽

Mutation Burden ◽

Immune Related Genes

Abstract Background As an important part of tumor immunotherapy for adjunct, therapeutic tumor vaccines have been effective against multiple solid cancers, while their efficacy against lower grade glioma (LGG) remains undefined. Immunophenotyping of tumors is an essential tool to evaluate the immune function of patients with immunodeficiency or autoimmunity. Therefore, this study aims to find the potential tumor antigen of LGG and identify the suitable population for cancer vaccination based on the immune landscape. Method The genomic and clinical data of 529 patients with LGG were obtained from TCGA, the mRNA_seq data of normal brain tissue were downloaded from GTEx. Differential expression gene and mutation analysis were performed to screen out potential antigens, K-M curves were carried out to investigate the correlation between the level of potential antigens and OS and DFS of patients. TIMER dataset was used to explore the correlation between genes and immune infiltrating cells. Immunophenotyping of 529 tumor samples was based on the single-sample gene sets enrichment analysis. Cibersort and Estimate algorithm were used to explore the tumor immune microenvironment characteristics in each immune subtype. Weighted gene co-expression network analysis (WGCNA) clustered immune-related genes and screened the hub genes, and pathway enrichment analyses were performed on the hub modules related to immune subtype in the WGCNA. Results Selecting for the mutated, up-regulated, prognosis- and immune-related genes, four potential tumor antigens were identified in LGG. They were also significantly positively associated with the antigen-presenting immune cells (APCs). Three robust immune subtypes, IS1, IS2 and IS3, represented immune status "desert", "immune inhibition", and "inflamed" respectively, which might serve as a predictive parameter. Subsequently, clinicopathological features, including the codeletion status of 1p19q, IDH mutation status, tumor mutation burden, tumor stemness, etc., were significantly different among subtypes. Conclusion FCGBP, FLNC, TLR7, and CSF2RA were potential antigens for developing cancer vaccination, and the patients in IS3 were considered the most suitable for vaccination in LGG.

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Bioinformatics Analysis Reveals Functions of MicroRNAs in Rice Under the Drought Stress

Current Bioinformatics ◽

10.2174/1574893615666200207092410 ◽

2021 ◽

Vol 15 (8) ◽

pp. 927-936 ◽

Cited By ~ 3

Author(s):

Yan Peng ◽

Yuewu Liu ◽

Xinbo Chen

Keyword(s):

Drought Stress ◽

Target Genes ◽

Hot Spot ◽

Interaction Network ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Protein Protein Interaction ◽

Promising Tool ◽

Differentially Expressed Mirnas ◽

Aba Biosynthesis

Background: Drought is one of the most damaging and widespread abiotic stresses that can severely limit the rice production. MicroRNAs (miRNAs) act as a promising tool for improving the drought tolerance of rice and have become a hot spot in recent years. Objective: In order to further extend the understanding of miRNAs, the functions of miRNAs in rice under drought stress are analyzed by bioinformatics. Method: In this study, we integrated miRNAs and genes transcriptome data of rice under the drought stress. Some bioinformatics methods were used to reveal the functions of miRNAs in rice under drought stress. These methods included target genes identification, differentially expressed miRNAs screening, enrichment analysis of DEGs, network constructions for miRNA-target and target-target proteins interaction. Results: (1) A total of 229 miRNAs with differential expression in rice under the drought stress, corresponding to 73 rice miRNAs families, were identiﬁed. (2) 1035 differentially expressed genes (DEGs) were identified, which included 357 up-regulated genes, 542 down-regulated genes and 136 up/down-regulated genes. (3) The network of regulatory relationships between 73 rice miRNAs families and 1035 DEGs was constructed. (4) 25 UP_KEYWORDS terms of DEGs, 125 GO terms and 7 pathways were obtained. (5) The protein-protein interaction network of 1035 DEGs was constructed. Conclusion: (1) MiRNA-regulated targets in rice might mainly involve in a series of basic biological processes and pathways under drought conditions. (2) MiRNAs in rice might play critical roles in Lignin degradation and ABA biosynthesis. (3) MiRNAs in rice might play an important role in drought signal perceiving and transduction.

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ADAMTS12 acts as a tumor microenvironment related cancer promoter in gastric cancer

Scientific Reports ◽

10.1038/s41598-021-90330-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Yangming Hou ◽

Yingjuan Xu ◽

Dequan Wu

Keyword(s):

Gastric Cancer ◽

Tumor Microenvironment ◽

Immune Cell ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Tumor Promoter ◽

Protein Protein Interaction ◽

Oxidative Phosphorylation Pathway ◽

Cox Proportional Hazard Regression

AbstractThe infiltration degree of immune and stromal cells has been shown clinically significant in tumor microenvironment (TME). However, the utility of stromal and immune components in Gastric cancer (GC) has not been investigated in detail. In the present study, ESTIMATE and CIBERSORT algorithms were applied to calculate the immune/stromal scores and the proportion of tumor-infiltrating immune cell (TIC) in GC cohort, including 415 cases from The Cancer Genome Atlas (TCGA) database. The differentially expressed genes (DEGs) were screened by Cox proportional hazard regression analysis and protein–protein interaction (PPI) network construction. Then ADAMTS12 was regarded as one of the most predictive factors. Further analysis showed that ADAMTS12 expression was significantly higher in tumor samples and correlated with poor prognosis. Gene Set Enrichment Analysis (GSEA) indicated that in high ADAMTS12 expression group gene sets were mainly enriched in cancer and immune-related activities. In the low ADAMTS12 expression group, the genes were enriched in the oxidative phosphorylation pathway. CIBERSORT analysis for the proportion of TICs revealed that ADAMTS12 expression was positively correlated with Macrophages M0/M1/M2 and negatively correlated with T cells follicular helper. Therefore, ADAMTS12 might be a tumor promoter and responsible for TME status and tumor energy metabolic conversion.

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Screen Key Genes Associated with Distraction-Induced Osteogenesis of Stem Cells Using Bioinformatics Methods

International Journal of Molecular Sciences ◽

10.3390/ijms22126505 ◽

2021 ◽

Vol 22 (12) ◽

pp. 6505

Author(s):

Jishizhan Chen ◽

Jia Hua ◽

Wenhui Song

Keyword(s):

Stem Cells ◽

Molecular Mechanisms ◽

Enrichment Analysis ◽

Negative Control ◽

Gene Set Enrichment Analysis ◽

Venn Diagram ◽

Hub Genes ◽

Protein Protein Interaction ◽

Two Samples ◽

Key Genes

Applying mesenchymal stem cells (MSCs), together with the distraction osteogenesis (DO) process, displayed enhanced bone quality and shorter treatment periods. The DO guides the differentiation of MSCs by providing mechanical clues. However, the underlying key genes and pathways are largely unknown. The aim of this study was to screen and identify hub genes involved in distraction-induced osteogenesis of MSCs and potential molecular mechanisms. Material and Methods: The datasets were downloaded from the ArrayExpress database. Three samples of negative control and two samples subjected to 5% cyclic sinusoidal distraction at 0.25 Hz for 6 h were selected for screening differentially expressed genes (DEGs) and then analysed via bioinformatics methods. The Gene Ontology (GO) terms and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment were investigated. The protein–protein interaction (PPI) network was visualised through the Cytoscape software. Gene set enrichment analysis (GSEA) was conducted to verify the enrichment of a self-defined osteogenic gene sets collection and identify osteogenic hub genes. Results: Three hub genes (IL6, MMP2, and EP300) that were highly associated with distraction-induced osteogenesis of MSCs were identified via the Venn diagram. These hub genes could provide a new understanding of distraction-induced osteogenic differentiation of MSCs and serve as potential gene targets for optimising DO via targeted therapies.

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Cyclin B1 acts as a tumor microenvironment-related cancer promoter and prognostic biomarker in hepatocellular carcinoma

Journal of International Medical Research ◽

10.1177/03000605211016265 ◽

2021 ◽

Vol 49 (5) ◽

pp. 030006052110162

Author(s):

Yangming Hou ◽

Xin Wang ◽

Junwei Wang ◽

Xuemei Sun ◽

Xinbo Liu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Tumor Microenvironment ◽

Proportional Hazards ◽

Enrichment Analysis ◽

Gene Signature ◽

Cyclin B1 ◽

Cox Proportional Hazards ◽

Gene Set Enrichment Analysis ◽

Tumor Promoter ◽

Protein Protein Interaction

Objectives The present study aimed to develop a gene signature based on the ESTIMATE algorithm in hepatocellular carcinoma (HCC) and explore possible cancer promoters. Methods The ESTIMATE and CIBERSORT algorithms were applied to calculate the immune/stromal scores and the proportion of tumor-infiltrating immune cells (TICs) in a cohort of HCC patients. The differentially expressed genes (DEGs) were screened by Cox proportional hazards regression analysis and protein–protein interaction (PPI) network construction. Cyclin B1 (CCNB1) function was verified using experiments. Results The stromal and immune scores were associated with clinicopathological factors and recurrence-free survival (RFS) in HCC patients. In total, 546 DEGs were up-regulated in low score groups, 127 of which were associated with RFS. CCNB1 was regarded as the most predictive factor closely related to prognosis of HCC and could be a cancer promoter. Gene Set Enrichment Analysis (GSEA) and CIBERSORT analyses indicated that CCNB1 levels influenced HCC tumor microenvironment (TME) immune activity. Conclusions The ESTIMATE signature can be used as a prognosis tool in HCC. CCNB1 is a tumor promoter and contributes to TME status conversion.

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Decoding the molecular mechanism of parthenocarpy in Musa spp. through protein–protein interaction network

Scientific Reports ◽

10.1038/s41598-021-93661-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Suthanthiram Backiyarani ◽

Rajendran Sasikala ◽

Simeon Sharmiladevi ◽

Subbaraya Uma

Keyword(s):

Candidate Genes ◽

Protein Interaction ◽

Target Genes ◽

Interaction Network ◽

Enrichment Analysis ◽

Auxin Signaling ◽

Pathway Enrichment Analysis ◽

Ppi Network ◽

Protein Protein Interaction ◽

The Difference

AbstractBanana, one of the most important staple fruit among global consumers is highly sterile owing to natural parthenocarpy. Identification of genetic factors responsible for parthenocarpy would facilitate the conventional breeders to improve the seeded accessions. We have constructed Protein–protein interaction (PPI) network through mining differentially expressed genes and the genes used for transgenic studies with respect to parthenocarpy. Based on the topological and pathway enrichment analysis of proteins in PPI network, 12 candidate genes were shortlisted. By further validating these candidate genes in seeded and seedless accession of Musa spp. we put forward MaAGL8, MaMADS16, MaGH3.8, MaMADS29, MaRGA1, MaEXPA1, MaGID1C, MaHK2 and MaBAM1 as possible target genes in the study of natural parthenocarpy. In contrary, expression profile of MaACLB-2 and MaZEP is anticipated to highlight the difference in artificially induced and natural parthenocarpy. By exploring the PPI of validated genes from the network, we postulated a putative pathway that bring insights into the significance of cytokinin mediated CLAVATA(CLV)–WUSHEL(WUS) signaling pathway in addition to gibberellin mediated auxin signaling in parthenocarpy. Our analysis is the first attempt to identify candidate genes and to hypothesize a putative mechanism that bridges the gaps in understanding natural parthenocarpy through PPI network.

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