scholarly journals Identification of biological pathways and genes associated with neurogenic heterotopic ossification by text mining

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8276 ◽  
Author(s):  
Yichong Zhang ◽  
Yuanbo Zhan ◽  
Yuhui Kou ◽  
Xiaofeng Yin ◽  
Yanhua Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Text Mining ◽  
Heterotopic Ossification ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Egf Receptor ◽  
Enrichment Analysis ◽  
Biological Pathways ◽  
Specific Gene ◽  
Cord Injury

Background Neurogenic heterotopic ossification is a disorder of aberrant bone formation affecting one in five patients sustaining a spinal cord injury or traumatic brain injury (SCI-TBI-HO). However, the underlying mechanisms of SCI-TBI-HO have proven difficult to elucidate. The aim of the present study is to identify the most promising candidate genes and biological pathways for SCI-TBI-HO. Methods In this study, we used text mining to generate potential explanations for SCI-TBI-HO. Moreover, we employed several additional datasets, including gene expression profile data, drug data and tissue-specific gene expression data, to explore promising genes that associated with SCI-TBI-HO. Results We identified four SCI-TBI-HO-associated genes, including GDF15, LDLR, CCL2, and CLU. Finally, using enrichment analysis, we identified several pathways, including integrin signaling, insulin pathway, internalization of ErbB1, urokinase-type plasminogen activator and uPAR-mediated signaling, PDGFR-beta signaling pathway, EGF receptor (ErbB1) signaling pathway, and class I PI3K signaling events, which may be associated with SCI-TBI-HO. Conclusions These results enhance our understanding of the molecular mechanisms of SCI-TBI-HO and offer new leads for researchers and innovative therapeutic strategies.

scholarly journals Blood Gene Expression Profile Study Revealed the Activation of Apoptosis and p53 Signaling Pathway May Be the Potential Molecular Mechanisms of Ionizing Radiation Damage and Radiation-Induced Bystander Effects

Dose-Response ◽  
2020 ◽  
Vol 18 (1) ◽  
pp. 155932582091418
Author(s):  
Guangyao He ◽  
Anzhou Tang ◽  
Mao Xie ◽  
Wei Xia ◽  
Pengcheng Zhao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Ionizing Radiation ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
P53 Signaling ◽  
Gene Correlation ◽  
Radiation Induced ◽  
P53 Signaling Pathway

Radiotherapy is an effective treatment for local solid tumors, but the mechanism of damage to human body caused by radiation therapy needs further study. In this study, gene expression profiles of human peripheral blood samples exposed to different doses and rates of ionizing radiation (IR) were used for bioinformatics analysis to investigate the mechanism of IR damage and radiation-induced bystander effect (RIBE). Differentially expressed genes analysis, weighted gene correlation network analysis, functional enrichment analysis, hypergeometric test, gene set enrichment analysis, and gene set variation analysis were applied to analyze the data. Moreover, receiver operating characteristic curve analysis was performed to identify core genes of IR damage. Weighted gene correlation network analysis identified 3 modules associated with IR damage, 2 were positively correlated and 1 was negatively correlated. The analysis showed that the positively correlated modules were significantly involved in apoptosis and p53 signaling pathway, and ESR1, ATM, and MYC were potential transcription factors regulating these modules. Thus, the study suggested that apoptosis and p53 signaling pathway may be the potential molecular mechanisms of IR damage and RIBE, which could be driven by ESR1, ATM, and MYC.

scholarly journals Diagnostic biomarker candidates for pulpitis revealed by bioinformatics analysis of merged microarray gene expression datasets

2020 ◽  
Author(s):  
Ming Chen ◽  
Junkai Zeng ◽  
Yeqing Yang ◽  
Buling Wu
Keyword(s):  
Gene Expression ◽  
Signaling Pathway ◽  
Dental Pulp ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Biological Pathways ◽  
Gene Set Enrichment Analysis ◽  
Diagnostic Biomarker ◽  
Hub Genes ◽  
Geo Database

Abstract Background Pulpitis is known as an inflammatory disease classified by the level of inflammation. The existed traditional methods of evaluating status of dental pulp tissue in clinical practice still have some shortages and limitations. Immediate and accurate diagnosis of pulpitis is essential to the choice of treatment. Through integrating different datasets from Gene Expression Omnibus (GEO) database, we analyzed the merged expression matrix of pulpitis, aiming to identified biological pathways and diagnostic biomarker of pulpitis.Methods By integrating two datasets (GSE77459 and GSE92681) in GEO database using sva and limma packages, differentially expressed genes (DEGs) of pulpitis were identified. Then DEGs were used to analyze biological pathways of dental pulp inflammation with Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and the Gene Set Enrichment Analysis (GSEA). Protein–protein interaction (PPI) networks and modules were constructed to identify hub genes with the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Cytoscape.Results A total of 472 DEGs consisting of 396 upregulated and 76 downregulated genes were found in pulpitis tissue. DEGs in GO analysis were enriched in biological processes about inflammation and in KEGG pathway analysis were cytokine-cytokine receptor interaction, chemokine signaling pathway and NF-κB signaling pathway. GSEA results provided further functional annotations including complement system, IL6/JAK/STAT3 signaling pathway and inflammatory response pathways. According to the degrees of nodes in PPI network, 10 hub genes were obtained and 8 diagnostic biomarker candidates were screened, including PTPRC, CD86, CCL2, IL6, TLR8, MMP9, CXCL8 and ICAM1.

scholarly journals Identification of Ferroptotic Genes in Spinal Cord Injury at Different Time Points: Bioinformatics and Experimental Validation

2021 ◽  
Author(s):  
Yu Kang ◽  
Qiangwei Li ◽  
Rui Zhu ◽  
Shuang Li ◽  
Xin Xu ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Interaction Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Protein Protein Interaction ◽  
Cord Injury ◽  
Key Genes

Abstract Programmed cell death (PCD) is an important pathologic process after spinal cord injury (SCI), and as a newly type of PCD, ferroptosis is also involved in the secondary SCI, however, the underlying molecular mechanisms remain unclear. Integrating animal experiment and bioinformatics, we validated the ferroptotic phenotype in SCI first, and then bioinformatic analyses, including Gene Ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, gene set enrichment analysis and protein-protein interaction analysis were performed to investigate the ferroptotic genes at 1 day, 3 days, 7 days, 14 days and 56 days post-SCI, finally, the ferroptotic genes in SCI were identified and expression of 5 key genes were validated by western blot. The ferroptotic symbols including iron overload, lipid peroxidation, shrunken mitochondria and ROS accumulation were detected in the acute and sub-acute phase of SCI. The outcomes of bioinformatics suggested that mTOR signaling pathway, HIF-1 signaling pathway, VEGF signaling pathway, Protein processing in endoplasmic reticulum were involved in ferroptotic regulation and ATF-3, XBP-1, HO-1, DDIT-3 and CHAC-1 were selected as the ferroptotic key genes in SCI. Besides, response to oxidative stress, amide metabolic process, cation transport and cytokine production were showed as the essential biological process in ferroptosis after SCI. The ferroptotic phenotype following SCI was validated and the ferroptotic genes and signaling pathways were identified. The results contribute to exploring the ferroptotic mechanism underlying secondary SCI and to providing potential target for clinical treatment.

Serial analysis of gene expression (SAGE) during porcine embryo development

2004 ◽  
Vol 16 (2) ◽  
pp. 87 ◽  
Author(s):  
Le Ann Blomberg ◽  
Kurt A. Zuelke
Keyword(s):  
Gene Expression ◽  
Functional Genomics ◽  
Embryo Development ◽  
Molecular Mechanisms ◽  
Physiological Role ◽  
Transgenic Animals ◽  
Specific Gene ◽  
Research Strategies

Functional genomics provides a powerful means for delving into the molecular mechanisms involved in pre-implantation development of porcine embryos. High rates of embryonic mortality (30%), following either natural mating or artificial insemination, emphasise the need to improve the efficiency of reproduction in the pig. The poor success rate of live offspring from in vitro-manipulated pig embryos also hampers efforts to generate transgenic animals for biotechnology applications. Previous analysis of differential gene expression has demonstrated stage-specific gene expression for in vivo-derived embryos and altered gene expression for in vitro-derived embryos. However, the methods used to date examine relatively few genes simultaneously and, thus, provide an incomplete glimpse of the physiological role of these genes during embryogenesis. The present review will focus on two aspects of applying functional genomics research strategies for analysing the expression of genes during elongation of pig embryos between gestational day (D) 11 and D12. First, we compare and contrast current methodologies that are being used for gene discovery and expression analysis during pig embryo development. Second, we establish a paradigm for applying serial analysis of gene expression as a functional genomics tool to obtain preliminary information essential for discovering the physiological mechanisms by which distinct embryonic phenotypes are derived.

scholarly journals Bioinformatic analysis identifies potential biomarkers and therapeutic targets of septic-shock-associated acute kidney injury

Hereditas ◽  
2021 ◽  
Vol 158 (1) ◽  
Author(s):  
Yun Tang ◽  
Xiaobo Yang ◽  
Huaqing Shu ◽  
Yuan Yu ◽  
Shangwen Pan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Septic Shock ◽  
Acute Kidney Injury ◽  
Molecular Mechanisms ◽  
Therapeutic Targets ◽  
Kidney Injury ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Blood Samples ◽  
Potential Biomarkers

Abstract Background Sepsis and septic shock are life-threatening diseases with high mortality rate in intensive care unit (ICU). Acute kidney injury (AKI) is a common complication of sepsis, and its occurrence is a poor prognostic sign to septic patients. We analyzed co-differentially expressed genes (co-DEGs) to explore relationships between septic shock and AKI and reveal potential biomarkers and therapeutic targets of septic-shock-associated AKI (SSAKI). Methods Two gene expression datasets (GSE30718 and GSE57065) were downloaded from the Gene Expression Omnibus (GEO). The GSE57065 dataset included 28 septic shock patients and 25 healthy volunteers and blood samples were collected within 0.5, 24 and 48 h after shock. Specimens of GSE30718 were collected from 26 patients with AKI and 11 control patents. AKI-DEGs and septic-shock-DEGs were identified using the two datasets. Subsequently, Gene Ontology (GO) functional analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) network analysis were performed to elucidate molecular mechanisms of DEGs. We also evaluated co-DEGs and corresponding predicted miRNAs involved in septic shock and AKI. Results We identified 62 DEGs in AKI specimens and 888, 870, and 717 DEGs in septic shock blood samples within 0.5, 24 and 48 h, respectively. The hub genes of EGF and OLFM4 may be involved in AKI and QPCT, CKAP4, PRKCQ, PLAC8, PRC1, BCL9L, ATP11B, KLHL2, LDLRAP1, NDUFAF1, IFIT2, CSF1R, HGF, NRN1, GZMB, and STAT4 may be associated with septic shock. Besides, co-DEGs of VMP1, SLPI, PTX3, TIMP1, OLFM4, LCN2, and S100A9 coupled with corresponding predicted miRNAs, especially miR-29b-3p, miR-152-3p, and miR-223-3p may be regarded as promising targets for the diagnosis and treatment of SSAKI in the future. Conclusions Septic shock and AKI are related and VMP1, SLPI, PTX3, TIMP1, OLFM4, LCN2, and S100A9 genes are significantly associated with novel biomarkers involved in the occurrence and development of SSAKI.

scholarly journals Identifying Main Genes and Pathways by Using Gene Expression Profiling in Primary Immunodeficiency HOIL-1/RBCK1 Disorder Patients

2021 ◽  
Author(s):  
Khyber Shinwari ◽  
Guojun Liu ◽  
Mikhail Bolkov ◽  
Monib Ullah ◽  
Irina Tuzankina
Keyword(s):  
Gene Expression ◽  
Cell Adhesion ◽  
Signaling Pathway ◽  
Focal Adhesion ◽  
Molecular Mechanisms ◽  
Kegg Pathway ◽  
Wnt Signaling Pathway ◽  
Negative Regulation ◽  
Coagulation Cascade ◽  
Bacterial Disease

HOIL-1/RBCK1 deficiency is a new autosomal receiving disorder with dysfunctional cellular responses to pro-inflammatory cytokines, leading to auto-inflammation, pyogenic bacterial disease, and muscle amylopectinosis growth. Our study with integrated bioinformatics studies of the feature genes and the correlative gene functions, investigated the molecular mechanisms of RBCK1 deficiency. GSE31064 dataset expression profile was downloaded from the Omnibus Gene Expression database. Between RBCK1, MYDK88, NEMO deficient fibroblast, and healthy fibroblast specimens, differentially expressed genes (DEGs) were defined. Gene ontology (GO) gene role enrichment analysis and the Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis were performed using the Annotation, Visualization and Integrated Discovery Database (DAVID). The protein-protein interaction (PPI) of these DEGs was visualized using Cytoscape. GO analysis revealed that the “Skeletal system development, Extracellular matrix organization, Positive regulation of cell migration, Negative regulation of canonical Wnt signaling pathway, Cell adhesion, Angiogenesis and Negative regulation of BMP signaling pathway, Serine-type carboxypeptidase activity, Polysaccharide binding, Calcium ion binding, frizzled binding, Neuropilin binding, and cell adhesion molecule binding, extracellular exosome, extracellular space, extracellular region, lysosomal lumen, endoplasmic reticulum lumen, cell surface and focal adhesion to BP, MF, and CC, respectively. The study of the KEGG pathway showed that the complement and coagulation cascade, interactions of the ECM receptor, PI3K-Akt signaling pathway, PPAR signaling pathway, TGF-beta signaling pathway, cancer pathway, viral carcinogenesis and focal adhesion pathway were closely correlated with the incidence of RBCK1 deficiency. Importantly, it has been predicted that TK1, AURKB, CDCA2, UBE2C, KIFC1, CEP55, CDCA3, GINS2, MCM6 and CDC45 are significantly associated with RCBK1 deficiency. Our study offers a record of damaged genes and pathways in RCBK1, which will boost the understanding of RBCK1 deficiency pathogenesis and other inherent immunodeficiency diseases. This research has the potential and can possibly use in the clinic for diagnosis and targeted therapy of HOIL-1/RBCK1 disorder and other inherent immunodeficiencies.

scholarly journals Convergent evolution of venom gland transcriptomes across Metazoa

2021 ◽  
Author(s):  
Giulia Zancolli ◽  
Maarten Reijnders ◽  
Robert Waterhouse ◽  
Marc Robinson-Rechavi
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Venom Gland ◽  
Bioactive Molecules ◽  
Specific Gene ◽  
Animal Kingdom ◽  
Venom Glands

Animals have repeatedly evolved specialized organs and anatomical structures to produce and deliver a cocktail of potent bioactive molecules to subdue prey or predators: venom. This makes it one of the most widespread convergent functions in the animal kingdom. Whether animals have adopted the same genetic toolkit to evolved venom systems is a fascinating question that still eludes us. Here, we performed the first comparative analysis of venom gland transcriptomes from 20 venomous species spanning the main Metazoan lineages, to test whether different animals have independently adopted similar molecular mechanisms to perform the same function. We found a strong convergence in gene expression profiles, with venom glands being more similar to each other than to any other tissue from the same species, and their differences closely mirroring the species phylogeny. Although venom glands secrete some of the fastest evolving molecules (toxins), their gene expression does not evolve faster than evolutionarily older tissues. We found 15 venom gland specific gene modules enriched in endoplasmic reticulum stress and unfolded protein response pathways, indicating that animals have independently adopted stress response mechanisms to cope with mass production of toxins. This, in turns, activates regulatory networks for epithelial development, cell turnover and maintenance which seem composed of both convergent and lineage-specific factors, possibly reflecting the different developmental origins of venom glands. This study represents the first step towards an understanding of the molecular mechanisms underlying the repeated evolution of one of the most successful adaptive traits in the animal kingdom.

Identification of Four Key Biomarkers and Small Molecule Drugs Innasopharyngeal Carcinoma by Weighted Gene Co-expression Network Analysis

2020 ◽  
Author(s):  
Xi Pan ◽  
Jian-Hao Liu
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Small Molecule ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Tumor Stage ◽  
Functional Enrichment ◽  
Hub Genes ◽  
Therapeutic Goals ◽  
Small Molecule Drugs

Abstract Background Nasopharyngeal carcinoma (NPC) is a heterogeneous carcinoma that the underlying molecular mechanisms involved in the tumor initiation, progression, and migration are largely unclear. The purpose of the present study was to identify key biomarkers and small-molecule drugs for NPC screening, diagnosis, and therapy via gene expression profile analysis. Methods Raw microarray data of NPC were retrieved from the Gene Expression Omnibus (GEO) database and analyzed to screen out the potential differentially expressed genes (DEGs). The key modules associated with histology grade and tumor stage was identified by using weighted correlation network analysis (WGCNA). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of genes in the key module were performed to identify potential mechanisms. Candidate hub genes were obtained, which based on the criteria of module membership (MM) and high connectivity. Then we used receiver operating characteristic (ROC) curve to evaluate the diagnostic value of hub genes. The Connectivity map database was further used to screen out small-molecule drugs of hub genes. Results A total of 430 DEGs were identified based on two GEO datasets. The green gene module was considered as key module for the tumor stage of NPC via WGCNA analysis. The results of functional enrichment analysis revealed that genes in the green module were enriched in regulation of cell cycle, p53 signaling pathway, cell part morphogenesis. Furthermore, four DEGs-related hub genes in the green module were considered as the final hub genes. Then ROC revealed that the final four hub genes presented with high areas under the curve, suggesting these hub genes may be diagnostic biomarkers for NPC. Meanwhile, we screened out several small-molecule drugs that have provided potentially therapeutic goals for NPC. Conclusions Our research identified four potential prognostic biomarkers and several candidate small-molecule drugs for NPC, which may contribute to the new insights for NPC therapy.

scholarly journals Diagnostic biomarker candidates for pulpitis revealed by bioinformatics analysis of merged microarray gene expression datasets

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Ming Chen ◽  
Junkai Zeng ◽  
Yeqing Yang ◽  
Buling Wu
Keyword(s):  
Gene Expression ◽  
Dental Pulp ◽  
Bioinformatics Analysis ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Biological Pathways ◽  
Signalling Pathway ◽  
Diagnostic Biomarker ◽  
Hub Genes ◽  
Geo Database

Abstract Background Pulpitis is an inflammatory disease, the grade of which is classified according to the level of inflammation. Traditional methods of evaluating the status of dental pulp tissue in clinical practice have limitations. The rapid and accurate diagnosis of pulpitis is essential for determining the appropriate treatment. By integrating different datasets from the Gene Expression Omnibus (GEO) database, we analysed a merged expression matrix of pulpitis, aiming to identify biological pathways and diagnostic biomarkers of pulpitis. Methods By integrating two datasets (GSE77459 and GSE92681) in the GEO database using the sva and limma packages of R, differentially expressed genes (DEGs) of pulpitis were identified. Then, the DEGs were analysed to identify biological pathways of dental pulp inflammation with Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and Gene Set Enrichment Analysis (GSEA). Protein–protein interaction (PPI) networks and modules were constructed to identify hub genes with the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Cytoscape. Results A total of 470 DEGs comprising 394 upregulated and 76 downregulated genes were found in pulpitis tissue. GO analysis revealed that the DEGs were enriched in biological processes related to inflammation, and the enriched pathways in the KEGG pathway analysis were cytokine-cytokine receptor interaction, chemokine signalling pathway and NF-κB signalling pathway. The GSEA results provided further functional annotations, including complement system, IL6/JAK/STAT3 signalling pathway and inflammatory response pathways. According to the degrees of nodes in the PPI network, 10 hub genes were identified, and 8 diagnostic biomarker candidates were screened: PTPRC, CD86, CCL2, IL6, TLR8, MMP9, CXCL8 and ICAM1. Conclusions With bioinformatics analysis of merged datasets, biomarker candidates of pulpitis were screened and the findings may be as reference to develop a new method of pulpitis diagnosis.

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