Novel Insight Into the Association Between Obesity and Hepatocellular Carcinoma Occurrence and Recurrence: High-Throughput Microarray Data Set Analysis of Differentially Expressed Genes

PURPOSE This study aims to identify potential biomarkers of hepatocellular carcinoma (HCC) occurrence/recurrence and obesity, along with the molecular mechanisms that involve these biomarkers. METHODS Three microarray data sets, namely GSE18897, GSE25097, and GSE36376 (genetic suppressor elements associated with obesity, tumor, and recurrence, respectively), were downloaded from Gene Expression Omnibus database to be investigated for their expression as differentially expressed genes (DEGs) in HCC and obesity. The functional and pathway enrichment analysis of these DEGs were identified by the Database for Annotation Visualization and Integrated Discovery. The protein-protein interaction network analysis was performed with STRING online tool and Cytoscape software. RESULTS One hundred sixty common DEGs were screened. We found that these genes were associated with certain pathways such as metabolic pathways, terpenoid backbone biosynthesis, and adipocytokine signaling pathway. The involvements of 10 genes, including RPS16, RPS7, CCT3, HNRNPA2B1, EIF4G1, PSMC4, NHP2, EGR1, FDPS, and MCM4, were identified in the subnetwork. HNRNPA2B1 and RPS7 in the GSE18897 data set, RPS16, RPS7, CCT3, HNRNPA2B1, PSMC4, NHP2, FDPS, and MCM4 in the GSE25097 data set, and RPS16, RPS7, CCT3, HNRNPA2B1, EIF4G1, PSMC4, NHP2, FDPS, and MCM4 in the GSE36376 data set exhibited positive fold changes. CONCLUSION These DEGs and pathways could be of diagnostic value as potential biomarkers involved in the pathogenesis of HCC, pertaining to both obesity and HCC occurrence/recurrence.

Download Full-text

VIRdb: a comprehensive database for interactive analysis of genes/proteins involved in the pathogenesis of vitiligo

PeerJ ◽

10.7717/peerj.9119 ◽

2020 ◽

Vol 8 ◽

pp. e9119

Author(s):

Priyansh Srivastava ◽

Alakto Choudhury ◽

Mehak Talwar ◽

Sabyasachi Mohanty ◽

Priyanka Narad ◽

...

Keyword(s):

Differentially Expressed Genes ◽

Protein Level ◽

Skin Color ◽

Systems Approach ◽

Basal Layer ◽

Interaction Network ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Gene Interaction Network

Vitiligo is a chronic asymptomatic disorder affecting melanocytes from the basal layer of the epidermis which leads to a patchy loss of skin color. Even though it is one of the neglected disease conditions, people suffering from vitiligo are more prone to psychological disorders. As of now, various studies have been done in order to project auto-immune implications as the root cause. To understand the complexity of vitiligo, we propose the Vitiligo Information Resource (VIRdb) that integrates both the drug-target and systems approach to produce a comprehensive repository entirely devoted to vitiligo, along with curated information at both protein level and gene level along with potential therapeutics leads. These 25,041 natural compounds are curated from Natural Product Activity and Species Source Database. VIRdb is an attempt to accelerate the drug discovery process and laboratory trials for vitiligo through the computationally derived potential drugs. It is an exhaustive resource consisting of 129 differentially expressed genes, which are validated through gene ontology and pathway enrichment analysis. We also report 22 genes through enrichment analysis which are involved in the regulation of epithelial cell differentiation. At the protein level, 40 curated protein target molecules along with their natural hits that are derived through virtual screening. We also demonstrate the utility of the VIRdb by exploring the Protein–Protein Interaction Network and Gene–Gene Interaction Network of the target proteins and differentially expressed genes. For maintaining the quality and standard of the data in the VIRdb, the gold standard in bioinformatics toolkits like Cytoscape, Schrödinger’s GLIDE, along with the server installation of MATLAB, are used for generating results. VIRdb can be accessed through “http://www.vitiligoinfores.com/”.

Download Full-text

Identification and Interaction Analysis of Significant Genes and MicroRNAs in Pterygium

BioMed Research International ◽

10.1155/2019/2767512 ◽

2019 ◽

Vol 2019 ◽

pp. 1-12 ◽

Cited By ~ 2

Author(s):

Siying He ◽

Hui Sun ◽

Yifang Huang ◽

Shiqi Dong ◽

Chen Qiao ◽

...

Keyword(s):

Differentially Expressed Genes ◽

Molecular Mechanisms ◽

Interaction Analysis ◽

Interaction Network ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Gene Expression Omnibus ◽

Functional Enrichment ◽

Differentially Expressed ◽

Differentially Expressed Mirnas

Purpose. MiRNAs have been widely analyzed in the occurrence and development of many diseases, including pterygium. This study aimed to identify the key genes and miRNAs in pterygium and to explore the underlying molecular mechanisms. Methods. MiRNA expression was initially extracted and pooled by published literature. Microarray data about differentially expressed genes was downloaded from Gene Expression Omnibus (GEO) database and analyzed with the R programming language. Functional and pathway enrichment analyses were performed using the database for Annotation, Visualization and Integrated Discovery (DAVID). The protein-protein interaction network was constructed with the STRING database. The associations between chemicals, differentially expressed miRNAs, and differentially expressed genes were predicted using the online resource. All the networks were constructed using Cytoscape. Results. We found that 35 miRNAs and 301 genes were significantly differentially expressed. Functional enrichment analysis showed that upregulated genes were significantly enriched in extracellular matrix (ECM) organization, while downregulated genes were mainly involved in cell death and apoptotic process. Finally, we concluded the chemical-gene affected network, miRNA-mRNA interacted networks, and significant pathway network. Conclusion. We identified lists of differentially expressed miRNAs and genes and their possible interaction in pterygium. The networks indicated that ECM breakdown and EMT might be two major pathophysiological mechanisms and showed the potential significance of PI3K-Akt signalling pathway. MiR-29b-3p and collagen family (COL4A1 and COL3A1) might be new treatment target in pterygium.

Download Full-text

Meta-analysis of gene signatures and key pathways indicates suppression of JNK pathway as a regulator of chemo-resistance in AML

Scientific Reports ◽

10.1038/s41598-021-91864-2 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Parastoo Modarres ◽

Farzaneh Mohamadi Farsani ◽

Amir Abas Nekouie ◽

Sadeq Vallian

Keyword(s):

Differentially Expressed Genes ◽

Molecular Mechanisms ◽

Meta Analysis ◽

Regulatory Gene ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Jnk Pathway ◽

Gene Signatures ◽

Cellular Apoptosis

AbstractThe pathways and robust deregulated gene signatures involved in AML chemo-resistance are not fully understood. Multiple subgroups of AMLs which are under treatment of various regimens seem to have similar regulatory gene(s) or pathway(s) related to their chemo-resistance phenotype. In this study using gene set enrichment approach, deregulated genes and pathways associated with relapse after chemotherapy were investigated in AML samples. Five AML libraries compiled from GEO and ArrayExpress repositories were used to identify significantly differentially expressed genes between chemo-resistance and chemo-sensitive groups. Functional and pathway enrichment analysis of differentially expressed genes was performed to assess molecular mechanisms related to AML chemotherapeutic resistance. A total of 34 genes selected to be differentially expressed in the chemo-resistance compared to the chemo-sensitive group. Among the genes selected, c-Jun, AKT3, ARAP3, GABBR1, PELI2 and SORT1 are involved in neurotrophin, estrogen, cAMP and Toll-like receptor signaling pathways. All these pathways are located upstream and regulate JNK signaling pathway which functions as a key regulator of cellular apoptosis. Our expression data are in favor of suppression of JNK pathway, which could induce pro-apoptotic gene expression as well as down regulation of survival factors, introducing this pathway as a key regulator of drug-resistance development in AML.

Download Full-text

Suppression of JNK Pathway as a Novel Regulator of Chemo-Resistance in AML: A Meta-Analysis of Gene Signatures and Key Pathways

10.21203/rs.3.rs-154119/v1 ◽

2021 ◽

Author(s):

Parastoo Modarres ◽

Farzaneh Mohammadi Farsani ◽

AmirAbas Nekouie ◽

Sadeq Vallian

Keyword(s):

Differentially Expressed Genes ◽

Molecular Mechanisms ◽

Meta Analysis ◽

Regulatory Gene ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Jnk Pathway ◽

Gene Signatures ◽

Cellular Apoptosis

Abstract The pathways and robust deregulated gene signatures involved in AML chemo-resistance are not fully understood. Multiple subgroups of AMLs which are under treatment of various regimens seem to have similar regulatory gene(s) or pathway(s) related to their chemo-resistance phenotype. In this study using gene set enrichment approach, deregulated genes and pathways associated with relapse after chemotherapy were investigated in AML samples. Five AML libraries compiled from GEO and ArrayExpress repositories were used to identify significantly differentially expressed genes between chemo-resistance and chemo-sensitive groups. Functional and pathway enrichment analysis of differentially expressed genes was performed to assess molecular mechanisms related to AML chemotherapeutic resistance. A total of 34 genes were selected to be differentially expressed in chemo-resistance compared to chemo-sensitive group. Among these genes, c-Jun, AKT3, ARAP3, GABBR1, PELI2 and SORT1 are involved in neurotrophin, estrogen, cAMP and Toll-like receptor signaling pathways. All these pathways are located upstream and regulate JNK signaling pathway which functions as a key regulator of cellular apoptosis. Our expression data are in favor of suppression of JNK pathway, which could induce pro-apoptotic gene expression as well as down regulation of survival factors, suggesting this pathway as a novel key regulator of drug-resistance development in AML.

Download Full-text

Differentially expressed genes SNRPC and PRPF38A are potential biomarkers candidates for osteosarcoma

10.21203/rs.3.rs-24106/v1 ◽

2020 ◽

Author(s):

Sheng Chang ◽

Yang Cao

Keyword(s):

Signaling Pathway ◽

Differentially Expressed Genes ◽

Osteogenic Sarcoma ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Ppi Network ◽

Protein Protein Interaction ◽

Potential Biomarkers

Abstract Background: Osteosarcoma (osteogenic sarcoma, OS) is a primary cause of morbidity and mortality and is associated with poor prognosis in the field of orthopedic. Globally, rates of OS are highest among 15 to 25-year-old adolescent. However, the mechanism of gene regulation and signaling pathway is unknown. Material and Methods: GSE9508, including 34 OS samples and 5 non-malignant bone samples, was gained from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were picked out by GEO2R online R soft tool. Furthermore, the protein-protein interaction (PPI) network between the DEGs was molded utilizing STRING online software. Afterward, PPI network of DEGs was constructed. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were carried out on DAVID online tool and visualized via cytoscape software. Subsequently, module analysis of PPI was performed by using MCODE app. What’s more, prognosis-related genes were screened by using online databases including GEPIA, UALCAN and cBioPortal databases. Results: Totally, 671 DEGs were picked out, including 501 up-regulated genes and 170 down-regulated genes. Moreover, 22 hub genes were identified to be significantly expressed in PPI network (16 up-regulated and 6 down-regulated). We found that spliceosome signaling pathway may provide a potential target in OS. Furthermore, on the basis of common crucial pathway, PRPF38A and SNRPC were closely associated with spliceosome. Conclusion: This study showed that SNRPC and PRPF38A are potential biomarkers candidates for osteosarcoma.

Download Full-text

Identification of a Transcription Factor-microRNA-Gene Coregulation Network in Meningioma through a Bioinformatic Analysis

BioMed Research International ◽

10.1155/2020/6353814 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13

Author(s):

Juan Wang ◽

Yan Liang ◽

Hui Yang ◽

Jian-Huang Wu

Keyword(s):

Transcription Factor ◽

Transcription Factors ◽

Differentially Expressed Genes ◽

Mirna Gene ◽

Control Sample ◽

Interaction Network ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Ontology Term

Background. Meningioma is a prevalent type of brain tumor. However, the initiation and progression mechanisms involved in the meningioma are mostly unknown. This study aimed at exploring the potential transcription factors/micro(mi)RNAs/genes and biological pathways associated with meningioma. Methods. mRNA expressions from GSE88720, GSE43290, and GSE54934 datasets, containing data from 83 meningioma samples and eight control samples, along with miRNA expression dataset GSE88721, which had 14 meningioma samples and one control sample, were integrated analyzed. The bioinformatics approaches were used for identifying differentially expressed genes and miRNAs, as well as predicting transcription factor targets related to the differentially expressed genes. The approaches were also used for gene ontology term analysis and biological pathway enrichment analysis, construction, and analysis of protein-protein interaction network, and transcription factor-miRNA-gene coregulation network construction. Results. Fifty-six upregulated and 179 downregulated genes were identified. Thirty transcription factors able to target the differentially expressed genes were predicted and selected based on public databases. One hundred seventeen overlapping genes were identified from the differentially expressed genes and the miRNAs predicted by miRWalk. Furthermore, NF-κB/IL6, PTGS2, MYC/hsa-miR-574-5p, hsa-miR-26b-5p, hsa-miR-335-5p, and hsa-miR-98-5p, which are involved in the transcription factor-miRNA-mRNA coregulation network, were found to be associated with meningioma. Conclusion. The bioinformatics analysis identified several potential molecules and relevant pathways that may represent critical mechanisms involved in the progression and development of meningioma. This work provides new insights into meningioma pathogenesis and treatments.

Download Full-text

Convergent transcriptomic targets of propranolol and primidone identify potential biomarkers for essential tremor

10.1101/2021.09.13.460137 ◽

2021 ◽

Author(s):

Charles-Etienne Castonguay ◽

Cal Liao ◽

Anouar Khayachi ◽

Gabrielle Houle ◽

Jay P Ross ◽

...

Keyword(s):

Essential Tremor ◽

Differentially Expressed Genes ◽

Movement Disorders ◽

Drug Targets ◽

Molecular Mechanisms ◽

Enrichment Analysis ◽

Cell Types ◽

Neuronal Morphology ◽

Differentially Expressed ◽

Pathway Enrichment Analysis

Essential tremor (ET) is one of the most common movement disorders, affecting nearly 5% of individuals over 65 years old. Despite its high heritability, few genetic risk loci for ET have been identified. Recent advances in pharmacogenomics have generated a wealth of data that led to the identification of molecular signatures in response to hundreds of chemical compounds. Among the different forms of data, gene expression has proven to be quite successful for the inference of drug response in cell models. We sought to leverage this approach in the context of ET where many patients are responsive two drugs: propranolol and primidone. Propranolol- and primidone-specific transcriptomic drug targets, as well as convergent gene targets across both drugs, could provide insights into the pathogenesis of ET and identify possible targets of interest for future treatments. In this study, cerebellar DAOY and neural progenitor cells were treated for 5 days with clinical concentrations of propranolol and primidone, after which RNA-sequencing was used to identify differentially expressed genes. The expression of genes previously implicated in genetic and transcriptomic studies of ET and other movement disorders, such as TRAPPC11, were significantly upregulated by propranolol. Pathway enrichment analysis identified multiple terms related to calcium signalling, endosomal sorting, axon guidance, and neuronal morphology. Convergent differentially expressed genes across all treatments and cell types were also found to be significantly more mutationally constrained, implying that they might harbour rare deleterious variants implicated in disease. Furthermore, these genes were enriched within cell types having high expression of ET related genes in both cortical and cerebellar tissues. Altogether, our results highlight potential cellular and molecular mechanisms associated with tremor reduction and identify relevant genetic biomarkers for drug-responsiveness in ET.

Download Full-text

Based on bioinformatics analysis, NF1, BTRC and MAPK14 are the potential biomarkers in the progression of osteoarthritis synovitis

10.21203/rs.3.rs-349764/v1 ◽

2021 ◽

Author(s):

Mingyi Yang ◽

Yani Su ◽

Yao Ma ◽

Yirixiati Aihaiti ◽

Peng Xu

Keyword(s):

Differentially Expressed Genes ◽

Interaction Network ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Gene Expression Omnibus ◽

Functional Enrichment ◽

Differentially Expressed ◽

Hub Genes ◽

Hub Gene ◽

Potential Biomarkers

Abstract Objective: To study the potential biomarkers and related pathways in osteoarthritis (OA) synovial lesions, and to provide theoretical basis and research directions for the pathogenesis and treatment of OA. Methods: Download the microarray data sets GSE12021 and GSE82107 from Gene Expression Omnibus. GEO2R recognizes differentially expressed genes. Perform functional enrichment analysis of differentially expressed genes and construct protein-protein interaction network. Cytoscape performs module analysis and enrichment analysis of top-level modules. Further identify the Hub gene and perform functional enrichment analysis. TargetScan, miRDB and miRWalk three databases predict the target miRNAs of Hub gene and identify key miRNAs. Results: Finally, 10 Hub genes and 17 key miRNAs related to the progression of OA synovitis were identified. NF1, BTRC and MAPK14 may play a vital role in OA synovial disease. Conclusion: The Hub genes and key miRNAs discovered in this study may be potential biomarkers in the development of OA synovitis, and provide research methods and target basis for the pathogenesis and treatment of OA.

Download Full-text

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.

Download Full-text

Investigating the molecular basis for heterophylly in the aquatic plant Potamogeton octandrus (Potamogetonaceae) with comparative transcriptomics

PeerJ ◽

10.7717/peerj.4448 ◽

2018 ◽

Vol 6 ◽

pp. e4448 ◽

Cited By ~ 3

Author(s):

Dingxuan He ◽

Pin Guo ◽

Paul F. Gugger ◽

Youhao Guo ◽

Xing Liu ◽

...

Keyword(s):

Differentially Expressed Genes ◽

High Throughput ◽

Molecular Mechanisms ◽

High Throughput Sequencing ◽

Kegg Pathway ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Pathway Enrichment ◽

Floating Leaves

Many plant species exhibit different leaf morphologies within a single plant, or heterophylly. The molecular mechanisms regulating this phenomenon, however, have remained elusive. In this study, the transcriptomes of submerged and floating leaves of an aquatic heterophyllous plant, Potamogeton octandrus Poir, at different stages of development, were sequenced using high-throughput sequencing (RNA-Seq), in order to aid gene discovery and functional studies of genes involved in heterophylly. A total of 81,103 unigenes were identified in submerged and floating leaves and 6,822 differentially expressed genes (DEGs) were identified by comparing samples at differing time points of development. KEGG pathway enrichment analysis categorized these unigenes into 128 pathways. A total of 24,025 differentially expressed genes were involved in carbon metabolic pathways, biosynthesis of amino acids, ribosomal processes, and plant-pathogen interactions. In particular, KEGG pathway enrichment analysis categorized a total of 70 DEGs into plant hormone signal transduction pathways. The high-throughput transcriptomic results presented here highlight the potential for understanding the molecular mechanisms underlying heterophylly, which is still poorly understood. Further, these data provide a framework to better understand heterophyllous leaf development in P. octandrus via targeted studies utilizing gene cloning and functional analyses.

Download Full-text