scholarly journals Identification of a Potential Autophagy-Associated Therapeutic Target in Osteosarcoma using Bioinformatic Analyses

2021 ◽  
Author(s):  
Haijun Feng ◽  
Liping Wang ◽  
Jie Liu ◽  
Shengbao Wang
Keyword(s):  
Differentially Expressed Genes ◽  
Protein Interactions ◽  
Treatment Resistance ◽  
Mesenchymal Cell ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Validation Dataset ◽  
Primary Malignancy ◽  
Early Stages

Abstract Background: Osteosarcoma, primarily resulting from mesenchymal cell differentiation, is the most common primary malignancy of the bone in children and adolescents. Metastases to other sites, such as the lung, often occur in the early stages and progress rapidly. Autophagy functions as a tumor-suppressing mechanism in the early stages of oncogenesis, however, in later stages, autophagy may promote tumor growth, spread, and increase treatment resistance. Methods: In the present study, we aimed to screen new key autophagy-related biomarkers that may serve as therapeutic targets for osteosarcoma. The expression profile of the GSE42352 dataset, including 103 OS cell lines and 15 MSC lines from Gene Expression Omnibus (GEO), was analyzed to identify the differentially expressed genes. Results: WGCNA was used to construct the gene co-expression network in osteosarcoma, identify co-expression modules for protein interactions (PPI), and screen the key genes. A total of 757 differentially expressed genes were identified by WGCNA analysis including one key autophagy-related module. Conclusions: Further, we performed the PPI analysis for module genes and identified a key gene. We also theoretically and functionally validated its expression using the validation dataset GSE14359, and in vitro experiments, respectively.

scholarly journals CircFAM13B promotes the proliferation of hepatocellular carcinoma by sponging miR-212, upregulating E2F5 expression and activating the P53 pathway

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ying Xie ◽  
Xiaofeng Hang ◽  
Wensheng Xu ◽  
Jing Gu ◽  
Yuanjing Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
In Vivo Studies ◽  
Circular Rnas ◽  
Novel Target ◽  
Underlying Mechanisms

Abstract Background Most of the biological functions of circular RNAs (circRNAs) and the potential underlying mechanisms in hepatocellular carcinoma (HCC) have not yet been discovered. Methods In this study, using circRNA expression data from HCC tumor tissues and adjacent tissues from the Gene Expression Omnibus database, we identified out differentially expressed circRNAs and verified them by qRT-PCT. Functional experiments were performed to evaluate the effects of circFAM13B in HCC in vitro and in vivo. Results We found that circFAM13B was the most significantly differentially expressed circRNA in HCC tissue. Subsequently, in vitro and in vivo studies also demonstrated that circFAM13B promoted the proliferation of HCC. Further studies revealed that circFAM13B, a sponge of miR-212, is involved in the regulation of E2F5 gene expression by competitively binding to miR-212, inhibits the activation of the P53 signalling pathway, and promotes the proliferation of HCC cells. Conclusions Our findings revealed the mechanism underlying the regulatory role played by circFAM13B, miR-212 and E2F5 in HCC. This study provides a new theoretical basis and novel target for the clinical prevention and treatment of HCC.

scholarly journals H2V, a Database for Human Proteins and Genes in Response to SARS-CoV-2, SARS-CoV, and MERS-CoV Infection

2020 ◽  
Author(s):  
Nan Zhou ◽  
Jinku Bao ◽  
Yuping Ning
Keyword(s):  
Differentially Expressed Genes ◽  
Protein Interactions ◽  
Viral Infections ◽  
Antiviral Agents ◽  
Differentially Expressed ◽  
Easy Access ◽  
Differentially Expressed Proteins ◽  
Protein Protein Interactions ◽  
Associated Proteins ◽  
Human Proteins

Abstract The ongoing COVID-19 pandemic in the world is caused by SARS-CoV-2, a new coronavirus firstly discovered in the end of 2019. It has led to more than 10 million confirmed cases and more than 500,000 confirmed deaths across 216 countries by 1 July 2020, according to WHO statistics. SARS-CoV-2, SARS-CoV, and MERS-CoV are alike, killing people, impairing economy, and inflicting long-term impacts on the society. However, no specific drug or vaccine has been approved as a cure for these viruses. The efforts to develop antiviral measures are hampered by insufficient understanding of molecular responses of human to viral infections. In this study, we collected experimentally validated human proteins that interact with SARS-CoV-2 proteins, human proteins whose expression, translation and phosphorylation levels experience significantly changes after SARS-CoV-2 or SARS-CoV infection, human proteins that correlate with COVID-19 severity, and human genes whose expression levels significantly changed upon SARS-CoV-2 or MERS-CoV infection. A database, H2V, was then developed for easy access to these data. Currently H2V includes: 332 human-SARS-CoV-2 protein-protein interactions; 65 differentially expressed proteins, 232 differentially translated proteins, 1298 differentially phosphorylated proteins, 204 severity associated proteins, and 4012 differentially expressed genes responding to SARS-CoV-2 infection; 66 differentially expressed proteins responding to SARS-CoV infection; and 6981 differentially expressed genes responding to MERS-CoV infection. H2V can help to understand the cellular responses associated with SARS-CoV-2, SARS-CoV and MERS-CoV infection. It is expected to speed up the development of antiviral agents and shed light on the preparation for potential coronavirus emergency in the future.Database url: http://www.zhounan.org/h2v

Comprehensive Analysis of Differentially Expressed Genes and Key Pathways in Neuropathic Pain by Spinal Nerve Ligation

2020 ◽  
Author(s):  
Chao Xu ◽  
HuiFang Li ◽  
YunPeng Zhang ◽  
TianYu Liu ◽  
Yi Feng
Keyword(s):  
Functional Analysis ◽  
Neuropathic Pain ◽  
Differentially Expressed Genes ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Spinal Nerve ◽  
Spinal Nerve Ligation ◽  
Differentially Expressed ◽  
Hub Genes ◽  
Long Term Treatment

Abstract Background: Neuropathic pain can cause significant physical and economic burden to people, and there are no effective long-term treatment methods for this condition. We conducted a bioinformatics analysis of microarray data to identify related mechanisms to determine strategies for more effective treatments of neuropathic pain.Methods: GSE24982 and GSE63442 microarray datasets were extracted from the Gene Expression Omnibus (GEO) database to analyze transcriptome differences of neuropathic pain in the dorsal root ganglions caused by spinal nerve ligation. We filtered the differentially expressed genes (DEGs) in the two datasets and Webgestalt was applied to conduct GeneOntology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the shared DEGs. String Database and Cytoscape software were used to construct the Protein-Protein Interaction (PPI) network to determine the hub genes, which were subsequently verified in the GSE30691 dataset. Finally, miRDB and miRWalk Databases were used to predict potential miRNA of the selected DEGs.Results: A total of 182 overlapped DEGs were found between GSE24982 and GSE63442 datasets. The GO functional analysis and KEGG enrichment analysis showed that the selected DEGs were mainly enriched in infection, transmembrane transport of ion channels, and synaptic transmission. Combining the results of PPI analysis and the verification of the GSE30691 dataset, we identified seven hub genes related to neuropathic pain (Atf3, Aif1, Ctss, Gfap, Scg2, Jun, and Vgf). Predicted miRNA targeting each selected hub genes were identified.Conclusion: Seven hub genes related to the pathogenesis of neuropathic pain and potential targeting miRNA were identified, expanding understanding of the mechanism of neuropathic pain and facilitating treatment development.

Extracting Biological Significant Subnetworks from Protein-Protein Interactions Induced by Differentially Expressed Genes of HIV-1 Vpr Variants

2015 ◽  
Vol 4 (4) ◽  
pp. 35-51 ◽  
Author(s):  
Bandana Barman ◽  
Anirban Mukhopadhyay
Keyword(s):  
Differentially Expressed Genes ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Protein Interaction Network ◽  
Interaction Network ◽  
Differentially Expressed ◽  
Wild Type ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Hiv 1

Identification of protein interaction network is very important to find the cell signaling pathway for a particular disease. The authors have found the differentially expressed genes between two sample groups of HIV-1. Samples are wild type HIV-1 Vpr and HIV-1 mutant Vpr. They did statistical t-test and found false discovery rate (FDR) to identify the genes increased in expression (up-regulated) or decreased in expression (down-regulated). In the test, the authors have computed q-values of test to identify minimum FDR which occurs. As a result they found 172 differentially expressed genes between their sample wild type HIV-1 Vpr and HIV-1 mutant Vpr, R80A. They found 68 up-regulated genes and 104 down-regulated genes. From the 172 differentially expressed genes the authors found protein-protein interaction network with string-db and then clustered (subnetworks) the PPI networks with cytoscape3.0. Lastly, the authors studied significance of subnetworks with performing gene ontology and also studied the KEGG pathway of those subnetworks.

scholarly journals Identification of key genes, pathways and potential therapeutic agents for IgA nephropathy using an integrated bioinformatics analysis

2020 ◽  
Vol 21 (2) ◽  
pp. 147032032091963
Author(s):  
Xiaoxue Chen ◽  
Mindan Sun
Keyword(s):  
Differentially Expressed Genes ◽  
Immunoglobulin A ◽  
Therapeutic Targets ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Signal Pathways ◽  
Immunoglobulin A Nephropathy ◽  
Hub Genes ◽  
Limma Package

Purpose: This study aims to identify immunoglobulin-A-nephropathy-related genes based on microarray data and to investigate novel potential gene targets for immunoglobulin-A-nephropathy treatment. Methods: Immunoglobulin-A-nephropathy chip data was obtained from the Gene Expression Omnibus database, which included 10 immunoglobulin-A-nephropathy and 22 normal samples. We used the limma package of R software to screen differentially expressed genes in immunoglobulin-A-nephropathy and normal glomerular compartment tissues. Functional enrichment (including cellular components, molecular functions, biological processes) and signal pathways were performed for the differentially expressed genes. The online analysis database (STRING) was used to construct the protein-protein interaction networks of differentially expressed genes, and Cytoscape software was used to identify the hub genes of the signal pathway. In addition, we used the Connectivity Map database to predict possible drugs for the treatment of immunoglobulin-A-nephropathy. Results: A total of 348 differentially expressed genes were screened including 107 up-regulated and 241 down-regulated genes. Functional analysis showed that up-regulated differentially expressed genes were mainly concentrated on leukocyte migration, and the down-regulated differentially expressed genes were significantly enriched in alpha-amino acid metabolic process. A total of six hub genes were obtained: JUN, C3AR1, FN1, AGT, FOS, and SUCNR1. The small-molecule drugs thapsigargin, ciclopirox and ikarugamycin were predicted therapeutic targets against immunoglobulin-A-nephropathy. Conclusion: Differentially expressed genes and hub genes can contribute to understanding the molecular mechanism of immunoglobulin-A-nephropathy and providing potential therapeutic targets and drugs for the diagnosis and treatment of immunoglobulin-A-nephropathy.

scholarly journals GENE-20. IDENTIFYING POTENTIAL GENES AND MECHANISMS DRIVING IDH-MUTANT GLIOMA PROGRESSION AND RECURRENCE THROUGH RNA-SEQUENCING

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi101-vi102
Author(s):  
Angela Cho ◽  
Amanda Hudson ◽  
Emily Colvin ◽  
Sarah Hayes ◽  
Helen Wheeler ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Treatment Resistance ◽  
Differentially Expressed ◽  
Low Grade ◽  
Sequencing Platform ◽  
Radiotherapy Group ◽  
Treatment Naïve ◽  
Radiotherapy Alone ◽  
Longitudinal Comparison ◽  
Glioma Progression

Abstract Gliomas are the most common primary brain tumors in adults. IDH-mutated low-grade gliomas of astrocytic lineage (astrocytomas) have a relatively indolent clinical course; however, over time they progress to a higher grade. Molecular studies revealed recurrent tumors harbor more mutations upon malignant progression when treated with chemotherapy and/or radiotherapy compared to treatment-naïve tumors. However, genes which promote progression and recurrence in these tumors are unknown. This study aims to identify the transcriptional drivers of progression and recurrence of IDH-mutant gliomas. Longitudinal comparison of transcriptional profiles was performed on 6 matched pairs of primary lesions and their higher-grade recurrent lesion collected 1 to 8 years later. Three patients received no treatment and three patients received radiotherapy alone between their first and second surgeries. RNA was extracted from frozen specimens and following quality control, analyzed with the Illumina Next-Generation Sequencing platform (HiSeq HT paired end, TruSeq Kit). Comparison of RNA-seq results from primary and recurrent specimens identified 2042 differentially expressed genes (FC ≥2) for the no-treatment group and 2066 differentially expressed genes for the radiotherapy group. These genes include CADM2, SPP1, NDRG2 and CA9 which are associated with pro-tumor processes such as signal transduction, cell adhesion and treatment resistance. Validation is in progress. Identifying key genes driving glioma progression and recurrence will increase our understanding of the nature of these tumors and reveal core processes and potential novel targets that may be exploited for additional therapies for this deadly cancer.

scholarly journals Transcriptome profiling of peanut (Arachis hypogaea) gynophores in gravitropic response

2013 ◽  
Vol 40 (12) ◽  
pp. 1249 ◽  
Author(s):  
Hai-fen Li ◽  
Xiao-Ping Chen ◽  
Fang-he Zhu ◽  
Hai-Yan Liu ◽  
Yan-Bin Hong ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Arachis Hypogaea ◽  
Molecular Mechanisms ◽  
Carbon Fixation ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Pentose Phosphate ◽  
Differentially Expressed ◽  
Pcr Analysis

Peanut (Arachis hypogaea L.) produces flowers aerially, but the fruit develops underground. This process is mediated by the gynophore, which always grows vertically downwards. The genetic basis underlying gravitropic bending of gynophores is not well understood. To identify genes related to gynophore gravitropism, gene expression profiles of gynophores cultured in vitro with tip pointing upward (gravitropic stimulation sample) and downward (control) at both 6 and 12 h were compared through a high-density peanut microarray. After gravitropic stimulation, there were 174 differentially expressed genes, including 91 upregulated and 83 downregulated genes at 6 h, and 491 differentially expressed genes including 129 upregulated and 362 downregulated genes at 12 h. The differentially expressed genes identified were assigned to 24 functional categories. Twenty pathways including carbon fixation, aminoacyl-tRNA biosynthesis, pentose phosphate pathway, starch and sucrose metabolism were identified. The quantitative real-time PCR analysis was performed for validation of microarray results. Our study paves the way to better understand the molecular mechanisms underlying the peanut gynophore gravitropism.

scholarly journals Bioinformatic Analysis: Screening and Identification of Differentially Expressed Genes Modified by m6A in Ovarian Cancer

2020 ◽  
Author(s):  
Huidong Liu ◽  
Wen-wen Zhang ◽  
Ge Lou
Keyword(s):  
Ovarian Cancer ◽  
Differentially Expressed Genes ◽  
Clinical Sample ◽  
Therapeutic Targets ◽  
Enrichment Analysis ◽  
Underlying Mechanism ◽  
Bioinformatic Analysis ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Kegg Pathways

Abstract Background: N6-methyladenosine(m6A) is one of the most common RNA modifications that occurs at the nitrogen-6 position of adenine. Emerging evidence has revealed that regulatory functions of m6A play an essential role in the development of cancer. However the study of m6A in ovarian cancer(OC) is still in our infancy. In this work ,we aimed to identify and analysis the differentially expressed genes(DEGs） modified by m6A which can provide new therapeutic targets and key biomarkers in OC.Methods: We downloaded Microarray datasets GSE146553 and GSE124766 from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified by GEO2R analysis tools. Subsequently, The DAVID database was used to construct Enrichment analysis of GO and KEGG pathways. Next, the DEGs modified by m6A were identified by m6AVar database. Finally, the functional analysis and clinical sample validation of these genes were verified by ONCOMINE, GEPIA, cBioPortal online platform and Kaplan-Meier Plotter.Results:152 DEGs were selected ,and the DEGs were mainly enriched in extracellular exosome, spindle microtubule, response to hypoxia and cell cycle .And we identified 15 DEGs which were modified by m6A:MAPK10、MXRA5、CHD7、MECOM、SCN7A、GREB、PRUNE2、MX2、TOP2A、JAM2、DST、LAPTM5、CDKN2A、GATM and ANGPTL1. After statistical analysis, two DEGs (SCN7A and GAMT) were selected for detailed study. We revealed that SCN7A and GAMT were expressed at a low level in OC. Afterwards, Survival analysis showed that SCN7A and GAMT expression were correlated with OC overall survival. And the expression of SCN7A and GAMT mRNA decreasing in different TNM stages. Finally, we presumed that the modification of m6A spongs GAMT via EIF4A3 or FUS to participate in the occcurrence and the development of OC.Conclusion: Altogether, the current study identified and analysised the DEGs modified by m6A in OC. It will help us to investigate the underlying mechanism and progression of OC. In addition, it can provide new diagnostic markers and potential therapeutic targets in OC.

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