scholarly journals Identification of Key Candidate Biomarkers and Pathways in Atherosclerosis

2020 ◽  
Author(s):  
Zhijun Meng ◽  
Jia Gao ◽  
Hongping Liang ◽  
Caihong Liu ◽  
Jianli Zhao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signaling Pathway ◽  
Early Stage ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Effective Prevention ◽  
Diagnostic Indicator

Abstract Background Atherosclerosis is the leading cause of cardiovascular disease worldwide for which lacks effective prevention and therapeutic strategy. Therefore, clinical indicators for early diagnosis and screening are in great need. The present study aimed to elucidate the key genetic signatures and pathways identifying the key candidate biomarker in atherosclerosis by integrative bioinformatics analysis combining with experimental assay. Methods The gene expression profiles (GSE30169, GSE6584) were achieved from the Gene Expression Omnibus database. Functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to examine the biological functions of identified differentially expressed genes (DEGs). A protein-protein interaction (PPI) network was mapped using Cytoscape software. Results 91 DEGs were identified, including 68 up-regulated genes and 23 down-regulated genes. Functional enrichment analysis indicated that DEGs genes were significantly enriched in ferroptosis, TNF signaling pathway, IL-17 signaling pathway. 12 nodes with the highest degrees were selected as hub genes. CCL2, CXCL1, IL6, and DUSP1 can serve as a sensitive diagnostic indicator for the early stage of atherosclerosis; CEBPB and HMOX1 can serve as a diagnostic indicator for diabetic atherosclerosis; TRIB3 is a sensitive marker indicating atherosclerosis risks in diabetic women group.Conclusions In conclusion, we have identified key candidate genes that indicate the diagnosis of patients with atherosclerosis, and these genes may serve as potential therapeutic or drug development targets for atherosclerosis.

scholarly journals Understanding the Modus Operandi of MicroRNA Regulatory Clusters

Cells ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 1103 ◽  
Author(s):  
Arthur C. Oliveira ◽  
Luiz A. Bovolenta ◽  
Lucas Alves ◽  
Lucas Figueiredo ◽  
Amanda O. Ribeiro ◽  
...  
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Target Prediction ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Modus Operandi ◽  
Wide Range

MicroRNAs (miRNAs) are non-coding RNAs that regulate a wide range of biological pathways by post-transcriptionally modulating gene expression levels. Given that even a single miRNA may simultaneously control several genes enrolled in multiple biological functions, one would expect that these tiny RNAs have the ability to properly sort among distinctive cellular processes to drive protein production. To test this hypothesis, we scrutinized previously published microarray datasets and clustered protein-coding gene expression profiles according to the intensity of fold-change levels caused by the exogenous transfection of 10 miRNAs (miR-1, miR-7, miR-9, miR-124, miR-128a, miR-132, miR-133a, miR-142, miR-148b, miR-181a) in a human cell line. Through an in silico functional enrichment analysis, we discovered non-randomic regulatory patterns, proper of each cluster identified. We demonstrated that miRNAs are capable of equivalently modulate the expression signatures of target genes in regulatory clusters according to the biological function they are assigned to. Moreover, target prediction analysis applied to ten vertebrate species, suggest that such miRNA regulatory modus operandi is evolutionarily conserved within vertebrates. Overall, we discovered a complex regulatory cluster-module strategy driven by miRNAs, which relies on the controlled intensity of the repression over distinct targets under specific biological contexts. Our discovery helps to clarify the mechanisms underlying the functional activity of miRNAs and makes it easier to take the fastest and most accurate path in the search for the functions of miRNAs in any distinct biological process of interest.

scholarly journals Monozygotic Twins Discordant for Immunoglobulin A Nephropathy Display Differences in DNA Methylation and Gene Expression

2020 ◽  
pp. 1-10
Author(s):  
Min Wei ◽  
Sijun Meng ◽  
Sufang Shi ◽  
Lijun Liu ◽  
Xujie Zhou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Expression Profiles ◽  
Immunoglobulin A ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Genome Wide ◽  
Mz Twins

<b><i>Introduction:</i></b> Immunoglobulin A nephropathy (IgAN) is the most common primary glomerulonephritis. It involves both genetic and environmental factors, among which DNA methylation, the most studied epigenetic modification, was shown to play a role. Here, we assessed genome-wide DNA methylation and gene expression profiles in 2 pairs of IgAN-discordant monozygotic (MZ) twins, in order to characterize methylation changes and their potential influences on gene expression in IgAN. <b><i>Methods:</i></b> Genome-wide DNA methylation and gene expression profiles were evaluated in peripheral blood mononuclear cells obtained from 2 IgAN-discordant MZ twins. Differentially methylated regions (DMRs) and differentially expressed genes (DEGs) were detected, and an integrated analysis was performed. Finally, functional enrichment analysis was done for DMR-associated genes and DEGs. <b><i>Results:</i></b> Totally 521 DMRs were detected for 2 IgAN-discordant MZ twins. Among them, 9 DMRs were found to be mapped to genes that differentially expressed in 2 MZ twins, indicating the potential regulatory mechanisms of expression for these 9 genes (<i>MNDA</i>, <i>DYSF</i>, <i>IL1R2</i>, <i>TLR6</i>, <i>TREML2</i>, <i>TREM1</i>, <i>IL32</i>, <i>S1PR5</i>, and <i>ADGRE3</i>) in IgAN. Biological process analysis of them showed that they were mostly involved in the immune system process. Functional enrichment analysis of DEGs and DMR-associated genes both identified multiple pathways relevant to inflammatory and immune responses. And DMR-associated genes were significantly enriched in terms related to T-cell function. <b><i>Conclusions:</i></b> Our findings indicate that changes in DNA methylation patterns were involved in the pathogenesis of IgAN. Nine target genes detected in our study may provide new ideas for the exploration of molecular mechanisms of IgAN.

Identify Key Genes by Weighted Gene Co-Expression Network Analysis for Lung Adenocarcinoma

Nano LIFE ◽  
2019 ◽  
Vol 09 (01n02) ◽  
pp. 1940002
Author(s):  
Jichen Xu ◽  
Xianchun Zong ◽  
Qianshu Ren ◽  
Hongyu Wang ◽  
Lijuan Zhao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Lung Adenocarcinoma ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Oocyte Meiosis ◽  
Key Genes

The aim of this paper is to identify key genes in lung adenocarcinoma (LUAD) through weighted gene co-expression network analysis (WGCNA), and to further understand the molecular mechanism of LUAD. 107 gene expression profiles were downloaded from GSE10072 in the GEO database. We performed rigorous processing of the initial gene expression profile data. Subsequently, we used WGCNA to identify disease-driven modules and enforced functional enrichment analysis. The key genes were defined as the most connected genes in the driver module and were validated using the GSE75037 and TCGA database. GSE10072 removed 41 unpaired lung samples and 4 outliers. By analyzing the 62 samples using WGCNA, we obtained 26 modules and identified the brown and magenta modules as the driving modules for the LUAD. We found that the “Cell cycle”, “Oocyte meiosis” and “Progesterone-mediated oocyte maturation” pathways may be related to the occurrence of LUAD. GSE75037 removed 8 outlier and obtained 2909 differentially expressed genes (DEGs), 26 genes (9 genes in the brown module, 17 genes in the magenta module) overlap with key genes in the driver module. The results of the survival analysis suggest that 19 genes were significantly correlated with the patient’s survival time, including KPNA2, FEN1, RRM2, TOP2A, CENPF, MCM4, BIRC5, MELK, MAD2L1, CCNB1, CCNA2, KIF11, CDKN3, NUSAP1, CEP55, AURKA, NEK2, KIF14 and CDCA8, which may be potential biomarkers or therapeutic targets for LUAD. In this study, we provide a theoretical basis for further understanding the biological mechanism of LUAD through bioinformatics analysis of LUAD.

scholarly journals reString: an open-source Python software to perform automatic functional enrichment retrieval, results aggregation and data visualization

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Stefano Manzini ◽  
Marco Busnelli ◽  
Alice Colombo ◽  
Elsa Franchi ◽  
Pasquale Grossano ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Statistical Tests ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Knowledge Bases ◽  
Functional Enrichment ◽  
Reference Database ◽  
Multiple User ◽  
Daunting Task

AbstractFunctional enrichment analysis is an analytical method to extract biological insights from gene expression data, popularized by the ever-growing application of high-throughput techniques. Typically, expression profiles are generated for hundreds to thousands of genes/proteins from samples belonging to two experimental groups, and after ad-hoc statistical tests, researchers are left with lists of statistically significant entities, possibly lacking any unifying biological theme. Functional enrichment tackles the problem of putting overall gene expression changes into a broader biological context, based on pre-existing knowledge bases of reference: database collections of known expression regulation, relationships and molecular interactions. STRING is among the most popular tools, providing both protein–protein interaction networks and functional enrichment analysis for any given set of identifiers. For complex experimental designs, manually retrieving, interpreting, analyzing and abridging functional enrichment results is a daunting task, usually performed by hand by the average wet-biology researcher. We have developed reString, a cross-platform software that seamlessly retrieves from STRING functional enrichments from multiple user-supplied gene sets, with just a few clicks, without any need for specific bioinformatics skills. Further, it aggregates all findings into human-readable table summaries, with built-in features to easily produce user-customizable publication-grade clustermaps and bubble plots. Herein, we outline a complete reString protocol, showcasing its features on a real use-case.

scholarly journals Ten-gene signature reveals the significance of clinical prognosis and immuno-correlation of osteosarcoma and study on novel skeleton inhibitors regarding MMP9

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Weihang Li ◽  
Ziyi Ding ◽  
Dong Wang ◽  
Chengfei Li ◽  
Yikai Pan ◽  
...  
Keyword(s):  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Signature ◽  
Functional Enrichment ◽  
Computational Techniques ◽  
Hub Genes ◽  
Clinical Prognosis ◽  
Lead Compounds

Abstract Objectives This study aimed to identify novel targets in the carcinogenesis, therapy and prognosis of osteosarcoma from genomic level, together with screening ideal lead compounds with potential inhibition regarding MMP-9. Methods Gene expression profiles from GSE12865, GSE14359, GSE33382, GSE36001 and GSE99671 were obtained respectively from GEO database. Differentially expressed genes were identified, and functional enrichment analysis, such as GO, KEGG, GSEA, PPI were performed to make a comprehensive understanding of the hub genes. Next, a series of high-precision computational techniques were conducted to screen potential lead compounds targeting MMP9, including virtual screening, ADME, toxicity prediction, and accurate docking analysis. Results 10 genes, MMP9, CD74, SPP1, CXCL12, TYROBP, FCER1G, HCLS1, ARHGDIB, LAPTM5 and IGF1R were identified as hub genes in the initiation of osteosarcoma. Machine learning, multivariate Cox analysis, ssGSEA and survival analysis demonstrated that these genes had values in prognosis, immune-correlation and targeted treatment. Tow novel compounds, ZINC000072131515 and ZINC000004228235, were screened as potential inhibitor regarding MMP9, and they could bind to MMP9 with favorable interaction energy and high binding affinity. Meanwhile, they were precited to be efficient and safe drugs with low-ames mutagenicity, none weight evidence of carcinogenicity, as well as non-toxic with liver. Conclusions This study revealed the significance of 10-gene signature in the development of osteosarcoma. Besides, drug candidates identified in this study provided a solid basis on MMP9 inhibitors’ development.

scholarly journals Microarray Analysis of Transcriptome of Medulla Identifies Potential Biomarkers for Parkinson’s Disease

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Xiao-Yang Liao ◽  
Wei-Wen Wang ◽  
Zheng-Hui Yang ◽  
Jun Wang ◽  
Hang Lin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Motor Nucleus ◽  
Inferior Olivary Nucleus ◽  
Potential Biomarkers

To complement the molecular pathways contributing to Parkinson’s disease (PD) and identify potential biomarkers, gene expression profiles of two regions of the medulla were compared between PD patients and control. GSE19587 containing two groups of gene expression profiles [6 dorsal motor nucleus of the vagus (DMNV) samples from PD patients and 5 from controls, 6 inferior olivary nucleus (ION) samples from PD patients and 5 from controls] was downloaded from Gene Expression Omnibus. As a result, a total of 1569 and 1647 differentially expressed genes (DEGs) were, respectively, screened in DMNV and ION with limma package ofR. The functional enrichment analysis by DAVID server (the Database for Annotation, Visualization and Integrated Discovery) indicated that the above DEGs may be involved in the following processes, such as regulation of cell proliferation, positive regulation of macromolecule metabolic process, and regulation of apoptosis. Further analysis showed that there were 365 common DEGs presented in both regions (DMNV and ION), which may be further regulated by eight clusters of microRNAs retrieved with WebGestalt. The genes in the common DEGs-miRNAs regulatory network were enriched in regulation of apoptosis process via DAVID analysis. These findings could not only advance the understandings about the pathogenesis of PD, but also suggest potential biomarkers for this disease.

scholarly journals Gene Expression Profiles of Multiple Synchronous Lesions in Lung Adenocarcinoma

Cells ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 3484
Author(s):  
Jisun Lim ◽  
Yeon Bi Han ◽  
Soo Young Park ◽  
Soyeon Ahn ◽  
Hyojin Kim ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Adenocarcinoma ◽  
Immune Cell ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Killer Cell ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Stepwise Change

Many studies support a stepwise continuum of morphologic changes between atypical adenomatous hyperplasia (AAH) and lung adenocarcinoma (ADC). Here we characterized gene expression patterns and the association of differentially expressed genes and immune tumor microenvironment behaviors in AAH to ADC during ADC development. Tumor tissues from nine patients with ADC and synchronous multiple ground glass nodules/lesions (GGN/Ls) were analyzed using RNA sequencing. Using clustering, we identified genes differentially and sequentially expressed in AAH and ADC compared to normal tissues. Functional enrichment analysis using gene ontology terms was performed, and the fraction of immune cell types was estimated. We identified up-regulated genes (ACSL5 and SERINC2) with a stepwise change of expression from AAH to ADC and validated those expressions by quantitative PCR and immunohistochemistry. The immune cell profiles revealed increased B cell activities and decreased natural killer cell activities in AAH and ADC. A stepwise change of differential expression during ADC development revealed potential effects on immune function in synchronous precursors and in tumor lesions in patients with lung cancer.

scholarly journals Identification and Validation of Immune-Related Prognostic Genes in the Tumor Microenvironment of Colon Adenocarcinoma

2022 ◽  
Vol 12 ◽  
Author(s):  
Shenghua Pan ◽  
Tingting Tang ◽  
Yanke Wu ◽  
Liang Zhang ◽  
Zekai Song ◽  
...  
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Tumor Microenvironment ◽  
Signaling Pathway ◽  
Colon Adenocarcinoma ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Kaplan Meier

The tumor microenvironment (TME) has been shown to be involved in angiogenesis, tumor metastasis, and immune response, thereby affecting the treatment and prognosis of patients. This study aims to identify genes that are dysregulated in the TME of patients with colon adenocarcinoma (COAD) and to evaluate their prognostic value based on RNA omics data. We obtained 512 COAD samples from the Cancer Genome Atlas (TCGA) database and 579 COAD patients from the independent dataset (GSE39582) in the Gene Expression Omnibus (GEO) database. The immune/stromal/ESTIMATE score of each patient based on their gene expression was calculated using the ESTIMATE algorithm. Kaplan–Meier survival analysis, Cox regression analysis, gene functional enrichment analysis, and protein–protein interaction (PPI) network analysis were performed. We found that immune and stromal scores were significantly correlated with COAD patients’ overall survival (log rank p &lt; 0.05). By comparing the high immune/stromal score group with the low score group, we identified 688 intersection differentially expressed genes (DEGs) from the TCGA dataset (663 upregulated and 25 downregulated). The functional enrichment analysis of intersection DEGs showed that they were mainly enriched in the immune process, cell migration, cell motility, Toll-like receptor signaling pathway, and PI3K-Akt signaling pathway. The hub genes were revealed by PPI network analysis. Through Kaplan–Meier and Cox analysis, four TME-related genes that were significantly related to the prognosis of COAD patients were verified in GSE39582. In addition, we uncovered the relationship between the four prognostic genes and immune cells in COAD. In conclusion, based on the RNA expression profiles of 1091 COAD patients, we screened four genes that can predict prognosis from the TME, which may serve as candidate prognostic biomarkers for COAD.

scholarly journals Identification of Potential Target Genes in HER-2 Positive Breast Cancer by Bioinformatics Analysis.

2020 ◽  
Author(s):  
Song Wang ◽  
Yi Quan ◽  
Hongying Lyu ◽  
Jian Deng
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Signaling Pathway ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Her 2 ◽  
Positive Breast Cancer

Abstract Background: HER-2 positive breast cancer has a high risk of for relapse, metastasis and drug resistance, and is correlated with a poor prognosis. Thus, the study objective was to reveal target genes and key pathways in HER-2 subtype breast cancer. Methods: The gene expression dataset (GSE29431) was downloaded from the Gene Expression Omnibus database(GEO), and the differentially expressed genes (DEGs) were determined using LIMMA package in R software. Subsequently, Functional enrichment analysis were performed in ClusterProfiler package of R platform. The Search Tool for the Retrieval of Interacting Genes (STRING) database was used to construct a Protein-Protein Interaction (PPI) network of DEGs. Module analysis and target genes were identified by Cytoscape software. Further more, The influence of target genes on overall survival (OS) was assessed using the Kaplan-Meier plotter database.Results: The differential expression analysis revealed 96 genes were up-regulated while 407 genes were down-regulated in HER-2 positive breast cancer tissue compared to normal breast tissue. Functional enrichment analysis showed that the DEGs were mainly involved in regulation of lipid metabolic process, PPAR signaling pathway and PI3K-Akt signaling pathway. PPI network construction revealed a total of 199 nodes and 560 edges, and 12 target genes were identified by the highest value of degree. In addition, target genes were associated with worse overall prognosis, including NUSAP1, PTTG1, CEP55, TOP2A, CCNB1, CENPF, MELK, AURKA, UBE2C, BUB1B, KIF20A and RRM2.Conclusion: The present study identified 12 target genes associated with the development of HER-2 subtype breast cancer, which may help to provide new biomarkers and therapeutic targets.

scholarly journals Fine mapping of goat polledness variant in six Chinese native breeds

2021 ◽  
Author(s):  
Yong Li ◽  
tao chen ◽  
Manman Yang ◽  
hu han ◽  
Dan Jiang ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Genome Wide Association Study ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Specific Element ◽  
A Genome

Background: The genetic mechanism of goat polledness has been studied for decades, but identifying causative variants and functional genes remains challenging. Results: Using a genome-wide association study (GWAS), we identified a significant striking locus for polledness in two different goat breeds. To reduce the linkage disequilibrium among variants for localizing causative variants in the finer region, we sequenced 79 goats from six Chinese native breeds (Jining Gray, Matou, Guizhou black, Yunnan black bone, Chaidamu, and Ujumqin) and identified 483.5 kb CNV (150,334,567-150,818,099) translocated into the previously identified 11.7 kb polled intersex syndrome region, which was consistent with previous research using intersex goat populations. Within the 483.5 kb CNV, a ~322 bp horn-specific element, similar to the superfamily of tRNA-derived families of SINEs, located at the first intron of the ERG gene was identified. The results of the GO enrichment analysis showed that the Horn-SINE element-associated genes were involved in both nervous system and head development. Finally, we used RNA sequencing to investigate gene expression profiles in the horn bud and skin tissues of horned and polled goats. We identified 1077 and 1222 differentially expressed genes between the horn bud and skin tissue in polled and horned goats, respectively. We also identified 367 differentially expressed genes in horn buds between polled and horned animals and found that the two CNV-related genes, ERG and FOXL2 were upregulated in the horn bud of polled goats. Gene functional enrichment analysis demonstrated that the downregulated genes in the horn bud of polled goats were enriched in skeletal system development, whereas the upregulated genes were significantly overexpressed in muscle tissue development.

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