scholarly journals Bioinformatic Analysis of Gene Expression Profile in Plasma of Hypertensive Patients

2020 ◽  
Vol 33 (6) ◽  
pp. 581-581
Author(s):  
Yan-zhen Li ◽  
Hao-jie Xu ◽  
Jia-min Hu ◽  
Shi-zhu Lin ◽  
Na Zhang ◽  
...  
Keyword(s):  
Messenger Rna ◽  
Noncoding Rna ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Therapeutic Interventions ◽  
Total Rna ◽  
Hormone Synthesis ◽  
Public Data

Abstract Background To analyze expression profiles of long noncoding RNA (lncRNA) and messenger RNA (mRNA) in patients with essential hypertension (EH) and normotensive adults. Methods The gene chip dataset GSE76845, which was generated from 5 plasma samples from patients with EH and 5 normotensives, was downloaded from the National Biotechnology Information Center Public Data Platform. Each sample (total RNA) was pooled from the total RNA of 3 age- and gender-matched subjects (EH patients or healthy controls). A ClusterProfiler package including gene set enrichment analysis (GSEA) was used to identify differentially expressed genes. The target microRNA and mRNA were predicted by microcode, microDB, microTarBase, and TargetScan databases. Finally, a competing endogenous RNAs (ceRNA) regulatory network was constructed. Results Compared with the healthy control adults, 191 differential lncRNAs (90 upregulated and 101 downregulated) and 1,187 differential mRNAs (533 upregulated and 654 downregulated) were identified in EH patients. GSEA analysis showed that 17 pathways, including ubiquinone and terpenoid-quinone biosynthesis, parathyroid hormone synthesis secretion and action, fatty acid metabolism, and steroid hormone biosynthesis are involved in hypertension. A ceRNA network consisting of 150 nodes and 488 interactive pairs was constructed. Conclusions lncRNA and mRNA profile analysis provides new insight into molecular mechanisms of EH pathogenesis and potential targets for therapeutic interventions.

scholarly journals Identification of IL10RA by Weighted Correlation Network Analysis and in vitro Validation of Its Association With Prognosis of Metastatic Melanoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Si Cheng ◽  
Zhe Li ◽  
Wenhao Zhang ◽  
Zhiqiang Sun ◽  
Zhigang Fan ◽  
...  
Keyword(s):  
Network Analysis ◽  
Metastatic Melanoma ◽  
Large Scale ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Migration And Invasion

Skin cutaneous melanoma (SKCM) is the major cause of death for skin cancer patients, its high metastasis often leads to poor prognosis of patients with malignant melanoma. However, the molecular mechanisms underlying metastatic melanoma remain to be elucidated. In this study we aim to identify and validate prognostic biomarkers associated with metastatic melanoma. We first construct a co-expression network using large-scale public gene expression profiles from GEO, from which candidate genes are screened out using weighted gene co-expression network analysis (WGCNA). A total of eight modules are established via the average linkage hierarchical clustering, and 111 hub genes are identified from the clinically significant modules. Next, two other datasets from GEO and TCGA are used for further screening of biomarker genes related to prognosis of metastatic melanoma, and identified 11 key genes via survival analysis. We find that IL10RA has the highest correlation with clinically important modules among all identified biomarker genes. Further in vitro biochemical experiments, including CCK8 assays, wound-healing assays and transwell assays, have verified that IL10RA can significantly inhibit the proliferation, migration and invasion of melanoma cells. Furthermore, gene set enrichment analysis shows that PI3K-AKT signaling pathway is significantly enriched in metastatic melanoma with highly expressed IL10RA, indicating that IL10RA mediates in metastatic melanoma via PI3K-AKT pathway.

scholarly journals Comprehensive Analysis of Differentially Expressed Profiles of mRNA, lncRNA, and circRNA in the Uterus of Seasonal Reproduction Sheep

Genes ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 301 ◽  
Author(s):  
Yongfu La ◽  
Xiaoyun He ◽  
Liping Zhang ◽  
Ran Di ◽  
Xiangyu Wang ◽  
...  
Keyword(s):  
Thyroid Hormone ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Seasonal Reproduction ◽  
Hormone Synthesis ◽  
Long Photoperiod

Photoperiod is one of the important factors leading to seasonal reproduction of sheep. However, the molecular mechanisms underlying the photoperiod regulation of seasonal reproduction remain poorly understood. In this study, we compared the expression profiles of mRNAs, lncRNAs, and circRNAs in uterine tissues from Sunite sheep during three different photoperiods, namely, the short photoperiod (SP), short transfer to long photoperiod (SLP), and long photoperiod (LP). The results showed that 298, 403, and 378 differentially expressed (DE) mRNAs, 171, 491, and 499 DE lncRNAs, and 124, 270, and 400 DE circRNAs were identified between SP and LP, between SP and SLP, and between LP and SLP, respectively. Furthermore, functional enrichment analysis showed that the differentially expressed RNAs were mainly involved in the GnRH signaling pathway, thyroid hormone synthesis, and thyroid hormone signaling pathway. In addition, co-expression networks of lncRNA–mRNA were constructed based on the correlation analysis between the differentially expressed RNAs. Our study provides new insights into the expression changes of RNAs in different photoperiods, which might contribute to understanding the molecular mechanisms of seasonal reproduction in sheep.

scholarly journals Identification of cell cycle as the critical pathway modulated by exosome-derived microRNAs in gallbladder carcinoma

2021 ◽  
Vol 38 (12) ◽  
Author(s):  
Li Su ◽  
Jicheng Zhang ◽  
Xinglong Zhang ◽  
Lei Zheng ◽  
Zhifa Zhu
Keyword(s):  
Cell Cycle ◽  
Molecular Mechanisms ◽  
Early Stage ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Cell Cycle Checkpoints ◽  
Gene Set Enrichment Analysis ◽  
Clinical Samples ◽  
Critical Pathway ◽  
Cerna Network

AbstractGallbladder cancer (GBC), the most common malignancy in the biliary tract, is highly lethal malignant due to seldomly specific symptoms in the early stage of GBC. This study aimed to identify exosome-derived miRNAs mediated competing endogenous RNAs (ceRNA) participant in GBC tumorigenesis. A total of 159 differentially expressed miRNAs (DEMs) was identified as exosome-derived miRNAs, contains 34 upregulated exo-DEMs and 125 downregulated exo-DEMs based on the expression profiles in GBC clinical samples downloaded from the Gene Expression Omnibus database with the R package. Among them, 2 up-regulated exo-DEMs, hsa-miR-125a-3p and hsa-miR-4647, and 5 down-regulated exo-DEMs, including hsa-miR-29c-5p, hsa-miR-145a-5p, hsa-miR-192-5p, hsa-miR-194-5p, and hsa-miR-338-3p, were associated with the survival of GBC patients. Results of the gene set enrichment analysis showed that the cell cycle-related pathways were activated in GBC tumor tissues, mainly including cell cycle, M phase, and cell cycle checkpoints. Furthermore, the dysregulated ceRNA network was constructed based on the lncRNA-miRNA-mRNA interactions using miRDB, TargetScan, miRTarBase, miRcode, and starBase v2.0., consisting of 27 lncRNAs, 6 prognostic exo-DEMs, and 176 mRNAs. Together with prognostic exo-DEMs, the STEAP3-AS1/hsa-miR-192-5p/MAD2L1 axis was identified, suggesting lncRNA STEAP3-AS1, might as a sponge of exosome-derived hsa-miR-192-5p, modulates cell cycle progression via affecting MAD2L1 expression in GBC tumorigenesis. In addition, the biological functions of genes in the ceRNA network were also annotated by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Our study promotes exploration of the molecular mechanisms associated with tumorigenesis and provide potential targets for GBC diagnosis and treatment.

Integrated Transcriptomics and Reverse Pharmacophore Mapping-based Network Pharmacology to Explore the Mechanisms of Natural Compounds against Doxorubicin-induced Cardiotoxicity

2021 ◽  
Vol 24 ◽  
Author(s):  
Junfeng Zhu ◽  
Xiaojiao Yi ◽  
Haiying Ding ◽  
Like Zhong ◽  
Luo Fang
Keyword(s):  
Gene Expression ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Intervention Strategy ◽  
Enrichment Analysis ◽  
Natural Compounds ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Pharmacophore Mapping

Background: Doxorubicin-induced cardiotoxicity (DIC) has greatly limited the clinical benefits of this frontline drug in oncotherapy. Drug combination with natural compounds (NCs) that possess potency against DIC is considered as a promising intervention strategy. However, the mechanisms of action (MoAs) underlying such drug interactions remain poorly understood. The aim of this study was to systematically pursuit of the molecular mechanisms of NCs against DIC. Methods: First, the gene expression signatures of DIC were characterized from transcriptomics datasets with doxorubicin-treated and untreated cardiomyocytes using differentially expressed gene identification, functional enrichment analysis, and protein-protein interaction network analysis. Secondly, reverse pharmacophore mapping-based network pharmacology was employed to illustrate the MoAs of 82 publicly reported NCs with anti-DIC potency. Cluster analysis based on their enriched pathways was performed to gain systematic insights into the anti-DIC mechanisms of the NCs. Finally, the typical compounds were validated using gene set enrichment analysis (GSEA) of the relevant gene expression profiles from a public gene expression database. Results: Based on their anti-DIC MoAs, the 82 NCs could be divided into four groups, which corresponded to ten MoA clusters. GSEA and literature evidence on these compounds were provided to validate the MoAs identified through this bioinformatics analysis. The results suggested that NCs exerted potency against DIC through both common and different MoAs. Conclusion: This strategy integrating different types of bioinformatics approaches is expected to create new insights for elucidating the MoAs of NCs against DIC.

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

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.

scholarly journals Connectivity Map Analysis Indicates PI3K/Akt/mTOR Inhibitors as Potential Anti-Hypoxia Drugs in Neuroblastoma

Cancers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2809
Author(s):  
Paolo Uva ◽  
Maria Carla Bosco ◽  
Alessandra Eva ◽  
Massimo Conte ◽  
Alberto Garaventa ◽  
...  
Keyword(s):  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Drug Repurposing ◽  
Enrichment Analysis ◽  
Mtor Inhibitors ◽  
Gene Set Enrichment Analysis ◽  
Low Oxygen ◽  
Connectivity Map ◽  
Hypoxic Conditions ◽  
Connectivity Score

Neuroblastoma (NB) is one of the deadliest pediatric cancers, accounting for 15% of deaths in childhood. Hypoxia is a condition of low oxygen tension occurring in solid tumors and has an unfavorable prognostic factor for NB. In the present study, we aimed to identify novel promising drugs for NB treatment. Connectivity Map (CMap), an online resource for drug repurposing, was used to identify connections between hypoxia-modulated genes in NB tumors and compounds. Two sets of 34 and 21 genes up- and down-regulated between hypoxic and normoxic primary NB tumors, respectively, were analyzed with CMap. The analysis reported a significant negative connectivity score across nine cell lines for 19 compounds mainly belonging to the class of PI3K/Akt/mTOR inhibitors. The gene expression profiles of NB cells cultured under hypoxic conditions and treated with the mTORC complex inhibitor PP242, referred to as the Mohlin dataset, was used to validate the CMap findings. A heat map representation of hypoxia-modulated genes in the Mohlin dataset and the gene set enrichment analysis (GSEA) showed an opposite regulation of these genes in the set of NB cells treated with the mTORC inhibitor PP242. In conclusion, our analysis identified inhibitors of the PI3K/Akt/mTOR signaling pathway as novel candidate compounds to treat NB patients with hypoxic tumors and a poor prognosis.

scholarly journals Pineal gland transcriptomic profiling reveals the differential regulation of lncRNA and mRNA related to prolificacy in STH sheep with two FecB genotypes

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Chunyan Li ◽  
Xiaoyun He ◽  
Zijun Zhang ◽  
Chunhuan Ren ◽  
Mingxing Chu
Keyword(s):  
Pineal Gland ◽  
Expression Pattern ◽  
Noncoding Rna ◽  
Target Genes ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Rna Seq ◽  
Important Regulator ◽  
Gsh Metabolism ◽  
Transcriptome Expression

Abstract Background Long noncoding RNA (lncRNA) has been identified as important regulator in hypothalamic-pituitary-ovarian axis associated with sheep prolificacy. However, little is known of their expression pattern and potential roles in the pineal gland of sheep. Herein, RNA-Seq was used to detect transcriptome expression pattern in pineal gland between follicular phase (FP) and luteal phase (LP) in FecBBB (MM) and FecB++ (ww) STH sheep, respectively, and differentially expressed (DE) lncRNAs and mRNAs associated with reproduction were identified. Results Overall, 135 DE lncRNAs and 1360 DE mRNAs in pineal gland between MM and ww sheep were screened. Wherein, 39 DE lncRNAs and 764 DE mRNAs were identified (FP vs LP) in MM sheep, 96 DE lncRNAs and 596 DE mRNAs were identified (FP vs LP) in ww sheep. Moreover, GO and KEGG enrichment analysis indicated that the targets of DE lncRNAs and DE mRNAs were annotated to multiple biological processes such as phototransduction, circadian rhythm, melanogenesis, GSH metabolism and steroid biosynthesis, which directly or indirectly participate in hormone activities to affect sheep reproductive performance. Additionally, co-expression of lncRNAs-mRNAs and the network construction were performed based on correlation analysis, DE lncRNAs can modulate target genes involved in related pathways to affect sheep fecundity. Specifically, XLOC_466330, XLOC_532771, XLOC_028449 targeting RRM2B and GSTK1, XLOC_391199 targeting STMN1, XLOC_503926 targeting RAG2, XLOC_187711 targeting DLG4 were included. Conclusion All of these differential lncRNAs and mRNAs expression profiles in pineal gland provide a novel resource for elucidating regulatory mechanism underlying STH sheep prolificacy.

scholarly journals In Silico Identification of Contradictory Role of ADAMTS5 in Hepatocellular Carcinoma

2021 ◽  
Vol 20 ◽  
pp. 153303382098682
Author(s):  
Zhipeng Zhu ◽  
Jiuhua Xu ◽  
Xiaofang Wu ◽  
Sihao Lin ◽  
Lulu Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Subgroup Analysis ◽  
Prognostic Value ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Clinicopathological Parameters ◽  
Free Survival ◽  
Cox Regression Analysis ◽  
The Impact

Background: ADAMTS5 has different roles in multiple types of cancers and participates in various molecular mechanisms. However, the prognostic value of ADAMTS5 in patients with hepatocellular carcinoma (HCC) still remains unclear. We carried the study to evaluate the prognostic value and identified underlying molecular mechanisms in HCC. Methods: Firstly, the association of ADAMTS5 expression and clinicopathological parameters was evaluated by in GSE14520. Next, ADAMTS5 expression in HCC was performed using GSE14520, GSE36376, GSE76427 and The Cancer Genome Atlas (TCGA) profile. Furthermore, Kaplan-Meier analysis, Univariate and Multivariate Cox regression analysis, subgroup analysis was performed to evaluate the prognostic value of ADAMTS5 in HCC. Finally, GO enrichment analysis, gene set enrichment analysis (GSEA) and weighted gene co-expression network analysis (WGCNA) were performed to revealed underlying molecular mechanisms. Result: The expression of ADAMTS5 was positively correlated with the development of HCC. Next, high ADAMTS5 expression was significantly associated with poorer survival (all P < 0.05) and the impact of ADAMTS5 on all overall survival (OS), disease-free survival (DFS), relapse-free survival (RFS), disease specific survival (DSS) and progression free interval (PFI) was specific for HCC among other 29 cancer types. Subgroup analysis showed that ADAMTS5 overexpression was significantly associated with poorer OS in patients with HCC. Finally, ADAMTS5 might participate in the status conversion from metabolic-dominant to extracellular matrix-dominant, and the activation of ECM-related biological process might contribute to high higher mortality risk for patients with HCC. Conclusion: ADAMTS5 may play an important role in the progression of HCC, and may be considered as a novel and effective biomarker for predicting prognosis for patients with HCC.

Robust Metabolic Transcriptional Components in 34,494 Patient-Derived Samples and Cell Lines

2021 ◽  
Author(s):  
Vincent Christiaan Leeuwenburgh ◽  
Carlos G. Urzúa-Traslaviña ◽  
Arkajyoti Bhattacharya ◽  
Marthe T.C. Walvoort ◽  
Mathilde Jalving ◽  
...  
Keyword(s):  
Cell Lines ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Metabolic Processes ◽  
Gene Sets ◽  
Transcriptional Changes ◽  
Cancer Tissues ◽  
Tumor Biopsies ◽  
Transcriptional Landscape

Abstract Background: Patient-derived bulk expression profiles of cancers can provide insight into transcriptional changes that underlie reprogrammed metabolism in cancer. These profiles represent the average expression pattern of all heterogeneous tumor and non-tumor cells present in biopsies of tumor lesions. Hence, subtle transcriptional footprints of metabolic processes can be concealed by other biological processes and experimental artifacts. However, consensus Independent Component Analyses (c-ICA) can capture statistically independent transcriptional footprints, of both subtle and more pronounced metabolic processes. Methods: We performed c-ICA with 34,494 bulk expression profiles of patient-derived tumor biopsies, non-cancer tissues, and cell lines. Gene set enrichment analysis with 608 gene sets that describe metabolic processes was performed to identify transcriptional components enriched for metabolic processes (mTCs). The activity of these mTCs were determined in all samples to create a metabolic transcriptional landscape. Results: A set of 555 mTCs were identified of which many were robust across different datasets, platforms, and patient-derived tissues and cell lines. We demonstrate how the metabolic transcriptional landscape defined by the activity of these mTCs in samples can be used to explore associations between the metabolic transcriptome and drug sensitivities, patient outcomes, and the composition of the immune tumor microenvironment. Conclusions: To facilitate the use of our transcriptional metabolic landscape, we have provided access to all data via a web portal ( www.themetaboliclandscapeofcancer.com ). We believe this resource will contribute to the formulation of new hypotheses on how to metabolically engage the tumor or its (immune) microenvironment.

scholarly journals Protective Effect of Quercetin against H2O2-Induced Oxidative Damage in PC-12 Cells: Comprehensive Analysis of a lncRNA-Associated ceRNA Network

2020 ◽  
Vol 2020 ◽  
pp. 1-22
Author(s):  
Zheyu Zhang ◽  
Pengji Yi ◽  
Min Yi ◽  
Xiaoliang Tong ◽  
Xin Cheng ◽  
...  
Keyword(s):  
Hydrogen Peroxide ◽  
Oxidative Damage ◽  
Protective Effect ◽  
Messenger Rna ◽  
Noncoding Rna ◽  
Expression Profiles ◽  
Damage Model ◽  
Antioxidant Properties ◽  
Pc 12 Cells ◽  
Cerna Network

Quercetin is a bioflavonoid with potential antioxidant properties. However, the mechanisms underlying its effects remain unclear. Herein, we focused on integrating long noncoding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA) sequencing of PC-12 cells treated with quercetin. We treated PC-12 cells with hydrogen peroxide to generate a validated oxidative damage model. We evaluated the effects of quercetin on PC-12 cells and established the lncRNA, miRNA, and mRNA profiles of these cells. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses of these RNAs were conducted to identify the key pathways. Quercetin significantly protected PC-12 neuronal cells from hydrogen peroxide-induced death. We identified 297, 194, and 14 significantly dysregulated lncRNAs, miRNAs, and mRNAs, respectively, associated with the antioxidant effect of quercetin. Furthermore, the phosphatidylinositol-3-kinase/protein kinase B pathway was identified as the crucial signalling pathway. Finally, we constructed a lncRNA-associated competing endogenous RNA (ceRNA) network by utilizing oxidative damage mechanism-matched miRNA, lncRNA, and mRNA expression profiles and those changed by quercetin. In conclusion, quercetin exerted a protective effect against oxidative stress-induced damage in PC-12 cells. Our study provides novel insight into ceRNA-mediated gene regulation in the progression of oxidative damage and the action mechanisms of quercetin.

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