scholarly journals Effects of EFNA1 on cell phenotype and prognosis of esophageal carcinoma

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Yongqiang Zhang ◽  
Jinning Zhang ◽  
Guanlong Pan ◽  
Tianhao Guan ◽  
Changhao Zhang ◽  
...  
Keyword(s):  
Esophageal Carcinoma ◽  
Cell Model ◽  
Enrichment Analysis ◽  
Tnm Staging ◽  
Cell Phenotype ◽  
Pathway Enrichment Analysis ◽  
Tissue Samples ◽  
Paired Samples ◽  
The Relationship ◽  
Inhibit Cell Proliferation

Abstract Background To investigate the expression and clinical significance of EFNA1 in broad-spectrum tumors, and to evaluate its relationship with prognosis and biological functions of esophageal carcinoma (ESCA). Methods EFNA1 expression in various cancers was analyzed according to the data in the TCGA database. The clinical data were integrated, to analyze the relationship with ESCA clinical parameters and prognosis, and EFNA1 expression in ESCA tissue samples was detected by immunohistochemistry (IHC). Based on bioinformatics, the functional background of EFNA1 overexpression was analyzed. EFNA1 knockout cell model was established by EFNA1-shRNA transfecting ESCA cells, and the effect of knocking down EFNA1 on the proliferation of ESCA cells was detected by MTT. Results Among 7563 samples from TCGA, the EFNA1 gene highly expressed in 15 samples with common cancers and endangered the prognosis of patients with tumors. Its overexpression in ESCA and its influence on the prognosis were most significant. EFNA1 expression in 80 samples with ESCA and their paired samples was tested by IHC to verify its high expression (paired t test, P < 0.001) in ESCA tissues. It was found that EFNA1 expression was related to clinical factors (TNM staging, P = 0.031; lymph node metastasis, P = 0.043; infiltration, P = 0.016). Meanwhile, EFNA1 was found to be an independent risk factor based on the COX multi-factor analysis. And to further explore the importance of EFNA1 in tumors, EC-9706 and ECA109 cells were screened from 8 ESCA-related cell lines to build EFNA1 knockdown cell models. The results showed that EFNA1 knockdown significantly inhibited the proliferation of tumor cells (P < 0.05). In terms of molecular mechanism, EFNA1 related genes were significantly enriched in the proliferative pathway according to the pathway enrichment analysis. It was found that knocking down EFNA1 did inhibit cell proliferation based on cell experiments. Conclusions EFNA1 overexpression in ESCA tissue is related to the prognosis of patients. Knocking down EFNA1 can significantly inhibit the proliferation of ESCA cells.

scholarly journals Lipidomics profiling of goose granulosa cell model of stearoyl-CoA desaturase function identifies a pattern of lipid droplets associated with follicle development

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xin Yuan ◽  
Shenqiang Hu ◽  
Liang Li ◽  
Chunchun Han ◽  
Hehe Liu ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Lipid Droplets ◽  
Cell Model ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Follicle Development ◽  
Microscopy Analysis ◽  
Stearoyl Coa Desaturase ◽  
Underlying Mechanisms

Abstract Background Despite their important functions and nearly ubiquitous presence in cells, an understanding of the biology of intracellular lipid droplets (LDs) in goose follicle development remains limited. An integrated study of lipidomic and transcriptomic analyses was performed in a cellular model of stearoyl-CoA desaturase (SCD) function, to determine the effects of intracellular LDs on follicle development in geese. Results Numerous internalized LDs, which were generally spherical in shape, were dispersed throughout the cytoplasm of granulosa cells (GCs), as determined using confocal microscopy analysis, with altered SCD expression affecting LD content. GC lipidomic profiling showed that the majority of the differentially abundant lipid classes were glycerophospholipids, including PA, PC, PE, PG, PI, and PS, and glycerolipids, including DG and TG, which enriched glycerophospholipid, sphingolipid, and glycerolipid metabolisms. Furthermore, transcriptomics identified differentially expressed genes (DEGs), some of which were assigned to lipid-related Gene Ontology slim terms. More DEGs were assigned in the SCD-knockdown group than in the SCD-overexpression group. Integration of the significant differentially expressed genes and lipids based on pathway enrichment analysis identified potentially targetable pathways related to glycerolipid/glycerophospholipid metabolism. Conclusions This study demonstrated the importance of lipids in understanding follicle development, thus providing a potential foundation to decipher the underlying mechanisms of lipid-mediated follicle development.

scholarly journals Integrated analysis of lncRNA-miRNA-mRNA ceRNA network and the potential prognosis indicators in sarcomas

2020 ◽  
Author(s):  
Ling Zhang ◽  
Lu Gao ◽  
Yu Zhao ◽  
Xuelei Ma
Keyword(s):  
Survival Analysis ◽  
Protein Interactions ◽  
Sequence Data ◽  
Gene Prediction ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Integrated Analysis ◽  
Pathway Enrichment Analysis ◽  
Tissue Samples ◽  
Cerna Network

Abstract The ceRNA network has been demonstrated to play crucial roles in multiple biological processes and the development of neoplasms, which have the potential to become diagnostic and prognosis markers and therapeutic targets. In this work, we comparing the expression profiles between sarcoma identified differentially expressed genes (DEGs), lncRNAs (DELs) and miRNAs (DEMs) in sarcomas and normal tissue samples in GEO datasets. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied to investigate the major functions of the overlapping DEGs. Then, lncRNA-miRNA interactions and miRNA-mRNA interactions were predicted, and a ceRNA regulatory network was constructed. In addition, the mRNAs included in ceRNA network were used to construct the protein-protein interactions network, and the survival analysis of sarcomas was performed according to the biomarkers included in the ceRNA network. According to the RNA sequence data from GEO dataset, 1296 DEGs were identified in sarcoma samples by combining the GO and Pathway enrichment analysis, 338 DELs were discovered after re-annotating the probes, and 36 DEGs were ascertained through intersecting two different expression miRNAs sets. Further, 448 miRNA-mRNA interactions and 454 miRNA-lncRNA interactions were obtained through target gene prediction, and then, we constructed a lncRNA-miRNA-mRNA ceRNA network containing 9 miRNAs, 69 lncRNAs and 113 mRNAs. PPI network showed that the hub up-regulated nodes include IGF1, PRKCB and GNAI3, and the hub down-regulated nodes include AR, CYCS and PPP1CB. Survival analysis revealed that the expression levels of 12 RNAs involved in the ceRNA network were associated with overall survival of sarcoma patients. Our study showed that the ceRNA network in sarcomas based on that lncRNA could serve as ceRNA and discovered the potential indicators for prognosis of sarcoma patients.

Transcriptome Analysis Reveals Dynamic Changes of Inflammation and Stress Responses during Different Infected Stages with Burkholderia pseudomallei

2020 ◽  
Author(s):  
Chenglong Rao(Former Corresponding Author) ◽  
Chan Mao ◽  
Yupei Xia ◽  
Meijuan Zhang ◽  
Zhiqiang Hu ◽  
...  
Keyword(s):  
Stress Responses ◽  
Burkholderia Pseudomallei ◽  
Cellular Response ◽  
Cell Model ◽  
Mrna Level ◽  
A549 Cells ◽  
Enrichment Analysis ◽  
Host Cells ◽  
P Value ◽  
Pathway Enrichment Analysis

Abstract Background: Burkholderia pseudomallei causes melioidosis and usually affects patients’ lungs, its persistent infection promotes the fusion of host cells, leading to the formation of multinucleated giant cells (MGCs) at the late infected stage. In this study, the global transcriptomic responses of B. pseudomallei infection of a human lung epithelial A549 cell model with different infected stages were investigated by means of microarray analysis to further elucidate the host cellular factors involved in the occurrence and development of the event. Results: A set of 35 common differential expression genes (DEGs) in EI and LI on the mRNA level applying a cut-off level of 1.5-fold change and a p-value < 0.05 were observed. Microarray data were further verified by Real-Time quantitative PCR (RT-qPCR). GO classification and pathway enrichment analysis revealed these DEGs mainly involved in inflammatory response related processes, such as cellular response to tumor necrosis factor, cellular response to lipopolysaccharide, positive regulation of NF-κB transcription factor activity. p-eIF2α, ATF4,NF-κB2(p52) and IL-1β were next selected to be validated by western bloting, which indicated B. pseudomallei could activate the eIF2α-ATF4 axis and NF-κB2 pathway in A549 cells. Conclusion: Our data shed light on the transcriptome dynamics of A549 cells which persistently infected with B. pseudomallei and suggested that the formation of MGCs may be a means for B. pseudomallei to manipulate the host's inflammation and stress response to adapt to intracellular life.

scholarly journals Hidden in plain sight: The effects of BCG vaccination in COVID-19 pandemic

2020 ◽  
Author(s):  
Eman Ali Toraih ◽  
Jessica Ashraf Sedhom ◽  
Titilope Modupe Dokunmu ◽  
Mohammad Hosny Hussein ◽  
Emmanuelle ML Ruiz ◽  
...  
Keyword(s):  
Enrichment Analysis ◽  
Protective Role ◽  
Pathway Enrichment Analysis ◽  
Infection Group ◽  
Bcg Vaccination ◽  
Pathway Enrichment ◽  
Kegg Pathways ◽  
The Relationship ◽  
Bioinformatic Approach ◽  
Cross Reference

AbstractTo investigate the relationship between BCG vaccination and SARS-CoV-2 by bioinformatic approach. Two datasets for Sars-CoV-2 infection group and BCG-vaccinated group were downloaded. Differentially Expressed Genes were identified. Gene ontology and pathways were functionally enriched, and networking was constructed in NetworkAnalyst. Lastly, correlation between post-BCG vaccination and COVID-19 transcriptome signatures were established. A total of 161 DEGs (113 upregulated DEGs and 48 downregulated genes) were identified in the Sars-CoV-2 group. In the pathway enrichment analysis, cross-reference of upregulated KEGG pathways in Sars-CoV-2 with downregulated counterparts in the BCG-vaccinated group, resulted in the intersection of 45 common pathways, accounting for 86.5% of SARS-CoV-2 upregulated pathways. Of these intersecting pathways, a vast majority were immune and inflammatory pathways with top significance in IL-17, TNF, NOD-like receptors, and NF-κB signaling pathways. Our data suggests BCG-vaccination may incur a protective role in COVID-19 patients until a targeted vaccine is developed.Supplementary Materials(https://drive.google.com/open?id=15Na738L282XNaQAJUh0cZf1WoG9jJfzJ)

scholarly journals The Contribution of MicroRNAs to the Inflammatory and Neoplastic Characteristics of Erdheim–Chester Disease

Cancers ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3240
Author(s):  
Ran Weissman ◽  
Eli L. Diamond ◽  
Julien Haroche ◽  
Nir Pillar ◽  
Guy Shapira ◽  
...  
Keyword(s):  
In Silico Analysis ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Potential Contribution ◽  
Tissue Samples ◽  
Erdheim Chester Disease ◽  
Transcriptional Alterations ◽  
Signaling Inhibitors ◽  
Erdheim Chester ◽  
Chester Disease

The pathogenesis of histiocytic neoplasms is driven by mutations activating the MAPK/ERK pathway, but little is known about the transcriptional and post-transcriptional alterations involved in these neoplasms. We analyzed microRNA (miRNA) expression in plasma samples and tissue biopsies of Erdheim–Chester disease (ECD) and Langerhans cell histiocytosis (LCH) patients. In silico analysis revealed a potential role of miRNAs in regulating gene expression in these neoplasms as compared with healthy controls (HC). NanoString analysis revealed 101 differentially expressed plasma miRNAs in 16 ECD patients as compared with 11 HC, 95% of which were downregulated. MiRNAs-15a-5p, -15b-5p, -21-5p, -107, -221-3p, -320e, -630, and let-7 family miRNAs were further evaluated by qRT-PCR in an extended cohort of 32 ECD patients, seven LCH and 15 HC. Six miRNAs (let-7a, let-7c, miR-15a-5p, miR-15b-5p, miR-107 and miR-630) were highly expressed in LCH plasma and tissue samples as compared with ECD. Pathway enrichment analysis indicated the miRNA contribution to inflammatory and pro-survival signaling pathways. Moreover, the let-7 family members were downregulated in untreated ECD patients as compared with HC, while treatment with MAPK/ERK signaling inhibitors for 16 weeks resulted in their upregulation, which was in parallel with the radiologic response seen by PET-CT. The study highlights the potential contribution of miRNA to the inflammatory and neoplastic characteristics of ECD and LCH.

scholarly journals A Network Pharmacology Approach to Uncover the Pharmacological Mechanism of XuanHuSuo Powder on Osteoarthritis

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Huaqi Tang ◽  
Shuaibing He ◽  
Xinyue Zhang ◽  
Shilin Luo ◽  
Baixia Zhang ◽  
...  
Keyword(s):  
Interleukin 1 ◽  
Enrichment Analysis ◽  
Global Scale ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Complementary Method ◽  
Pharmacological Mechanism ◽  
First Time ◽  
The Relationship

As the most familiar type of arthritis and a chronic illness of the joints, Osteoarthritis (OA) affects a great number of people on the global scale. XuanHuSuo powder (XHSP), a conventional herbal formula from China, has been extensively applied in OA treatment. Nonetheless, its pharmacological mechanism has not been completely expounded. In this research, a network pharmacology approach has been chosen to study the pharmacological mechanism of XHSP on OA, and the pharmacology networks were established based on the relationship between four herbs found in XHSP, compound targets, and OA targets. The pathway enrichment analysis revealed that the significant bioprocess networks of XHSP on OA were regulation of inflammation, interleukin-1β(IL-1β) production and nitric oxide (NO) biosynthetic process, response to cytokine or estrogen stimuli, and antiapoptosis. These effects have not been reported previously. The comprehensive network pharmacology approach developed by our research has revealed, for the first time, a connection between four herbs found in XHSP, corresponding compound targets, and OA pathway systems that are conducive to expanding the clinical application of XHSP. The proposed network pharmacology approach could be a promising complementary method by which researchers might better evaluate multitarget or multicomponent drugs on a systematic level.

scholarly journals Meta-analysis of gene expression disease signatures in colonic biopsy tissue from patients with ulcerative colitis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bryan Linggi ◽  
Vipul Jairath ◽  
Guangyong Zou ◽  
Lisa M. Shackelton ◽  
Dermot P. B. McGovern ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ulcerative Colitis ◽  
Chemokine Receptors ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Interleukin 10 ◽  
Pathway Enrichment Analysis ◽  
Tissue Samples ◽  
Biopsy Tissue

AbstractPublicly available ulcerative colitis (UC) gene expression datasets from observational studies and clinical trials include inherently heterogeneous disease characteristics and methodology. We used meta-analysis to identify a robust UC gene signature from inflamed biopsies. Eight gene expression datasets derived from biopsy tissue samples from noninflammatory bowel disease (IBD) controls and areas of active inflammation from patients with UC were publicly available. Expression- and meta-data were downloaded with GEOquery. Differentially expressed genes (DEG) in individual datasets were defined as those with fold change > 1.5 and a Benjamini–Hochberg adjusted P value < .05. Meta-analysis of all DEG used a random effects model. Reactome pathway enrichment analysis was conducted. Meta-analysis identified 946 up- and 543 down-regulated genes in patients with UC compared to non-IBD controls (1.2 and 1.7 times fewer up- and down-regulated genes than the median of the individual datasets). Top-ranked up- and down-regulated DEG were LCN2 and AQP8. Multiple immune-related pathways (e.g., ‘Chemokine receptors bind chemokine’ and ‘Interleukin-10 signaling’) were significantly up-regulated in UC, while ‘Biological oxidations’ and ‘Fatty acid metabolism’ were downregulated. A web-based data-mining tool with the meta-analysis results was made available (https://premedibd.com/genes.html). A UC inflamed biopsy disease gene signature was derived. This signature may be an unbiased reference for comparison and improve the efficiency of UC biomarker studies by increasing confidence for identification of disease-related genes and pathways.

scholarly journals Idebenone-Activating Autophagic Degradation of α-Synuclein via Inhibition of AKT-mTOR Pathway in a SH-SY5Y-A53T Model of Parkinson’s Disease: A Network Pharmacological Approach

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Pei Kun He ◽  
Yu Yuan Gao ◽  
Feng-Juan Lyu ◽  
Jia Ning Chen ◽  
Yu Hu Zhang ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Molecular Docking ◽  
Cell Model ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Mtor Pathway ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Autophagic Flux

Background. Parkinson’s disease (PD) is the second most common neurodegenerative disease worldwide, which currently lacks disease-modifying therapy to slow down its progression. Idebenone, a coenzyme Q10 (CQ10) analogue, is a well-known antioxidant and has been used to treat neurological disorders. However, the mechanism of Idebenone on PD has not been fully elucidated. This study aims to predict the potential targets of Idebenone and explore its therapeutic mechanism against PD. Method. We obtained potential therapeutic targets through database prediction, followed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Next, we constructed and analyzed a protein-protein interaction network (PPI) and a drug-target-pathway-disease network. A molecular docking test was conducted to identify the interactions between Idebenone and potential targets. Lastly, a PD cell line of SH-SY5Y overexpressing mutant α-synuclein was used to validate the molecular mechanism. Result. A total of 87 targets were identified based on network pharmacology. The enrichment analysis highlighted manipulation of MAP kinase activity and the PI3K-AKT signaling pathway as potential pharmacological targets for Idebenone against PD. Additionally, molecular docking showed that AKT and MAPK could bind tightly with Idebenone. In the cell model of PD, Idebenone activated autophagy and promoted α-synuclein degradation by suppressing the AKT/mTOR pathway. Pretreating cells with chloroquine (CQ) to block autophagic flux could diminish the pharmacological effect of Idebenone to clear α-synuclein. Conclusion. This study demonstrated that Idebenone exerts its anti-PD effects by enhancing autophagy and clearance of α-synuclein, thus providing a theoretical and experimental basis for Idebenone therapy against PD.

scholarly journals Identification of miRNAs and associated pathways regulated by Leukemia Inhibitory Factor in trophoblastic cell lines

2018 ◽  
Author(s):  
Diana M. Morales-Prieto ◽  
Emanuel Barth ◽  
Jose Martín Murrieta-Coxca ◽  
Rodolfo R. Favaro ◽  
Ruby N. Gutiérrez-Samudio ◽  
...  
Keyword(s):  
Cell Lines ◽  
Leukemia Inhibitory Factor ◽  
Cell Model ◽  
Enrichment Analysis ◽  
Inhibitory Factor ◽  
Pathway Enrichment Analysis ◽  
Trophoblast Cells ◽  
Trophoblastic Cell ◽  
Data Set

ABSTRACTIntroductionLeukemia Inhibitory Factor (LIF) regulates behavior of trophoblast cells and their interaction with immune and endothelial cells.In vitro, trophoblast cell response to LIF may vary depending on the cell model. Reported differences in the miRNA profile of trophoblastic cells may be responsible for these observations. Therefore, miRNA expression was investigated in four trophoblastic cell lines under LIF stimulation followed byin silicoanalysis of altered miRNAs and their associated pathways.MethodsLow density TaqMan miRNA assays were used to quantify levels of 762 mature miRNAs under LIF stimulation in three choriocarcinoma-derived (JEG-3, ACH-3P and AC1-M59) and a trophoblast immortalized (HTR-8/SVneo) cell lines. Expression of selected miRNAs was confirmed in primary trophoblast cells and cell lines by qPCR. Targets and associated pathways of the differentially expressed miRNAs were inferred from the miRTarBase followed by a KEGG Pathway Enrichment Analysis. HTR-8/SVneo and JEG-3 cells were transfected with miR-21-mimics and expression of miR-21 targets was assessed by qPCR.ResultsA similar number of miRNAs changed in each tested cell line upon LIF stimulation, however, low coincidence of individual miRNA species was observed and occurred more often among choriocarcinoma-derived cells (complete data set athttp://www.ncbi.nlm.nih.gov/geo/under GEO accession number GSE130489). Altered miRNAs were categorized into pathways involved in human diseases, cellular processes and signal transduction. Six cascades were identified as significantly enriched, including JAK/STAT and TGFB-SMAD. Upregulation of miR-21-3p was validated in all cell lines and primary cells and STAT3 was confirmed as its target.DiscussionDissimilar miRNA responses may be involved in differences of LIF effects on trophoblastic cell lines.

scholarly journals A Meta-Path-Based Prediction Method for Human miRNA-Target Association

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Jiawei Luo ◽  
Cong Huang ◽  
Pingjian Ding
Keyword(s):  
Mirna Target ◽  
Prediction Method ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Sequence Information ◽  
Considerable Problem ◽  
Meta Path ◽  
Target Association ◽  
The Relationship ◽  
Gene Expressing

MicroRNAs (miRNAs) are short noncoding RNAs that play important roles in regulating gene expressing, and the perturbed miRNAs are often associated with development and tumorigenesis as they have effects on their target mRNA. Predicting potential miRNA-target associations from multiple types of genomic data is a considerable problem in the bioinformatics research. However, most of the existing methods did not fully use the experimentally validated miRNA-mRNA interactions. Here, we developed RMLM and RMLMSe to predict the relationship between miRNAs and their targets. RMLM and RMLMSe are global approaches as they can reconstruct the missing associations for all the miRNA-target simultaneously and RMLMSe demonstrates that the integration of sequence information can improve the performance of RMLM. In RMLM, we use RM measure to evaluate different relatedness between miRNA and its target based on different meta-paths; logistic regression and MLE method are employed to estimate the weight of different meta-paths. In RMLMSe, sequence information is utilized to improve the performance of RMLM. Here, we carry on fivefold cross validation and pathway enrichment analysis to prove the performance of our methods. The fivefold experiments show that our methods have higher AUC scores compared with other methods and the integration of sequence information can improve the performance of miRNA-target association prediction.

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