scholarly journals Screening of prognostic biomarkers for endometrial carcinoma based on a ceRNA network

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e6091 ◽  
Author(s):  
Ming-Jun Zheng ◽  
Rui Gou ◽  
Wen-Chao Zhang ◽  
Xin Nie ◽  
Jing Wang ◽  
...  
Keyword(s):  
Endometrial Carcinoma ◽  
Differentially Expressed Genes ◽  
Differentially Expressed ◽  
Prognostic Biomarkers ◽  
Rna Seq ◽  
Cerna Network ◽  
Topological Network ◽  
Regulation Network ◽  
Underlying Mechanisms

Objective This study aims to reveal the regulation network of lncRNAs-miRNAs-mRNA in endometrial carcinoma (EC), to investigate the underlying mechanisms of EC occurrence and progression, to screen prognostic biomarkers. Methods RNA-seq and miRNA-seq data of endometrial carcinoma were downloaded from the TCGA database. Edge.R package was used to screen differentially expressed genes. A database was searched to determine differentially expressed lncRNA-miRNA and miRNA-mRNA pairs, to construct the topological network of ceRNA, and to elucidate the key RNAs that are for a prognosis of survival. Results We screened out 2632 mRNAs, 1178 lncRNAs and 189 miRNAs that were differentially expressed. The constructed ceRNA network included 97 lncRNAs, 20 miRNAs and 73 mRNAs. Analyzing network genes for associations with prognosies revealed 169 prognosis-associated RNAs, including 92 lncRNAs, 16miRNAs and 61 mRNAs. Conclusion Our results reveal new potential mechanisms underlying the carcinogenesis and progression of endometrial carcinoma.

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 Identification of prognostic biomarkers related to the tumor microenvironment in thyroid carcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jun-wei Du ◽  
Guo-quan Li ◽  
Yang-sen Li ◽  
Xin-guang Qiu
Keyword(s):  
Tumor Microenvironment ◽  
Thyroid Carcinoma ◽  
Differentially Expressed Genes ◽  
Essential Role ◽  
Endocrine Tumor ◽  
Differentially Expressed ◽  
Differential Analysis ◽  
Additional Information ◽  
Cerna Network ◽  
Immune Score

AbstractThyroid Carcinoma (THCA) is the most common endocrine tumor that is mainly treated using surgery and radiotherapy. In addition, immunotherapy is a recently developed treatment option that has played an essential role in the management of several types of tumors. However, few reports exist on the use of immunotherapy to treat THCA. The study downloaded the miRNA, mRNA and lncRNA data for THCA patients from the TCGA database (https://portal.gdc.cancer.gov/). Thereafter, the tumor samples were divided into cold and hot tumors, based on the immune score of the tumor microenvironment. Moreover, the differentially expressed lncRNAs and miRNAs were obtained. Finally, the study jointly constructed a ceRNA network through differential analysis of the mRNA data for cold and hot tumors. The study first assessed the level of immune infiltration in the THCA tumor microenvironment then divided the samples into cold and hot tumors, based on the immune score. Additionally, a total of 568 up-regulated and 412 down-regulated DEGs were screened by analyzing the differences between hot and cold tumors. Thereafter, the study examined the differentially expressed genes for lncRNA and miRNA. The results revealed 629 differentially expressed genes related to lncRNA and 114 associated with miRNA. Finally, a ceRNA network of the differentially expressed genes was constructed. The results showed a five-miRNA hubnet, i.e., hsa-mir-204, hsa-mir-128, hsa-mir-214, hsa-mir-150 and hsa-mir-338. The present study identified the immune-related mRNA, lncRNA and miRNA in THCA then constructed a ceRNA network. These results are therefore important as they provide more insights on the immune mechanisms in THCA. The findings also provides additional information for possible THCA immunotherapy.

scholarly journals Construction of a competitive endogenous RNA network and analysis of potential regulatory axis targets in glioblastoma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Kai Yu ◽  
Huan Yang ◽  
Qiao-li Lv ◽  
Li-chong Wang ◽  
Zi-long Tan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Differentially Expressed Genes ◽  
Pearson Correlation ◽  
Differentially Expressed ◽  
Migration And Invasion ◽  
Glioblastoma Cells ◽  
Network Chain ◽  
Cerna Network ◽  
Potential Marker

Abstract Background Glioblastoma is the most common primary malignant brain tumor. Because of the limited understanding of its pathogenesis, the prognosis of glioblastoma remains poor. This study was conducted to explore potential competing endogenous RNA (ceRNA) network chains and biomarkers in glioblastoma by performing integrated bioinformatics analysis. Methods Transcriptome expression data from The Cancer Genome Atlas database and Gene Expression Omnibus were analyzed to identify differentially expressed genes between glioblastoma and normal tissues. Biological pathways potentially associated with the differentially expressed genes were explored by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, and a protein-protein interaction network was established using the STRING database and Cytoscape. Survival analysis using Gene Expression Profiling Interactive Analysis was based on the Kaplan–Meier curve method. A ceRNA network chain was established using the intersection method to align data from four databases (miRTarBase, miRcode, TargetScan, and lncBace2.0), and expression differences and correlations were verified by quantitative reverse-transcription polymerase chain reaction analysis and by determining the Pearson correlation coefficient. Additionally, an MTS assay and the wound-healing and transwell assays were performed to evaluate the effects of complement C1s (C1S) on the viability and migration and invasion abilities of glioblastoma cells, respectively. Results We detected 2842 differentially expressed (DE) mRNAs, 2577 DE long non-coding RNAs (lncRNAs), and 309 DE microRNAs (miRNAs) that were dysregulated in glioblastoma. The final ceRNA network consisted of six specific lncRNAs, four miRNAs, and four mRNAs. Among them, four DE mRNAs and one DE lncRNA were correlated with overall survival (p < 0.05). C1S was significantly correlated with overall survival (p= 0.015). In functional assays, knockdown of C1S inhibited the proliferation and invasion of glioblastoma cell lines. Conclusions We established four ceRNA networks that may influence the occurrence and development of glioblastoma. Among them, the MIR155HG/has-miR-129-5p/C1S axis is a potential marker and therapeutic target for glioblastoma. Knockdown of C1S inhibited the proliferation, migration, and invasion of glioblastoma cells. These findings clarify the role of the ceRNA regulatory network in glioblastoma and provide a foundation for further research.

scholarly journals HIV-1 Infection Transcriptomics: Meta-Analysis of CD4+ T Cells Gene Expression Profiles

Viruses ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 244 ◽  
Author(s):  
Antonio Victor Campos Coelho ◽  
Rossella Gratton ◽  
João Paulo Britto de Melo ◽  
José Leandro Andrade-Santos ◽  
Rafael Lima Guimarães ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Differentially Expressed Genes ◽  
Cd4 T Cells ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Infected Cells ◽  
Hiv 1

HIV-1 infection elicits a complex dynamic of the expression various host genes. High throughput sequencing added an expressive amount of information regarding HIV-1 infections and pathogenesis. RNA sequencing (RNA-Seq) is currently the tool of choice to investigate gene expression in a several range of experimental setting. This study aims at performing a meta-analysis of RNA-Seq expression profiles in samples of HIV-1 infected CD4+ T cells compared to uninfected cells to assess consistently differentially expressed genes in the context of HIV-1 infection. We selected two studies (22 samples: 15 experimentally infected and 7 mock-infected). We found 208 differentially expressed genes in infected cells when compared to uninfected/mock-infected cells. This result had moderate overlap when compared to previous studies of HIV-1 infection transcriptomics, but we identified 64 genes already known to interact with HIV-1 according to the HIV-1 Human Interaction Database. A gene ontology (GO) analysis revealed enrichment of several pathways involved in immune response, cell adhesion, cell migration, inflammation, apoptosis, Wnt, Notch and ERK/MAPK signaling.

scholarly journals Phytophthora infestans Sporangia Produced in Culture and on Tomato Leaflet Lesions Show Marked Differences in Indirect Germination Rates, Aggressiveness, and Global Transcription Profiles

2019 ◽  
Vol 32 (5) ◽  
pp. 515-526 ◽  
Author(s):  
William E. Fry ◽  
Sean P. Patev ◽  
Kevin L. Myers ◽  
Kan Bao ◽  
Zhangjun Fei
Keyword(s):  
Phytophthora Infestans ◽  
Differentially Expressed Genes ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Moist Chamber ◽  
Field Isolates ◽  
Rxlr Effectors ◽  
Transcription Profiles ◽  
Independent Field ◽  
Pure Cultures

Sporangia of Phytophthora infestans from pure cultures on agar plates are typically used in lab studies, whereas sporangia from leaflet lesions drive natural infections and epidemics. Multiple assays were performed to determine if sporangia from these two sources are equivalent. Sporangia from plate cultures showed much lower rates of indirect germination and produced much less disease in field and moist-chamber tests. This difference in aggressiveness was observed whether the sporangia had been previously incubated at 4°C (to induce indirect germination) or at 21°C (to prevent indirect germination). Furthermore, lesions caused by sporangia from plates produced much less sporulation. RNA-Seq analysis revealed that thousands of the >17,000 P. infestans genes with a RPKM (reads per kilobase of exon model per million mapped reads) >1 were differentially expressed in sporangia obtained from plate cultures of two independent field isolates compared with sporangia of those isolates from leaflet lesions. Among the significant differentially expressed genes (DEGs), putative RxLR effectors were overrepresented, with almost half of the 355 effectors with RPKM >1 being up- or downregulated. DEGs of both isolates include nine flagellar-associated genes, and all were down-regulated in plate sporangia. Ten elicitin genes were also detected as DEGs in both isolates, and nine (including INF1) were up-regulated in plate sporangia. These results corroborate previous observations that sporangia produced from plates and leaflets sometimes yield different experimental results and suggest hypotheses for potential mechanisms. We caution that use of plate sporangia in assays may not always produce results reflective of natural infections and epidemics.

scholarly journals Bioinformatics-based Screening of Key Genes for Saponin Metabolism in Quinoa

2021 ◽  
Author(s):  
Chengang Guo ◽  
Zhimin wei ◽  
Wei Lyu ◽  
Yanlou Geng
Keyword(s):  
Differentially Expressed Genes ◽  
Principal Component ◽  
Enrichment Analysis ◽  
Hierarchical Cluster ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Differential Analysis ◽  
Rna Seq ◽  
Protein Coding ◽  
Key Genes

Abstract Quinoa saponins have complex, diverse and evident physiologic activities. However, the key regulatory genes for quinoa saponin metabolism are not yet well studied. The purpose of this study was to explore genes closely related to quinoa saponin metabolism. In this study, the significantly differentially expressed genes in yellow quinoa were firstly screened based on RNA-seq technology. Then, the key genes for saponin metabolism were selected by gene set enrichment analysis (GSEA) and principal component analysis (PCA) statistical methods. Finally, the specificity of the key genes was verified by hierarchical clustering. The results of differential analysis showed that 1654 differentially expressed genes were achieved after pseudogenes deletion. Therein, there were 142 long non-coding genes and 1512 protein-coding genes. Based on GSEA analysis, 116 key candidate genes were found to be significantly correlated with quinoa saponin metabolism. Through PCA dimension reduction analysis, 57 key genes were finally obtained. Hierarchical cluster analysis further demonstrated that these key genes can clearly separate the four groups of samples. The present results could provide references for the breeding of sweet quinoa and would be helpful for the rational utilization of quinoa saponins.

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