scholarly journals Identification of prognostic factors for intrahepatic cholangiocarcinoma based on long non-coding RNAs-associated ceRNA network

2020 ◽  
Author(s):  
Zhichen Kang ◽  
Lixin Guo ◽  
Zhuo Zhu ◽  
Rongfeng Qu
Keyword(s):  
Prognostic Factors ◽  
Intrahepatic Cholangiocarcinoma ◽  
Messenger Rna ◽  
Transcriptome Sequencing ◽  
Tumor Biology ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Sequencing Data ◽  
Cerna Network ◽  
Non Coding Rnas

Abstract Background Accumulating evidence has highlighted the important roles of long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) in tumor biology. However, the roles of cancer long non coding RNAs (lncRNAs) in lncRNA-related ceRNA network of intrahepatic cholangiocarcinoma (ICC) remain enigmatic. The current study aims to identify prognostic factors in the lncRNA-related ceRNA network of ICC. Methods The transcriptome sequencing data of the lncRNAs, messenger RNA (mRNA) and microRNA (miR) were downloaded from SRA, and TCGA database respectively. Differentially expressed lncRNAs (DElncRNAs), DEmiRs and DEmRNAs were identified and adopted to construct lncRNA-miR-mRNA ceRNA network. ICC-associated DEmRNAs were adopted to construct the PPI network. The expression of the top 6 genes in the hub module was validated in mRNA transcriptome sequencing data and ICC-related gene expression dataset GSE45001, followed by GO and KEGG pathway enrichment analysis. The potential function of genes in hub module in the ceRNA network was finally subjected to GSEA. Results Sixty coexpression DEmRNAs were identified in the ceRNA network. The 6 top genes in the hub module consists of FOS, HGF, IGF2, FOXO1, NTF3 (downregulated), and IGF1R (upregulated) in ICC tissues compared to normal adjacent tissues, followed by the successful construction of lncRNA-miR-hub network with 86 ceRNA modules. FOS, IGF2 or IGF1R might regulate the development of ICC by targeting “N-glycan biosynthesis”, “α-linolenic acid metabolism” or “type II diabetes” pathways respectively. Conclusion These results show FOS, IGF2 and IGF1R serve as prognostic factors of ICC patients.

scholarly journals Identification of prognostic factors for intrahepatic cholangiocarcinoma using long non-coding RNAs-associated ceRNA network

2020 ◽  
Author(s):  
Zhichen Kang ◽  
Lixin Guo ◽  
Zhuo Zhu ◽  
Rongfeng Qu
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Signaling Pathway ◽  
Intrahepatic Cholangiocarcinoma ◽  
Messenger Rna ◽  
Transcriptome Sequencing ◽  
Pathway Enrichment Analysis ◽  
Sequencing Data ◽  
Cerna Network ◽  
Non Coding Rnas

Abstract Background: Accumulating amount of evidence has highlighted the important roles of long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) in tumor pathogenesis. However, the roles of long non coding RNAs (lncRNAs) in the lncRNA-related ceRNA network of intrahepatic cholangiocarcinoma (ICC) still remain enigmatic. The current study aims to identify prognostic factors in the lncRNA-related ceRNA network of ICC.Methods: The transcriptome sequencing data of lncRNAs, messenger RNA (mRNA) and microRNA (miR) were downloaded from the SRA and TCGA databases. Differentially expressed lncRNAs (DElncRNAs), DEmiRs and DEmRNAs were identified and adopted to construct an lncRNA-miR-mRNA ceRNA network. ICC-associated DEmRNAs were adopted to construct the protein-protein interaction (PPI) network. The expression of the top 6 genes in the hub module was validated with mRNA transcriptome sequencing data and ICC-related gene expression dataset GSE45001, followed by GO and KEGG pathway enrichment analysis. The relationship between the hub gene-associated ceRNA network and the overall survival of patients with ICC was predicted by conducting a Kaplan-Meier survival analysis. Results: Sixty co-expressed DEmRNAs were identified in the ceRNA network. The top 6 hub genes consisted of downregulated FOS, IGF2, FOXO1 and NTF3, upregulated IGF1R, and insignificantly downregulated HGF in ICC tissues, when compared to that of normal adjacent tissues, followed by the successful construction of lncRNA-miR-hub network consisting of 86 ceRNA modules. MME-AS1 and hsa-miR-182 were associated with overall survival in ICC patients. FOS, IGF1R, IGF2, FOXO1, and NTF3 might target “TGF-β signaling pathway”, “the hedgehog signaling pathway”, “retinol metabolism”, or “type II diabetes mellitus” pathways respectively. Conclusion: These results indicate that FOS, IGF1R, IGF2, FOXO1, and NTF3 were useful prognostic factors in determining the prognosis of patients with ICC.

scholarly journals RNA sequencing data integration reveals an miRNA interactome of osteoarthritis cartilage

2018 ◽  
Vol 78 (2) ◽  
pp. 270-277 ◽  
Author(s):  
Rodrigo Coutinho de Almeida ◽  
Yolande F M Ramos ◽  
Ahmed Mahfouz ◽  
Wouter den Hollander ◽  
Nico Lakenberg ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Messenger Rna ◽  
Enrichment Analysis ◽  
Integrated Approach ◽  
Nervous System Development ◽  
Regulatory Mechanisms ◽  
Pathway Enrichment Analysis ◽  
Sequencing Data ◽  
Pathway Enrichment ◽  
Mrna Targets

ObjectiveTo uncover the microRNA (miRNA) interactome of the osteoarthritis (OA) pathophysiological process in the cartilage.MethodsWe performed RNA sequencing in 130 samples (n=35 and n=30 pairs for messenger RNA (mRNA) and miRNA, respectively) on macroscopically preserved and lesioned OA cartilage from the same patient and performed differential expression (DE) analysis of miRNA and mRNAs. To build an OA-specific miRNA interactome, a prioritisation scheme was applied based on inverse Pearson’s correlations and inverse DE of miRNAs and mRNAs. Subsequently, these were filtered by those present in predicted (TargetScan/microT-CDS) and/or experimentally validated (miRTarBase/TarBase) public databases. Pathway enrichment analysis was applied to elucidate OA-related pathways likely mediated by miRNA regulatory mechanisms.ResultsWe found 142 miRNAs and 2387 mRNAs to be differentially expressed between lesioned and preserved OA articular cartilage. After applying prioritisation towards likely miRNA-mRNA targets, a regulatory network of 62 miRNAs targeting 238 mRNAs was created. Subsequent pathway enrichment analysis of these mRNAs (or genes) elucidated that genes within the ‘nervous system development’ are likely mediated by miRNA regulatory mechanisms (familywise error=8.4×10−5). Herein NTF3 encodes neurotrophin-3, which controls survival and differentiation of neurons and which is closely related to the nerve growth factor.ConclusionsBy an integrated approach of miRNA and mRNA sequencing data of OA cartilage, an OA miRNA interactome and related pathways were elucidated. Our functional data demonstrated interacting levels at which miRNA affects expression of genes in the cartilage and exemplified the complexity of functionally validating a network of genes that may be targeted by multiple miRNAs.

scholarly journals Integrative Analysis of lncRNAs, miRNAs, and mRNA-Associated ceRNA Network in an Atopic Dermatitis Recurrence Model

2018 ◽  
Vol 19 (10) ◽  
pp. 3263 ◽  
Author(s):  
Xiaoyu Wang ◽  
Kaifan Bao ◽  
Peng Wu ◽  
Xi Yu ◽  
Can Wang ◽  
...  
Keyword(s):  
Atopic Dermatitis ◽  
Messenger Rna ◽  
Integrative Analysis ◽  
Ample Evidence ◽  
Cerna Network ◽  
Non Coding Rna ◽  
Recurrence Model ◽  
Non Coding Rnas ◽  
Remission Phase ◽  
Long Non Coding Rna

Atopic dermatitis (AD) is a prevalent inflammatory skin disease characterized by its chronic nature and relapse. Ample evidence suggests that non-coding RNAs play a major role in AD pathogenesis. However, the mechanism remains unknown, particularly in AD recurrence. Dynamic morphological and cytokine changes were measured throughout the whole course of an FITC-induced AD recurrence murine model. Microarray assay and integrative analysis were performed to comprehensively explore long non-coding RNA (lncRNA), messenger RNA (mRNA), and microRNA (miRNA) networks. Our results showed that an AD recurrence model was established. Overall, 5766 lncRNAs, 4025 mRNAs, and 202 miRNAs changed after elicitation, whereas, 419 lncRNAs, 349 mRNAs, and more notably, only 23 miRNAs, were dysregulated in the remission phase. Gene ontology (GO) and KEGG pathway enrichment analyses were used to investigate the potential functions of the dysregulated genes. The altered regulation of seven miRNAs and seven lncRNAs were validated in different stages of the model. The competing endogenous RNA (ceRNA) network inferred that lncRNA humanlincRNA0490+ could compete for miR-155-5p binding, through which it might affect Pkiα expression. Altogether, our findings have provided a novel perspective on the potential roles of non-coding RNAs in AD, and suggest that specific non-coding RNAs could be new therapeutic targets against AD recurrence.

Predicting functional circular RNA-based competitive endogenous RNA network in gastric carcinoma using novel bioinformatics analysis

2021 ◽  
pp. 153537022110487
Author(s):  
Zirui Zhu ◽  
Rui Huang ◽  
Baojun Huang
Keyword(s):  
Messenger Rna ◽  
Expression Profiles ◽  
Clinical Stage ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Rank Aggregation ◽  
Circular Rnas ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Competitive Endogenous Rna

Gastric cancer (GC) remains one of the most prevalent types of malignancies worldwide, and also one of the most reported lethal tumor-related diseases. Circular RNAs (circRNAs) have been certified to be trapped in multiple aspects of GC pathogenesis. Yet, the mechanism of this regulation is mostly undefined. This research is designed to discover the vital circRNA-microRNA (miRNA)-messenger RNA (mRNA) regulatory network in GC. Expression profiles with diverse levels including circRNAs, miRNAs, and mRNAs were all determined using microarray public datasets from Gene Expression Ominous (GEO). The differential circRNAs expressions were recognized against the published robust rank aggregation algorithm. Besides, a circRNA-based competitive endogenous RNA (ceRNA) interaction network was visualized via Cytoscape software (version 3.8.0). Functional and pathway enrichment analysis associated with differentially expressed targeted mRNAs were conducted using Cytoscape and an online bioinformatics database. Furthermore, an interconnected protein–protein interaction association network which consisted of 51 mRNAs was predicted, and hub genes were screened using STRING and CytoHubba. Then, several hub genes were chosen to explore their expression associated with survival rate and clinical stage in GEPIA and Kaplan-Meier Plotter databases. Finally, a carefully designed circRNA-related ceRNA regulatory subnetwork including four circRNAs, six miRNAs, and eight key hub genes was structured using the online bioinformatics tool.

scholarly journals LINC01018 and SMIM25 sponged miR-182-5p in endometriosis revealed by the ceRNA network construction

2020 ◽  
Vol 34 ◽  
pp. 205873842097630
Author(s):  
Li Jiang ◽  
Mengmeng Zhang ◽  
Sixue Wang ◽  
Yuzhen Xiao ◽  
Jingni Wu ◽  
...  
Keyword(s):  
Messenger Rna ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Protein Protein Interaction ◽  
Cerna Network ◽  
Non Coding Rna ◽  
Differentially Expressed Mirnas ◽  
Long Non Coding Rna

The current study intended to explore the interaction of the long non-coding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA) under the background of competitive endogenous RNA (ceRNA) network in endometriosis (EMs). The differentially expressed miRNAs (DEmiRs), differentially expressed lncRNA (DELs), and differentially expressed genes (DEGs) between EMs ectopic (EC) and eutopic (EU) endometrium based on three RNA-sequencing datasets (GSE105765, GSE121406, and GSE105764) were identified, which were used for the construction of ceRNA network. Then, DEGs in the ceRNA network were performed with Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and protein-protein interaction (PPI) analysis. Besides, the DEmiRs in the ceRNA network were validated in GSE124010. And the target DELs and DEGs of verified DEmiRs were validated in GSE86534. The correlation of verified DEmiRs, DEGs, and DELs was explored. Moreover, gene set enrichment analysis (GSEA) was applied to investigate the function of verified DEmiRs, DEGs, and DELs. Overall, 1352 DEGs and 595 DELs from GSE105764, along with 27 overlapped DEmiRs between GSE105765 and GSE121406, were obtained. Subsequently, a ceRNA network, including 11 upregulated and 16 downregulated DEmiRs, 7 upregulated and 13 downregulated DELs, 48 upregulated and 46 downregulated DEGs, was constructed. The GO and KEGG pathway analysis showed that this ceRNA network probably was associated with inflammation-related pathways. Furthermore, hsa-miR-182-5p and its target DELs (LINC01018 and SMIM25) and DEGs (BNC2, CHL1, HMCN1, PRDM16) were successfully verified in the validation analysis. Besides, hsa-miR-182-5p was significantly negatively correlated with these target DELs and DEGs. The GSEA analysis implied that high expression of LINC01018, SMIM25, and CHL1, and low expression of hsa-miR-182-5p would activate inflammation-related pathways in endometriosis EU samples. LINC01018 and SMIM25 might sponge hsa-miR-182-5p to upregulate downstream genes such as CHL1 to promote the development of endometriosis.

scholarly journals Blood Transcriptome Profiling Reveals Diet-Induced Changes in Metabolic Pathway Gene Expression

2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 938-938
Author(s):  
Jaapna Dhillon ◽  
Jose Godoy-Lugo ◽  
Rudy Ortiz
Keyword(s):  
Gene Expression ◽  
Young Adults ◽  
Signal Transduction Pathway ◽  
Enrichment Analysis ◽  
Immunoglobulin Superfamily ◽  
Pathway Enrichment Analysis ◽  
Sequencing Data ◽  
P Values ◽  
Pathway Gene ◽  
Blood Transcriptome

Abstract Objectives This study explored the effects of diet-induced (almonds vs. crackers) changes on blood transcriptome profiles of young adults. Methods Young adults (age: 18–22 years) were randomly assigned to consume either almonds (2 oz./d, n = 13) or an isocaloric control snack of graham crackers (325 kcal/d, n = 10) daily for 4 weeks. Blood samples were collected at baseline and 4 weeks after intervention. Total leukocyte RNA was extracted and sequenced. Gene expression profiling was carried out using a 3′ Tag-RNA-Seq protocol. Barcoded sequencing libraries were prepared using the QuantSeq FWD kit for multiplexed sequencing. Data were preprocessed, STAR aligned, and count tables generated using the QuantSeq FWD-UMI pipeline. Differential expression (DE) analysis was conducted on the time x diet model using the limma-voom packages in R. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on the DE p-values was conducted using the Wilcoxon rank-sum test in R. P-values were adjusted for false discovery rate correction (FDR). Results Out of 13,018 filtered genes, 69 were differentially expressed (FDR < 0.1). Glutamic-oxaloacetic transaminase 2 (GOT2), diacylglycerol kinase alpha (DGKA), and glutaryl-CoA dehydrogenase (GCDH) genes were upregulated with almond consumption. GOT2 plays a role in amino acid metabolism and the urea and tricarboxylic acid cycles, DGKA is involved in lipid metabolism, and GCDH is involved in lysine degradation and tryptophan metabolism. Cracker consumption resulted in greater upregulation of TGF-beta activated kinase 1 gene (MAP3K7) binding protein 3 (TAB3) gene which is involved in the NF-kappaB signal transduction pathway and a greater downregulation in the immunoglobulin superfamily member 8 (IGSF8) gene. Enrichment analyses indicate gene annotations to 341 KEGG pathways. Thermogeneic and ribosomal pathways were significantly enriched (FDR < 0.1). Pathways related to oxidative phosphorylation, sphingolipid signaling, and tryptophan, propanoate, and starch and sucrose metabolism were also differentially enriched (P < 0.05, FDR < 0.3). Conclusions These findings indicate that diet (almond vs cracker) potentially alters metabolism through changes in gene transcription. The implications of these findings and associations with health and disease outcomes need to be investigated further. Funding Sources NIH

scholarly journals Identification of Potential Prognostic Competing Triplets in High-Grade Serous Ovarian Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Jian Zhao ◽  
Xiaofeng Song ◽  
Tianyi Xu ◽  
Qichang Yang ◽  
Jingjing Liu ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
High Throughput Sequencing ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Sequencing Data ◽  
P53 Signaling ◽  
Oocyte Meiosis ◽  
The Difference ◽  
Division Cell ◽  
The Impact

Increasing lncRNA-associated competing triplets were found to play important roles in cancers. With the accumulation of high-throughput sequencing data in public databases, the size of available tumor samples is becoming larger and larger, which introduces new challenges to identify competing triplets. Here, we developed a novel method, called LncMiM, to detect the lncRNA–miRNA–mRNA competing triplets in ovarian cancer with tumor samples from the TCGA database. In LncMiM, non-linear correlation analysis is used to cover the problem of weak correlations between miRNA–target pairs, which is mainly due to the difference in the magnitude of the expression level. In addition, besides the miRNA, the impact of lncRNA and mRNA on the interactions in triplets is also considered to improve the identification sensitivity of LncMiM without reducing its accuracy. By using LncMiM, a total of 847 lncRNA-associated competing triplets were found. All the competing triplets form a miRNA–lncRNA pair centered regulatory network, in which ZFAS1, SNHG29, GAS5, AC112491.1, and AC099850.4 are the top five lncRNAs with most connections. The results of biological process and KEGG pathway enrichment analysis indicates that the competing triplets are mainly associated with cell division, cell proliferation, cell cycle, oocyte meiosis, oxidative phosphorylation, ribosome, and p53 signaling pathway. Through survival analysis, 107 potential prognostic biomarkers are found in the competing triplets, including FGD5-AS1, HCP5, HMGN4, TACC3, and so on. LncMiM is available at https://github.com/xiaofengsong/LncMiM.

scholarly journals CYP1B1-AS1 Is a Novel Biomarker in Glioblastoma by Comprehensive Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Tao Ye ◽  
Lan-lan Li ◽  
Xue-mei Peng ◽  
Qin Li
Keyword(s):  
Mutual Effect ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Sequencing Data ◽  
Molecular Biomarker ◽  
Kaplan Meier ◽  
Cancer Types ◽  
Signal Path ◽  
Tumor Types ◽  
Spearman’S Correlation

Objective. Growing evidence shows that enhancer RNAs (eRNAs) are pivotal for tumor progression. In this research, our team aimed to identify the survival-related eRNAs and further explore their potential function in glioblastoma (GBM). Methods. RNA-sequencing data in 31 tumor types were acquired from TCGA datasets. The survival-related eRNAs were identified by the use of Kaplan-Meier survival analyses and Spearman’s correlation analyses. KEGG pathway enrichment analysis was completed to investigate the underlying signal paths of the critical eRNA. Pancancer assays were applied to explore the association between CYP1B1-AS1 and CYP1B1. Results. We identified 74 survival-related eRNAs and focused on CYP1B1-AS1 which displayed the greatest cor value. CYP1B1 was identified as a regulatory target of CYP1B1-AS1. KEGG analyses suggested that CYP1B1-AS1 might play an essential role through CK-CKR mutual effect, complement and coagulation cascades, TNF signal path, and JAK-STAT signal path. The pancancer verification outcomes revealed that CYP1B1-AS1 was related to survival in 4 cancers, i.e., LIHC, KIRP, KICH, and KIRC. Association was discovered between CYP1B1-AS1 and the targeted gene, CYP1B1, in 29 cancer types. Conclusion. The outcomes herein provided the first evidence that overexpression of CYP1B1-AS1 might be a potential molecular biomarker for predicting the prognosis of patients with GBM.

scholarly journals Comprehensive circRNA Expression Profile and Construction of circRNAs-Related ceRNA Network in a Mouse Model of Autism

2021 ◽  
Vol 11 ◽  
Author(s):  
Ji Wang ◽  
Zhongxiu Yang ◽  
Canming Chen ◽  
Yang Xu ◽  
Hongguang Wang ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Expression Profile ◽  
Enrichment Analysis ◽  
Notch Signaling Pathway ◽  
Mapk Signaling ◽  
Circular Rnas ◽  
Pathway Enrichment Analysis ◽  
Common Disease ◽  
Cerna Network

Autism is a common disease that seriously affects the quality of life. The role of circular RNAs (circRNAs) in autism remains largely unexplored. We aimed to detect the circRNA expression profile and construct a circRNA-based competing endogenous RNA (ceRNA) network in autism. Valproate acid was used to establish an in vivo model of autism in mice. A total of 1,059 differentially expressed circRNAs (477 upregulated and 582 downregulated) in autism group was identified by RNA sequencing. The expression of novel_circ_015779 and novel_circ_035247 were detected by real-time PCR. A ceRNA network based on altered circRNAs was established, with 9,715 nodes and 150,408 edges. Module analysis was conducted followed by GO and KEGG pathway enrichment analysis. The top three modules were all correlated with autism-related pathways involving “TGF-beta signaling pathway,” “Notch signaling pathway,” “MAPK signaling pathway,” “long term depression,” “thyroid hormone signaling pathway,” etc. The present study reveals a novel circRNA involved mechanisms in the pathogenesis of autism.

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