scholarly journals Integrated analysis of competing endogenous RNA network revealing potential prognostic biomarkers of hepatocellular carcinoma

2019 ◽  
Vol 10 (14) ◽  
pp. 3267-3283 ◽  
Author(s):  
Xiwen Liao ◽  
Xiangkun Wang ◽  
Ketuan Huang ◽  
Chuangye Han ◽  
Jianlong Deng ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Prognostic Biomarkers ◽  
Integrated Analysis ◽  
Competing Endogenous Rna ◽  
Competing Endogenous Rna Network

Competing endogenous RNA network and prognostic nomograms for hepatocellular carcinoma patients who underwent R0 resection

2019 ◽  
Vol 234 (11) ◽  
pp. 20342-20353 ◽  
Author(s):  
Yuntong Li ◽  
Bingfen Ma ◽  
Zhenyu Yin ◽  
Pingguo Liu ◽  
Jianming Liu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
R0 Resection ◽  
Competing Endogenous Rna ◽  
Competing Endogenous Rna Network

scholarly journals Integrated analysis identifies a pathway-related competing endogenous RNA network in the progression of pancreatic cancer

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Fuqiang Zu ◽  
Peng Liu ◽  
Huaitao Wang ◽  
Ting Zhu ◽  
Jian Sun ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Tumor Formation ◽  
Functional Enrichment ◽  
Integrated Analysis ◽  
Competing Endogenous Rna ◽  
Hub Genes ◽  
Cerna Network ◽  
Competing Endogenous Rna Network

Abstract Background It is well acknowledged that cancer-related pathways play pivotal roles in the progression of pancreatic cancer (PC). Employing Integrated analysis, we aim to identify the pathway-related ceRNA network associated with PC progression. Methods We divided eight GEO datasets into three groups according to their platform, and combined TCGA and GTEx databases as a group. Additionally, we screened out the differentially expressed genes (DEGs) and performed functional enrichment analysis in each group, and recognized the top hub genes in the most enriched pathway. Furthermore, the upstream of miRNAs and lncRNAs were predicted and validated according to their expression and prognostic roles. Finally, the co-expression analysis was applied to identify a pathway-related ceRNA network in the progression of PC. Results A total of 51 significant pathways that common enriched in all groups were spotted. Enrichment analysis indicated that pathway in cancer was greatly linked with tumor formation and progression. Next, the top 20 hug genes in this pathway were recognized, and stepwise prediction and validation from mRNA to lncRNA, including 11 hub genes, 4 key miRNAs, and 2 key lncRNAs, were applied to identify a meaningful ceRNA network according to ceRNA rules. Ultimately, we identified the PVT1/miR-20b/CCND1 axis as a promising pathway-related ceRNA axis in the progression of PC. Conclusion Overall, we elucidate the pathway-related ceRNA regulatory network of PVT1/miR-20b/CCND1 in the progression of PC, which can be considered as therapeutic targets and encouraging prognostic biomarkers for PC.

scholarly journals Competing endogenous RNA network: Potential entrants to gene editing in Hepatocellular Carcinoma Gene editing of ceRNA in Hepatocellular Carcinoma

2018 ◽  
Author(s):  
Ayman El-Sayed Shafei ◽  
Marwa Matboli ◽  
Mahmoud A. Ali ◽  
Ziad Nagy ◽  
Maged Reda ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Line ◽  
Hepg2 Cell ◽  
In Silico ◽  
Gene Editing ◽  
Hepg2 Cell Line ◽  
Competing Endogenous Rna ◽  
Competing Endogenous Rna Network ◽  
Synthetic Circuit ◽  
Polymerase Chain

AbstractBackgroundHepatocellular Carcinoma (HCC) is the leading cause of cancer deaths worldwide as well as in Egypt. We aimed to use Clustered Regulatory Interspaced Short Palindromic Repeats (CRISPR) gene editing technique to induce forced down-regulation of the circRNA which consequently modified miRNA expression in HepG2 cell line to prove the regulatory relationship between the RNA parts of an in silico-detected competing endogenous RNA network in HCCMethodWe first retrieved hsa_circ_0000064-miR-1285-TRIM2 mRNA from public microarray databases followed by in silico modelling to mimic the regulation kinetics of cirRNA associated ceRNA network. Secondly, we performed polymerase chain reaction (PCR)-based amplification of synthetic fragments, Gibson assembly of both CRISPR and non CRISPR based circuits, E-coli transformation, plasmid purification, HePG2 cell line transfection. Finally Expression levels of the chosen RNAs in hepatocellular carcinoma (HCC) cell line, HepG2, were examined by quantitative reverse transcription polymerase chain reaction (qRT-PCR) and the cytotoxic effect was validated by viability assay.TRIM2 protein expression was proved by immunohistochemistry and flowcytometry.ResultsInduction of hsa_circ_0000064 into HepG2 cell line via CRISPR-and non-CRISPR mediated synthetic circuit resulted in statistically significant decrease in cell number and, then, cellular viability with marked increase in hsa_circ_0000064 and TRIM2 mRNA levels and concomitant decrease in miR-1285 expression in HepG2 cell line compared with control (p<0.0). Moreover exogenous expression of hsa_circ_0000064 in HepG2 cell line showed increased expression of the tumor suppressor protein, TRIM2.ConclusionsOur integrative approach, including in silico data analysis and experimental validation proved that CRISPR-mediated synthetic circuit-based overexpression of hsa_circ_0000064 was more efficient than conventional transient transfection, representing a promising therapeutic strategy for HCC.Data AvailabilityOur Data was made available online on the IGEM wiki of team AFCM-EGYPT:http://2017.igem.org/Team:AFCM-Egypt. Synthetic parts have been submitted to IGEM Parts Registry.Financial DisclosureThe project was funded by Armed Forces College of Medicine AFCM, Zewail City of Science and Technology, National Research Center NRC, VitaBiotics, PHARCO Pharmaceuticals, Sim Era and DANUB Paintings. IDT provided 20 kb of DNA synthesis. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

scholarly journals Integrated analysis identifies a pathway-related competing endogenous RNA network in the progression of Pancreatic cancer

2020 ◽  
Author(s):  
Fuqiang Zu ◽  
Peng Liu ◽  
Huaitao Wang ◽  
Ting Zhu ◽  
Jian Sun ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Tumor Formation ◽  
Functional Enrichment ◽  
Integrated Analysis ◽  
Competing Endogenous Rna ◽  
Hub Genes ◽  
Cerna Network ◽  
Competing Endogenous Rna Network

Abstract Background: It is well acknowledged that cancer-related pathways play pivotal roles in the progression of pancreatic cancer (PC). Employing Integrated analysis, we aim to identify the pathway-related ceRNA network associated with PC progression.Methods: We divided eight GEO datasets into three groups according to their platform, and combined TCGA and GTEx databases as a group. Additionally, we screened out the differentially expressed genes (DEGs) and performed functional enrichment analysis in each group, and recognized the top hub genes in the most enriched pathway. Furthermore, the upstream of miRNAs and lncRNAs were predicted and validated according to their expression and prognostic roles. Finally, the co-expression analysis was applied to identify a pathway-related ceRNA network in the progression of PC.Results: A total of 51 significant pathways that common enriched in all groups were spotted. Enrichment analysis indicated that pathway in cancer was greatly linked with tumor formation and progression. Next, the top 20 hug genes in this pathway were recognized, and stepwise prediction and validation from mRNA to lncRNA, including 11 hub genes, 4 key miRNAs, and 2 key lncRNAs, were applied to identify a meaningful ceRNA network according to ceRNA rules. Ultimately, we identified the PVT1/miR-20b-/CCND1 axis as a promising pathway-related ceRNA axis in the progression of PC.Conclusion: Overall, we elucidate the pathway-related ceRNA regulatory network of PVT1/miR-20b-/CCND1 in the progression of PC, which can be considered as therapeutic targets and encouraging prognostic biomarkers for PC.

scholarly journals Identification of a Competing Endogenous RNA Network Related to Immune Signature in Lung Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Ting Zhu ◽  
Yong Yu ◽  
Jun Liu ◽  
Kaiming Ren
Keyword(s):  
Immune Responses ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Competing Endogenous Rna ◽  
Hub Genes ◽  
New Era ◽  
Immune Signature ◽  
Cerna Network ◽  
Competing Endogenous Rna Network ◽  
Immune Related Genes

BackgroundThe establishment of immunotherapy has led to a new era in oncotherapy. But the signature of immune-related genes (IRGs) in LUAD remains to be elucidated. Here we use integrated analysis to identify IRGs roles in immune signature and detect their relationship with competing endogenous RNA (ceRNA) networks in LUAD progression.MethodsBy analyzing the RNA-seq data from different platforms, we recognized the differentially expressed genes (DEGs) of each platform and screened out the top 20 hub IRGs related to immune responses. Then, we applied the CIBERSORT algorithm to explore the landscape of tumor-infiltrating immune cells (TILs) in LUAD and their connection with hub genes. Next, we predicted and validated the upstream miRNAs and lncRNAs according to their expression and prognostic roles. Finally, we constructed and validated an immune-related ceRNA network by co-expression analysis.ResultsA total of 71 IRGs were identified among 248 DEGs, which play key roles in immune responses. CIBERSORT analysis showed that six hub genes were closely related to TILs, such as SPP1 and naive B cells (R = −0.17), TEK and resting mast cells (R = 0.37). Stepwise prediction and validation from mRNA to lncRNA, including 6 hub genes, 5 miRNAs, and 9 lncRNAs, were applied to construct a ceRNA network. Ultimately, we confirmed the TMPO-AS1/miR-126-5p/SPP1 and CARD8-AS1/miR-21-5p/TEK as immune-related ceRNA networks in LUAD progression.ConclusionWe elucidated two immune-related ceRNA networks in LUAD progression, which can be considered as immunotherapy targets for this disease.

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