Identification of circular RNA–microRNA–messenger RNA regulatory network in hepatocellular carcinoma by integrated analysis

2019 ◽  
Vol 35 (1) ◽  
pp. 157-164 ◽  
Author(s):  
Xiangjun Sun ◽  
Xinfeng Ge ◽  
Zhiyong Xu ◽  
Dongfeng Chen
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regulatory Network ◽  
Messenger Rna ◽  
Circular Rna ◽  
Integrated Analysis

scholarly journals Identification of Circular RNA-MicroRNA-Messenger RNA Regulatory Network in Atrial Fibrillation by Integrated Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Tao Liu ◽  
Guoru Zhang ◽  
Yaling Wang ◽  
Mingyue Rao ◽  
Yang Zhang ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Regulatory Network ◽  
Messenger Rna ◽  
Noncoding Rna ◽  
Expression Profiles ◽  
Arrhythmogenic Right Ventricular Cardiomyopathy ◽  
Circular Rna ◽  
Host Gene ◽  
Differentially Expressed ◽  
Integrated Analysis

Background. Circular RNA (circRNA) is a noncoding RNA that forms a closed-loop structure, and its abnormal expression may cause disease. We aimed to find potential network for circRNA-related competitive endogenous RNA (ceRNA) in atrial fibrillation (AF). Methods. The circRNA, miRNA, and mRNA expression profiles in the heart tissue from AF patients were retrieved from the Gene Expression Omnibus database and analyzed comprehensively. Differentially expressed circRNAs (DEcircRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed mRNAs (DEmRNAs) were identified, followed by the establishment of DEcircRNA-DEmiRNA-DEmRNA regulatory network. Functional annotation analysis of host gene of DEcircRNAs and DEmRNAs in ceRNA regulatory network was performed. In vitro experiment and electronic validation were used to validate the expression of DEcircRNAs, DEmiRNAs, and DEmRNAs. Results. A total of 1611 DEcircRNAs, 51 DEmiRNAs, and 1250 DEmRNAs were identified in AF. The DEcircRNA-DEmiRNA-DEmRNA network contained 62 circRNAs, 14 miRNAs, and 728 mRNAs. Among which, two ceRNA regulatory pairs of hsa-circRNA-100053-hsa-miR-455-5p-TRPV1 and hsa-circRNA-005843-hsa-miR-188-5p-SPON1 were identified. In addition, six miRNA-mRNA regulatory pairs including hsa-miR-34c-5p-INMT, hsa-miR-1253-DDIT4L, hsa-miR-508-5p-SMOC2, hsa-miR-943-ACTA1, hsa-miR-338-3p-WIPI1, and hsa-miR-199a-3p-RAP1GAP2 were also obtained. MTOR was a significantly enriched signaling pathway of host gene of DEcircRNAs. In addition, arrhythmogenic right ventricular cardiomyopathy, dilated cardiomyopathy, and hypertrophic cardiomyopathy were remarkably enriched signaling pathways of DEmRNAs in DEcircRNA-DEmiRNA-DEmRNA regulatory network. The expression validation of hsa-circRNA-402565, hsa-miR-34c-5p, hsa-miR-188-5p, SPON1, DDIT4L, SMOC2, and WIPI1 was consistent with the integrated analysis. Conclusion. We speculated that hsa-circRNA-100053-hsa-miR-455-5p-TRPV1 and hsa-circRNA-005843-hsa-miR-188-5p-SPON1 interaction pairs may be involved in AF.

scholarly journals Analysis and Validation of circRNA-miRNA Network in Regulating m6A RNA Methylation Modulators Reveals CircMAP2K4/miR-139-5p/YTHDF1 Axis Involving the Proliferation of Hepatocellular Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Fanwu Chi ◽  
Yong Cao ◽  
Yuhan Chen
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regulatory Network ◽  
Excision Repair ◽  
Circular Rna ◽  
Gene Expression Omnibus ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Mechanism Study ◽  
Rna Methylation

The m6A RNA methylation modulators play a crucial role in regulating hepatocellular carcinoma (HCC) progression. The circular RNA (circRNA) regulatory network in regulating m6A RNA methylation modulators in HCC remains largely unknown. In this study, 5 prognostic m6A RNA methylation modulators in HCC were identified from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) projects. The differentially expressed microRNAs (DEmiRNAs) and circRNAs (DEcircRNAs) between paired tumor and normal tissues were screened out from TCGA and or Gene Expression Omnibus (GEO) database to construct the circRNA-miRNA- m6A RNA methylation modulator regulatory network, which included three m6A RNA methylation modulators (HNRNPC, YTHDF1, and YTHDF2), 11 DEmiRNAs, and eight DEcircRNAs. Among the network, hsa-miR-139-5p expression was negatively correlated with YTHDF1. Hsa-miR-139-5p low or YTHDF1 high expression was correlated with high pathological grade, advanced stage and poor survival of HCC. Additionally, cell cycle, base excision repair, and homologous recombination were enriched in YTHDF1 high expression group by GSEA. A hub circRNA regulatory network was constructed based on hsa-miR-139-5p/YTHDF1 axis. Furthermore, hsa_circ_0007456(circMAP2K4) was validated to promote HCC cell proliferation by binding with hsa-miR-139-5p to promote YTHDF1 expression. Taken together, we identified certain circRNA regulatory network related to m6A RNA methylation modulators and provided clues for mechanism study and therapeutic targets for HCC.

scholarly journals Identification and integrated analysis of hepatocellular carcinoma-related circular RNA signature

2020 ◽  
Vol 8 (6) ◽  
pp. 294-294
Author(s):  
Feiran Wang ◽  
Xiaodong Xu ◽  
Nannan Zhang ◽  
Zhong Chen
Keyword(s):  
Hepatocellular Carcinoma ◽  
Circular Rna ◽  
Integrated Analysis ◽  
Rna Signature

scholarly journals RNA sequencing analysis reveals the competing endogenous RNAs interplay in resected hepatocellular carcinoma patients who received interferon-alpha therapy

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yibin Wu ◽  
Longrong Wang ◽  
Xiaoshuang Wang ◽  
Yiming Zhao ◽  
Anrong Mao ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Interferon Alpha ◽  
Immune Cells ◽  
Regulatory Network ◽  
Circular Rna ◽  
Sequencing Analysis ◽  
Significant Differential Expression ◽  
Gene Markers ◽  
Cerna Network ◽  
Competing Endogenous Rnas

Abstract Background Interferon-alpha (IFN-α) is a general therapeutic regimen to be utilized in hepatocellular carcinoma (HCC). However, regulatory mechanisms of IFN-α on competing endogenous RNAs (ceRNAs) level in anti-HCC relapse are rarely understood. Methods HCC patients with and without IFN-α treatment were calculated to analyze the expression profile of mRNA, long non-coding RNA (lncRNA), microRNA (miRNA), and circular RNA (circRNA) by RNA sequence, and significant differential expression (DE) of these types of RNAs were selected for further analysis. A ceRNA regulatory network was constructed to explore the potential mechanisms of IFN-α intervention on anti-HCC relapse. Finally, the potential prognostic associated genes among these DE RNAs were identified. Results Totally, 556 mRNAs, 120 circRNAs, 87 lncRNAs, and 96 miRNAs were differentially expressed in patients who received IFN-α treatment. A ceRNA regulatory network including a circRNA-miRNA-mRNA network which composed of 4 up- and 10 down-regulated circRNAs, 8 up- and 5 down-regulated miRNAs, 28 up- and 9 down-regulated mRNAs, and a lncRNA-miRNA-mRNA network which composed of 10 up- and 3 down-regulated lncRNAs, 11 up- and 5 down-regulated miRNAs, 28 up- and 10 down-regulated mRNAs was constructed. Gene enrichment and pathway analysis revealed that the ceRNA network was associated with immune-related pathway and corresponding molecular function in patients who accepted IFN-α treatment. Next, we identified 3 most relevant to IFN-α treatment to HCC among these DE RNAs, namely FAM20A, IGFBP4 and MARCH3, as the prognostic associated genes for HCC. Furthermore, MARCH3 expression correlated with infiltrating levels of tumor infiltrating immune cells (TICCs) in HCC. MARCH3 expression also showed strong correlations with the gene markers of diverse immune cells in HCC. Conclusion Our data discovered a novel ceRNA network in HCC patients receiving IFN-α therapy, which might lay the foundation for better understand the regulatory mechanism of IFN-α treatment.

scholarly journals Integrated analysis of methylation-driven genes and pretreatment prognostic factors in patients with hepatocellular carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Dongsheng He ◽  
Shengyin Liao ◽  
Lifang Cai ◽  
Weiming Huang ◽  
Xuehua Xie ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Prognostic Factors ◽  
Risk Score ◽  
Prognostic Model ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Integrated Analysis ◽  
Calibration Plot ◽  
Clinical Parameters ◽  
T Stage

Abstract Background The potential reversibility of aberrant DNA methylation indicates an opportunity for oncotherapy. This study aimed to integrate methylation-driven genes and pretreatment prognostic factors and then construct a new individual prognostic model in hepatocellular carcinoma (HCC) patients. Methods The gene methylation, gene expression dataset and clinical information of HCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Methylation-driven genes were screened with a Pearson’s correlation coefficient less than − 0.3 and a P value less than 0.05. Univariable and multivariable Cox regression analyses were performed to construct a risk score model and identify independent prognostic factors from the clinical parameters of HCC patients. The least absolute shrinkage and selection operator (LASSO) technique was used to construct a nomogram that might act to predict an individual’s OS, and then C-index, ROC curve and calibration plot were used to test the practicability. The correlation between clinical parameters and core methylation-driven genes of HCC patients was explored with Student’s t-test. Results In this study, 44 methylation-driven genes were discovered, and three prognostic signatures (LCAT, RPS6KA6, and C5orf58) were screened to construct a prognostic risk model of HCC patients. Five clinical factors, including T stage, risk score, cancer status, surgical method and new tumor events, were identified from 13 clinical parameters as pretreatment-independent prognostic factors. To avoid overfitting, LASSO analysis was used to construct a nomogram that could be used to calculate the OS in HCC patients. The C-index was superior to that from previous studies (0.75 vs 0.717, 0.676). Furthermore, LCAT was found to be correlated with T stage and new tumor events, and RPS6KA6 was found to be correlated with T stage. Conclusion We identified novel therapeutic targets and constructed an individual prognostic model that can be used to guide personalized treatment in HCC patients.

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