scholarly journals Construction and comprehensive analysis of a ceRNA network to reveal potential prognostic biomarkers for hepatocellular carcinoma

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Junyu Long ◽  
Yi Bai ◽  
Xiaobo Yang ◽  
Jianzhen Lin ◽  
Xu Yang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Comprehensive Analysis ◽  
Prognostic Biomarkers ◽  
Cerna Network

Effect of an lncRNA-associated ceRNA regulatory network in MVI-positive hepatocellular carcinoma on their sensitivity to sorafenib.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e16615-e16615
Author(s):  
Zhiwen Luo ◽  
Xinyu Bi
Keyword(s):  
Hepatocellular Carcinoma ◽  
Expression Profiles ◽  
Recurrence Risk ◽  
Vital Role ◽  
Prognostic Biomarkers ◽  
Protein Coding ◽  
Functional Roles ◽  
Cerna Network ◽  
Mirna Sponges ◽  
Regulate Protein

e16615 Background: Microvascular invasion (MVI) is a histological feature of hepatocellular carcinoma (HCC) related to aggressiveness. But different sensitivity to first line targeted drug, sorafenib, in MVI+ HCC has been observed. Long noncoding RNAs (lncRNAs) can act as microRNA (miRNA) sponges to regulate protein-coding gene expression; so lncRNAs are considered as a major part of competitive endogenous RNA (ceRNA) network and have attracted growing attention. We explored the regulatory mechanisms and functional roles of lncRNAs as ceRNAs in MVI+ HCC, and ceRNA network’s potential impact on prognosis and sensitivity to sorafenib in MVI+ HCC patient. Methods: We studied the expression profiles, prognostic value of lncRNA, miRNA, and mRNA from MVI+ HCC patients, established a prognosis-related network of dysregulated ceRNAs and analyzed its role in sensitivity to sorafenib and radiomics features by bioinformatics methods. Results: A ceRNA network including 13 lncRNAs, 3 miRNAs, and 2 mRNAs specific to MVI+ HCC was established. 6 lncRNAs ( ARHGEF7-AS1, ATP2B2-IT1, LINC00330, MUC2, TLR8-AS1 and ZNF385D-AS1), 2 miRNAs ( hsa-mir-206 and hsa-mir-373) and two mRNAs ( PAX3, SIK1) were prognostic biomarkers for MVI+ HCC. PAX3 was an unfavorable prognostic gene (HR = 1.9, 95%CI 1.01 ~ 3.60), while SIK1 favored the prognosis (HR = 0.4, 95%CI 0.19 ~ 0.85). PAX3 as a stratification in recurrence predicting model was used to identify MVI+ HCC with high or low recurrence risk. Datamining into the dataset of phase 3 STORM trial showed no difference in the influence of PAX3 level on the outcome between sorafenib HCC group and placebo HCC group. However, deep datamining into GDSC dataset revealed our high PAX3 group in MVI+ HCC related to resistance to sorafenib ( P = 0.0039). Radiomics features were extracted from CT of MVI+ HCC, and texture analysis in MVI+ HCCs is ongoing. Conclusions: The proposed ceRNA network may help elucidate the regulatory mechanism by which lncRNAs function as ceRNAs and contribute to the pathogenesis of MVI in HCC. Importantly, the candidate lncRNAs, miRNAs, and mRNAs involved in the ceRNA network have shown to be potential therapeutic targets and prognostic biomarkers for MVI+ HCC. PAX3 might play a vital role in the mechanism of sorafenib resistance in MVI+ HCC, exclusively, this aggressive HCC subtype. The ongoing experiments on radiomics might add potent supports to identify sorafenib sensitive MVI+ HCC.

scholarly journals Identification of Prognostic Biomarkers and Correlation With Immune Infiltrates in Hepatocellular Carcinoma Based on a Competing Endogenous RNA Network

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhangya Pu ◽  
Yuanyuan Zhu ◽  
Xiaofang Wang ◽  
Yun Zhong ◽  
Fang Peng ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cells ◽  
Survival Analysis ◽  
Immune Cell ◽  
Cox Regression ◽  
Quantitative Polymerase Chain Reaction ◽  
Prognostic Biomarkers ◽  
Hub Genes ◽  
Immune Infiltration ◽  
Cerna Network

BackgroundHepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide. Recently, competing endogenous RNAs (ceRNA) have revealed a significant role in the progression of HCC. Herein, we aimed to construct a ceRNA network to identify potential biomarkers and illustrate its correlation with immune infiltration in HCC.MethodsRNA sequencing data and clinical traits of HCC patients were downloaded from TCGA. The limma R package was used to identify differentially expressed (DE) RNAs. The predicted prognostic model was established using univariate and multivariate Cox regression. A K-M curve, TISIDB and GEPIA website were utilized for survival analysis. Functional annotation was determined using Enrichr and Reactome. Protein-to-protein network analysis was implemented using SRTNG and Cytoscape. Hub gene expression was validated by quantitative polymerase chain reaction, Oncomine and the Hunan Protein Atlas database. Immune infiltration was analyzed by TIMMER, and Drugbank was exploited to identify bioactive compounds.ResultsThe predicted model that was established revealed significant efficacy with 3- and 5-years of the area under ROC at 0.804 and 0.744, respectively. Eleven DEmiRNAs were screened out by a K-M survival analysis. Then, we constructed a ceRNA network, including 56 DElncRNAs, 6 DEmiRNAs, and 28 DEmRNAs. The 28 DEmRNAs were enriched in cancer-related pathways, for example, the TNF signaling pathway. Moreover, six hub genes, CEP55, DEPDC1, KIF23, CLSPN, MYBL2, and RACGAP1, were all overexpressed in HCC tissues and independently correlated with survival rate. Furthermore, expression of hub genes was related to immune cell infiltration in HCC, including B cells, CD8+ T cells, CD4+ T cells, monocytes, macrophages, neutrophils, and dendritic cells.ConclusionThe findings from this study demonstrate that CEP55, DEPDC1, KIF23, CLSPN, MYBL2, and RACGAP1 are closely associated with prognosis and immune infiltration, representing potential therapeutic targets or prognostic biomarkers in HCC.

scholarly journals Comprehensive analysis of TPX2-related ceRNA network as prognostic biomarkers in lung adenocarcinoma

2020 ◽  
Vol 17 (16) ◽  
pp. 2427-2439
Author(s):  
Chen Huo ◽  
Meng-Yu Zhang ◽  
Rui Li ◽  
Xi-Jia Zhou ◽  
Ting-Ting Liu ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Comprehensive Analysis ◽  
Prognostic Biomarkers ◽  
Cerna Network

scholarly journals Identification of Prognostic Biomarkers and Correlation with Immune Infiltrates in Hepatocellular Carcinoma Based on a Competing Endogenous RNA Network

2020 ◽  
Author(s):  
Zhangya Pu ◽  
Yuanyuan Zhu ◽  
Xiaofang Wang ◽  
Yun Zhong ◽  
Fang Peng ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cells ◽  
Survival Analysis ◽  
Immune Cell ◽  
Cox Regression ◽  
Malignant Tumors ◽  
Prognostic Biomarkers ◽  
Hub Genes ◽  
Immune Infiltration ◽  
Cerna Network

Abstract Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide. Recently, competing endogenous RNAs (ceRNA) have revealed a significant role in the progression of HCC. Herein, we aimed to construct a ceRNA network to identify potential biomarkers and illustrate its correlation with immune infiltration in HCC. Methods: RNA sequencing data and clinical traits of HCC patients were downloaded from TCGA. The limma R package was used to identify differentially expressed (DE) RNAs. The predicted prognostic model was established using univariate and multivariate Cox regression. A K-M curve and GEPIA website were utilized for survival analysis. Functional annotation was determined using Enrichr and Reactome. Protein-to-protein network analysis was implemented using SRTNG and Cytoscape. Hub gene expression was validated by Oncomine and the Hunan Protein Atlas database. Immune infiltration was analyzed by TIMMER, and Drugbank was exploited to identify bioactive compounds. Results: The predicted model that was established revealed significant efficacy with 3- and 5-years of the area under ROC at 0.804 and 0.744, respectively. Eleven DEmiRNAs were screened out by a K-M survival analysis. Then, we constructed a ceRNA network, including 56 DElncRNAs, 6 DEmiRNAs, and 28 DEmRNAs. The 28 DEmRNAs were enriched in cancer-related pathways, for example, the TNF signaling pathway. Moreover, six hub genes, CEP55, DEPDC1, KIF23, CLSPN, MYBL2, and RACGAP1, were all overexpressed in HCC tissues and independently correlated with survival rate. Furthermore, expression of hub genes was related to immune cell infiltration in HCC, including B cells, CD8 + T cells, CD4 + T cells, monocytes, macrophages, neutrophils, and dendritic cells. Conclusions: The findings from this study demonstrate that CEP55, DEPDC1, KIF23, CLSPN, MYBL2, and RACGAP1 are closely associated with prognosis and immune infiltration, representing potential therapeutic targets or prognostic biomarkers in HCC.

LINC00152 drives a ceRNA network in human hepatocellular carcinoma

2020 ◽  
Author(s):  
R Pellegrino ◽  
F Ticconi ◽  
B Skawran ◽  
M Castoldi ◽  
P Schirmacher ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Human Hepatocellular Carcinoma ◽  
Cerna Network

scholarly journals Transcript levels of spindle and kinetochore-associated complex 1/3 as prognostic biomarkers correlated with immune infiltrates in hepatocellular carcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
De-Chen Yu ◽  
Xiang-Yi Chen ◽  
Xin Li ◽  
Hai-Yu Zhou ◽  
De-Quan Yu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Protein Complex ◽  
Immune Cell ◽  
Prognostic Significance ◽  
Tumor Development ◽  
Disease Free Survival ◽  
Tumor Grade ◽  
Tumor Stage ◽  
Prognostic Biomarkers ◽  
High Expression

AbstractThe spindle and kinetochore-associated protein complex (Ska) is an essential component in chromosome segregation. It comprises three proteins (Ska1, Ska2, and Ska3) with theorized roles in chromosomal instability and tumor development, and its overexpression has been widely reported in a variety of tumors. However, the prognostic significance and immune infiltration of Ska proteins in hepatocellular carcinoma (HCC) are not completely understood. The bioinformatics tools Oncomine, UALCAN, gene expression profiling interactive analysis 2 (GEPIA2), cBioPortal, GeneMANIA, Metascape, and TIMER were used to analyze differential expression, prognostic value, genetic alteration, and immune cell infiltration of the Ska protein complex in HCC patients. We found that the mRNA expression of the Ska complex was markedly upregulated in HCC. High expression of the Ska complex is closely correlated with tumor stage, patient race, tumor grade, and TP53 mutation status. In addition, high expression of the Ska complex was significantly correlated with poor disease-free survival, while the high expression levels of Ska1 and Ska3 were associated with shorter overall survival. The biological functions of the Ska complex in HCC primarily involve the amplification of signals from kinetochores, the mitotic spindle, and (via a MAD2 invasive signal) unattached kinetochores. Furthermore, the expression of the complex was positively correlated with tumor-infiltrating cells. These results may provide new insights into the development of immunotherapeutic targets and prognostic biomarkers for HCC.

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