Construction of a ceRNA network and a genomic-clinicopathologic nomogram to predict survival for HBV-related HCC.

Some lncRNA-associated competing endogenous RNAs (ceRNAs) are considered as potential biomarkers for targeted therapies and prognosis in human cancer. In our present study, we aimed to construct a ceRNA network and establish a genomic-clinicopathologic nomogram to provide insights into the molecular mechanisms and predict survival for HBV-related HCC. The Cancer Genome Atlas (TCGA) database was applied to collect the data of LIHC RNA-seq dataset and miRNA-seq dataset as well as the clinicopathological information. Identification of differentially expressed RNAs (mRNAs, lncRNAs, and miRNAs) between HBV-related HCC samples and normal samples was conducted using Limma package in R. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used for performing the functional enrichment analysis of differentially expressed mRNAs. The ceRNA network was carried out using Cytoscape. The LASSO-penalized Cox regression analysis was implemented to identify HCC-related lncRNAs, and the multivariate Cox regression analysis was conducted for the establishment of a genomic-clinicopathology nomogram. A total of 1859 DEmRNAs, 113 DElncRNAs, and 89 DEmiRNAs were screened out etween HBV-related HCC samples and normal samples. A ceRNA network including 44 DEmRNAs, 7 DElncRNAs, and 20 DEmiRNAs was constructed. 7 DElncRNAs (PVT1, LINC01138, LINC02499, AL355488.2, FGF14-AS2, MAFG-AS1 and LINC00261) were finally identified as prognostic indicators. The area under the curve reached 0.8169 for the 7-lncRNA signature. The predictive accuracy and clinical application value were remarkably high for the genomic-clinicopathologic nomogram integrating the histological grade and the 7-gene-based prognostic index. Taken together, we have established a ceRNA network with HBV-related HCC-specific DElncRNAs, DEmiRNAs, and DEmRNAs. Furthermore, the genome-wide data of lncRNA expression were analyzed using the TCGA database, and a 7-lncRNA signature was identified as a potential prognostic predictor for HBV-related HCC patients. Novel functional studies were provided by our current findings for elucidating the molecular mechanism of lncRNA in HBV-related HCC.

Huang K ，Lu Z ，Li L ，Peng G ，Zhou W ，Ye Q ... -  《Human Cell》

Screening Prognosis-Related lncRNAs Based on WGCNA to Establish a New Risk Score for Predicting Prognosis in Patients with Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) remains an important cause of cancer death. The molecular mechanism of hepatocarcinogenesis and prognostic factors of HCC have not been completely uncovered. In this study, we screened out differentially expressed lncRNAs (DE lncRNAs), miRNAs (DE miRNAs), and mRNAs (DE mRNAs) by comparing the gene expression of HCC and normal tissue in The Cancer Genome Atlas (TCGA) database. DE mRNAs were used to perform Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Then, the miRNA and lncRNA/mRNA modules that were most closely related to the survival time of patients with HCC were screened to construct a competitive endogenous RNA (ceRNA) network by weighted gene coexpression network analysis (WGCNA). Moreover, univariable Cox regression and Kaplan-Meier curve analyses of DE lncRNAs and DE mRNAs were conducted. Finally, the lasso-penalized Cox regression analysis and nomogram model were used to establish a new risk scoring system and predict the prognosis of patients with liver cancer. The expression of survival-related DE lncRNAs was verified by qRT-PCR. A total of 1896 DEmRNAs, 330 DElncRNAs, and 76 DEmiRNAs were identified in HCC and normal tissue samples. Then, the turquoise miRNA and turquoise lncRNA/mRNA modules that were most closely related to the survival time of patients with HCC were screened to construct a ceRNA network by WGCNA. In this ceRNA network, there were 566 lncRNA-miRNA-mRNA regulatory pairs, including 30 upregulated lncRNAs, 16 downregulated miRNAs, and 75 upregulated mRNAs. Moreover, we screened out 19 lncRNAs and 14 hub mRNAs related to prognosis from this ceRNA network by univariable Cox regression and Kaplan-Meier curve analyses. Finally, a new risk scoring system was established by selecting the optimal risk lncRNAs from the 19 prognosis-related lncRNAs through lasso-penalized Cox regression analysis. In addition, we established a nomogram model consisting of independent prognostic factors to predict the survival rate of HCC patients. Finally, the correlation between the risk score and immune cell infiltration and gene set enrichment analysis were determined. In conclusion, the results may provide potential biomarkers or therapeutic targets for HCC and the establishment of the new risk scoring system and nomogram model provides the new perspective for predicting the prognosis of HCC.

Zhou X ，Dou M ，Liu Z ，Jiao D ，Li Z ，Chen J ，Li J ，Yao Y ，Li L ，Li Y ，Han X ... -  《-》

Construction of a disease-specific lncRNA-miRNA-mRNA regulatory network reveals potential regulatory axes and prognostic biomarkers for hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a heterogeneous malignancy with a high incidence and poor prognosis. Exploration of the underlying mechanisms and effective prognostic indicators is conducive to clinical management and optimization of treatment. The RNA-seq and clinical phenotype data of HCC were retrieved from The Cancer Genome Atlas (TCGA), and differential expression analysis was performed. Then, a differential lncRNA-miRNA-mRNA regulatory network was constructed, and the key genes were further identified and validated. By integrating this network with the online tool-based ceRNA network, an HCC-specific ceRNA network was obtained, and lncRNA-miRNA-mRNA regulatory axes were extracted. RNAs associated with prognosis were further obtained, and multivariate Cox regression models were established to identify the prognostic signature and nomogram. As a result, 198 DElncRNAs, 120 DEmiRNAs, and 2827 DEmRNAs were identified, and 30 key genes identified from the differential network were enriched in four cancer-related pathways. Four HCC-specific lncRNA-miRNA-mRNA regulatory axes were extracted, and SNHG11, CRNDE, MYLK-AS1, E2F3, and CHEK1 were found to be related with HCC prognosis. Multivariate Cox regression analysis identified a prognostic signature, comprised of CRNDE, MYLK-AS1, and CHEK1, for overall survival (OS) of HCC. A nomogram comprising the prognostic signature and pathological stage was established and showed some net clinical benefits. The AUC of the prognostic signature and nomogram for 1-year, 3-year, and 5-year survival was 0.777 (0.657-0.865), 0.722 (0.640-0.848), and 0.630 (0.528-0.823), and 0.751 (0.664-0.870), 0.773 (0.707-0.849), and 0.734 (0.638-0.845), respectively. These results provided clues for the study of potential biomarkers and therapeutic targets for HCC. In addition, the obtained 30 key genes and 4 regulatory axes might also help elucidate the underlying mechanism of HCC.

Zhang Q ，Sun L ，Zhang Q ，Zhang W ，Tian W ，Liu M ，Wang Y ... -  《Cancer Medicine》

Reconstruction and Analysis of the Differentially Expressed IncRNA-miRNA-mRNA Network Based on Competitive Endogenous RNA in Hepatocellular Carcinoma.

Cao D ，Wang Y ，Li D ，Wang L ... -  《CRITICAL REVIEWS IN EUKARYOTIC GENE EXPRESSION》

Systematic analysis of lncRNA-miRNA-mRNA competing endogenous RNA network identifies four-lncRNA signature as a prognostic biomarker for breast cancer.

Fan CN ，Ma L ，Liu N 《Journal of Translational Medicine》