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Objective: The goal of our study is to identify a competing endogenous RNA (ceRNA) network using dysregulated RNAs between HCC tumors and the adjacent normal liver tissues from The Cancer Genome Atlas (TCGA) datasets, and to investigate underlying prognostic indicators in hepatocellular carcinoma (HCC) patients. Methods: All of the RNA- and miRNA-sequencing datasets of HCC were obtained from TCGA, and dysregulated RNAs between HCC tumors and the adjacent normal liver tissues were investigated by DESeq and edgeR algorithm. Survival analysis was used to confirm underlying prognostic indicators. Results: In the present study, we constructed a ceRNA network based on 16 differentially expressed genes (DEGs), 7 differentially expressed microRNAs and 34 differentially expressed long non-coding RNAs (DELs). Among these dysregulated RNAs, three DELs (AP002478.1, HTR2A-AS1, and ERVMER61-1) and six DEGs (enhancer of zeste homolog 2 [EZH2], kinesin family member 23 [KIF23], chromobox 2 [CBX2], centrosomal protein 55 [CEP55], cell division cycle 25A [CDC25A], and claspin [CLSPN]) were used for construct a prognostic signature for HCC overall survival (OS), and performed well in HCC OS (adjusted P<0.0001, adjusted hazard ratio = 2.761, 95% confidence interval = 1.838-4.147). Comprehensive survival analysis demonstrated that this prognostic signature may be act as an independent prognostic indicator of HCC OS. Functional assessment of these dysregulated DEGs in the ceRNA network and gene set enrichment of this prognostic signature suggest that both were enriched in the biological processes and pathways of the cell cycle, cell division and cell proliferation. Conclusions: Our current study constructed a ceRNA network for HCC, and developed a prognostic signature that may act as an independent indicator for HCC OS., QC 20190624

Our current study investigates the prognostic values of genetic variants and mRNA expression of cytochrome p450 oxidoreductase (POR) in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). A total of 19 candidate single nucleotide polymorphisms (SNPs) located in the exons of POR were genotyped using Sanger sequencing from 476 HBV-related HCC patients who underwent hepatectomy between 2003 and 2013. The mRNA expression of POR in 212 patients with HBV-related HCC was obtained from GSE14520 dataset. Survival analysis was performed to investigate the association of POR variants and mRNA expression with overall survival (OS) and recurrence-free survival (RFS). Nomograms were used to predict the prognosis of HBV-related HCC patients. Gene set enrichment analysis (GSEA) was used to investigate the mechanism of POR in HBV-related HCC prognosis. The polymorphism POR-rs1057868 was significantly associated with HBV-related HCC OS (CT/TT vs. CC, hazard ratio [HR] = 0.69, 95% confidence interval [CI] = [0.54, 0.88], P = 0.003), but not significantly associated with RFS (CT/TT vs. CC, P = 0.378). POR mRNA expression was also significantly associated with HBV-related HCC OS (high vs. low, HR = 0.61, 95% CI = [0.38, 0.97], P= 0.036), but not significantly associated with the RFS (high vs. low, P = 0.201). Two nomograms were developed to predict the HBV-related HCC OS. Furthermore, GSEA suggests that multiple gene sets were significantly enriched in liver cancer survival and recurrence, as well as POR-related target therapy in the liver. In conclusion, our study suggests that POR-rs1057868 and mRNA expression may serve as a potential postoperative prognosis biomarker in HBV-related HCC., QC 20190325

Objective: Our study is aim to explore potential key biomarkers and pathways in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) using genome-wide expression profile dataset and methods. Methods: Dataset from the GSE14520 is used as the training cohort and The Cancer Genome Atlas dataset as the validation cohort. Differentially expressed genes (DEGs) screening were performed by the limma package. Gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), gene ontology, the Kyoto Encyclopedia of Genes and Genomes, and risk score model were used for pathway and genes identification. Results: GSEA revealed that several pathways and biological processes are associated with hepatocarcinogenesis, such as the cell cycle, DNA repair, and p53 pathway. A total of 160 DEGs were identified. The enriched functions and pathways of the DEGs included toxic substance decomposition and metabolism processes, and the P450 and p53 pathways. Eleven of the DEGs were identified as hub DEGs in the WGCNA. In survival analysis of hub DEGs, high expression of PRC1 and TOP2A were significantly associated with poor clinical outcome of HBV-related HCC, and shown a good performance in HBV-related HCC diagnosis. The prognostic signature consisting of PRC1 and TOP2A also doing well in the prediction of HBV-related HCC prognosis. The diagnostic and prognostic values of PRC1 and TOP2A was confirmed in TCGA HCC patients. Conclusions: Key biomarkers and pathways identified in the present study may enhance the comprehend of the molecular mechanisms underlying hepatocarcinogenesis. Additionally, mRNA expression of PRC1 and TOP2A may serve as potential diagnostic and prognostic biomarkers for HBV-related HCC., QC 20191107