Hepatocellular carcinoma (HCC) is one of the most common malignant types of cancer, with a high mortality rate. Sorafenib is the sole approved oral clinical therapy against advanced HCC. However, individual patients exhibit varying responses to sorafenib and the development of sorafenib resistance has been a new challenge for its clinical efficacy. The current study identified gene biomarkers and key pathways in sorafenib-resistant HCC using bioinformatics analysis. Gene dataset GSE73571 was obtained from the Gene Expression Omnibus (GEO) database, including four sorafenib-acquired resistant and three sorafenib-sensitive HCC phenotypes. Differentially expressed genes (DEGs) were identified using the web tool GEO2R. Functional and pathway enrichment of DEGs were analyzed using the Database for Annotation, Visualization and Integrated Discovery and the protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins and Cytoscape. A total of 1,319 DEGs were selected, which included 593 upregulated and 726 downregulated genes. Functional and pathway enrichment analysis revealed DEGs enriched in negative regulation of endopeptidase activity, cholesterol homeostasis, DNA replication and repair, coagulation cascades, insulin resistance, RNA transport, cell cycle and others. Eight hub genes, including kininogen 1, vascular cell adhesion molecule 1, apolipoprotein C3, alpha 2-HS glycoprotein, erb-b2 receptor tyrosine kinase 2, secreted protein acidic and cysteine rich, vitronectin and vimentin were identified from the PPI network. In conclusion, the present study identified DEGs and key genes in sorafenib-resistant HCC, which further the knowledge of potential mechanisms in the development of sorafenib resistance and may provide potential targets for early diagnosis and new treatments for sorafenib-resistant HCC.

Diethylnitrosamine (DEN) is present in food, water, and daily supplies and is regarded as a toxicant of carcinogenicity. The developmental toxicity of DEN has been rarely reported as yet. In this study, zebrafish were exposed to different concentrations of DEN at 6 h post-fertilization (hpf) to access embryonic toxicity of the compound. The results show that DEN resulted in negative effects of hatching rate, heartbeat, body length, and spontaneous movement. Deformities, including notochord malformation, pericardium edema, embryonic membrane turbidity, tail hypoplasia, yolk sac deformity, and growth retardation, happened during exposure period. Moreover, production of reactive oxygen species (ROS) significantly increased after DEN treatment. Then, alterations of the expression level of oxidative stress-related genes were observed in our results. To our knowledge, this is the first study concerning the effect of DEN on zebrafish. And from the information of our research, we speculated that development toxicity of DEN should be related to the excessive oxidative stress.

No abstract

Emerging evidence revealed the critical roles of long non-coding RNAs (lncRNAs) in maintaining genomic instability. However, genome instability-associated lncRNAs (GILncRNAs) and their performance in clinical prognostic significance in hepatocellular carcinoma (HCC) are rarely reported. Our study constructed a computational framework integrating somatic mutation information and lncRNA expression profiles of HCC genome and we identified 88 GILncRNAs of HCC. Function enrichment analysis revealed that GILncRNAs were involved in various metabolism processes and genome instability of cancer. A genome instability-derived lncRNA-based gene signature (GILncSig) was constructed using training set data. The performance of GILncSig for outcome prediction was validated in testing set and The Cancer Genome Atlas (TCGA) set. The multivariate cox regression analysis and stratification analysis demonstrated GILncSig could serve as an independent prognostic factor for the overall survival of HCC patients. The time-dependent Receiver Operating Characteristic (ROC) curve illustrated GILncSig outperformed two recently published lncRNA signatures for overall survival prediction. The combination of GILncSig and tumor protein p53 (TP53) mutation status exhibited better prognostic performance in survival evaluation compared to TP53 mutation status alone. AC145343.1 was further validated to be a risk factor for HCC in vitro among GILncSig . Overall, our study provided a novel approach for identification of genome instability-associated lncRNAs and established an independent risk score system for outcome prediction of HCC patients, which provided a new insight for exploring in-depth mechanism and potential therapy strategy.

Aims: We aimed to explore the crucial miRNA-mRNA axis through bioinformatics analysis and provide evidences for the development of pathophysiological mechanisms and new therapies for HBV-related HCC. Methods: MiRNA (GSE76903) and mRNA (GSE77509) dataset were used to screen differentially expressed miRNAs (DE-miRNAs) and differentially expressed mRNAs (DE-mRNAs) using R software. Overlapping genes between DE-mRNAs and target genes of DE-miRNAs were identified as candidate genes. Hub genes were obtained via cytohubba analysis. The expression at protein and mRNA levels and prognostic value of hub genes were evaluated based on The Cancer Genome Atlas (TCGA) data. Key miRNA-mRNA axes were constructed according to predicted miRNA-mRNA pairs. MiRNA expression and prognostic role were respectively identified using starBase v3.0 and Kaplan-Meier plotter database. Real-time PCR was performed to verify the expression of crucial miRNAs and mRNAs. Coexpression of crucial miRNA and mRNA were analyzed using starBase v3.0. Results: CDK1, CCNB1, CKS2 and CCNE1 were screened as hub genes, which were significantly upregulated at protein and mRNA levels. These up-regulated hub genes were also significantly associated with poor prognosis. Hsa-mir-195-5p/ CDK1 , hsa-mir-5589-3p/ CCNB1 and hsa-let-7c-3p/ CKS2 were screened as critical miRNA-mRNA axes. Critical miRNAs were decreased in HCC, which indicates unfavourable prognosis. QPCR results showed that crucial miRNAs were decreased, whereas critical mRNAs were increased in HBV-related HCC. A reverse relationship between miRNA and mRNA in crucial axis was further verified. Conclusion: This study identified several miRNA-mRNA axes in HBV-related HCC. Hsa-mir-195-5p/ CDK1 , hsa-mir-5589-3p/ CCNB1 and hsa-let-7c-3p/ CKS2 might serve as potential prognostic biomarkers and therapeutic targets for HBV-related HCC.