Hepatocellular carcinoma (HCC) is the third cause of cancer-related death worldwide. Accumulating studies have demonstrated that aberrant expression of several lncRNAs was found to be involved in the hepatocarcinogenesis. In this study, a lncRNA Ftx was chosen to investigate its effects on HCC cells, and clarify the possible mechanism. We demonstrated that the lncRNA Ftx and Ftx-derived miR-545 were up-regulated in both HCC tissues and cells. MiR-545 was positively correlated with lncRNA Ftx expression. Notably, clinical association analysis revealed that the high expression of lncRNA Ftx and miR-545 was associated with poor prognostic features, and conferred a reduced 5-year overall survival (OS) and disease-free survival (DFS) of HCC patients. We found that miR-545 was a pivotal mediator in Ftx-induced promotion of HCC cell growth. Subsequently, we identified RIG-I as a direct target of miR-545. The expression of RIG-I was downregulated in HCC tissues and was inversely correlated with miR-545 expression. Our data revealed that ectopic expression of RIG-I abrogated the effects of lncRNA Ftx or miR-545 on HCC cells. LncRNA Ftx/miR-545-mediated downregulation of RIG-I led to increased Akt phosphorylation in vitro and in vivo. Inhibition of Akt phosphorylation abolished the effects of lncRNA Ftx/miR-545 on HCC cells. In conclusion, our study demonstrates that the novel pathway lncRNA Ftx/miR-545/RIG-I promotes HCC development by activating PI3K/Akt signaling, and it may serve as a novel prognostic biomarker and therapeutic target for HCC.

Despite advances in the roles of long non-coding RNA (lncRNA) tumor suppressor candidate 7 (TUSC7) in cancer biology, which has been identified as a tumor suppressor by regulating cell proliferation, apoptosis, migration, invasion, cell cycle, and tumor growth, the function of TUSC7 in hepatocellular carcinoma (HCC) remains unknown. In this study, we observed that the expression of TUSC7 was immensely decreased in HCC. Clinically, the lower expression of TUSC7 predicted poorer survival and may be an independent risk factor for HCC patients. Moreover, TUSC7 inhibited cell metastasis, invasion, and epithelial-to-mesenchymal transformation (EMT) through competitively binding miR-10a. Furthermore, we found that TUSC7 could decrease the expression of Eph tyrosine kinase receptor A4 (EphA4), a downstream target of miR-10a as well as an EMT suppressor, through TUSC7-miR-10a-EphA4 axis. Taken together, we demonstrate that TUSC7 suppresses EMT through the TUSC7-miR-10a-EphA4 axis, which may be a potential target for therapeutic intervention in HCC.

Aberrant expression of microRNAs (miRNAs) and its dysfunction have been revealed as crucial modulators of cancer initiation and progression. MiR-129-2 has been reported to play a tumor suppressive role in different human malignancies. Here, we demonstrated that miR-129-2 was significantly decreased in hepatocellular carcinoma (HCC) tissues and cell lines. Furthermore, miR-129-2 was expressed at significant lower levels in aggressive and recurrent tumor tissues. Clinical analysis indicated that miR-129-2 expression was inversely correlated with venous infiltration, high Edmondson-Steiner grading and advanced tumor-node-metastasis (TNM) stage in HCC. Notably, miR-129-2 was an independent prognostic factor for indicating overall survival (OS) and disease-free survival (DFS) of HCC patients. Ectopic expression of miR-129-2 inhibited cell migration and invasion in vitro and in vivo. Furthermore, we confirmed that high mobility group box 1 (HMGB1) was a direct target of miR-129-2, and it abrogated the function of miR-129-2 in HCC. Mechanistic investigations showed that miR-129-2 overexpression inhibited AKT phosphorylation at Ser473 and decreased the expression of matrix metalloproteinase2/9 (MMP2/9). Upregulation of p-AKT abolished the decreased cell migration and invasion induced by miR-129-2 in HCC. Whereas inhibition of Akt phosphorylation significantly decreased HMGB1-enhanced HCC cell migration and invasion. Moreover, we found that miR-129-2 was downregulated by DNA methylation, and demethylation of miR-129-2 increased miR-129-2 expression in HCC cells and resulted in significant inhibitory effects on cell migration and invasion. In conclusion, miR-129-2 may serve as a prognostic indicator for HCC patients and exerts tumor suppressive role, at least in part, by inhibiting HMGB1.

Aberrant autophagic processes have been found to have fundamental roles in the pathogenesis of different kinds of tumors, including hepatocellular carcinoma (HCC). P300/CBP-associated factor (PCAF), a histone acetyltransferase (HAT), performs its function by acetylating both histone and non-histone proteins. Our previous studies showed that PCAF was downregulated in HCC tissues and its high expression was significantly associated with patient survival after surgery, serving as a prognostic marker. In this study we found that overexpression of PCAF induced autophagy of HCC cells and its knockdown depressed autophagy. As type II programmed cell death, autophagy induced by PCAF-elicited cell death in HCC cells. In vivo experiments confirmed that PCAF-induced autophagy inhibited tumor growth. Subsequent in vitro experiments showed that PCAF promoted autophagy by inhibiting Akt/mTOR signaling pathway. Our findings show that PCAF is a novel modulator of autophagy in HCC, and can serve as an attractive therapeutic strategy of HCC treatment.

BackgroundPortal vein system thrombosis (PVST) is potentially fatal for patients if the diagnosis is not timely or the treatment is not proper. There hasn’t been any available technique to detect clinic risk factors to predict PVST after splenectomy in cirrhotic patients. The aim of this study is to detect the clinic risk factors of PVST for splenectomy and cardia devascularization patients for liver cirrhosis and portal hypertension, and build an efficient predictive model to PVST via the detected risk factors, by introducing the machine learning method. We collected 92 clinic indexes of splenectomy plus cardia devascularization patients for cirrhosis and portal hypertension, and proposed a novel algorithm named as RFA-PVST (Risk Factor Analysis for PVST) to detect clinic risk indexes of PVST, then built a SVM (support vector machine) predictive model via the detected risk factors. The accuracy, sensitivity, specificity, precision, F-measure, FPR (false positive rate), FNR (false negative rate), FDR (false discovery rate), AUC (area under ROC curve) and MCC (Matthews correlation coefficient) were adopted to value the predictive power of the detected risk factors. The proposed RFA-PVST algorithm was compared to mRMR, SVM-RFE, Relief, S-weight and LLEScore. The statistic test was done to verify the significance of our RFA-PVST.ResultsAnticoagulant therapy and antiplatelet aggregation therapy are the top-2 risk clinic factors to PVST, followed by D-D (D dimer), CHOL (Cholesterol) and Ca (calcium). The SVM (support vector machine) model built on the clinic indexes including anticoagulant therapy, antiplatelet aggregation therapy, RBC (Red blood cell), D-D, CHOL, Ca, TT (thrombin time) and Weight factors has got pretty good predictive capability to PVST. It has got the highest PVST predictive accuracy of 0.89, and the best sensitivity, specificity, precision, F-measure, FNR, FPR, FDR and MCC of 1, 0.75, 0.85, 0.92, 0, 0.25, 0.15 and 0.8 respectively, and the comparable good AUC value of 0.84. The statistic test results demonstrate that there is a strong significant difference between our RFA-PVST and the compared algorithms, including mRMR, SVM-RFE, Relief, S-weight and LLEScore, that is to say, the risk indicators detected by our RFA-PVST are statistically significant.ConclusionsThe proposed novel RFA-PVST algorithm can detect the clinic risk factors of PVST effectively and easily. Its most contribution is that it can display all the clinic factors in a 2-dimensional space with independence and discernibility as y-axis and x-axis, respectively. Those clinic indexes in top-right corner of the 2-dimensional space are detected automatically as risk indicators. The predictive SVM model is powerful with the detected clinic risk factors of PVST. Our study can help medical doctors to make proper treatments or early diagnoses to PVST patients. This study brings the new idea to the study of clinic treatment for other diseases as well.