Underexpression of Deleted in liver cancer 2 (DLC2) is associated with overexpression of RhoA and poor prognosis in hepatocellular carcinoma

<p>Abstract</p> <p>Background</p> <p>DLC2, a unique RhoGAP, has been recently identified as a tumor suppressor gene in hepatocellular carcinoma (HCC). However, the expression of DLC2 protein, and its relationship with RhoA in clinical hepatocellular carcinoma have not been studied. The aim of this study was to investigate the DLC2 protein expression and its correlation with expression of RhoA, as well as to evaluate the prognostic value of DLC2 for HCC patients.</p> <p>Methods</p> <p>Western blot and immunohistochemical staining were employed to detect DLC2 protein expression in 128 HCC specimens. The correlation between DLC2 protein expression and clinicopathologic outcome, and prognostic value of DLC2 for HCC patients were analyzed.</p> <p>Results</p> <p>HCC tissues revealed significantly lower level of DLC2 protein than pericarcinomatous liver tissues (PCLT). There was significant correlation between underexpression of DLC2 protein and cell differentiation. Meanwhile, underexpression of DLC2 protein was correlated with overexression of RhoA. Furthermore, HCC Patients with DLC2-negative expression showed a significantly poorer prognosis than those with DLC2-positve expression.</p> <p>Conclusion</p> <p>Our data strongly suggested that decreased DLC2 expression in HCC correlates with cell differentiation of HCC and overexpression of RhoA, underexpression of DLC2 is associated with poor prognosis in HCC patients.</p

MicroRNA Profile Predicts Recurrence after Resection in Patients with Hepatocellular Carcinoma within the Milan Criteria

Objective: Hepatocellular carcinoma (HCC) is difficult to manage due to the high frequency of post-surgical recurrence. Early detection of the HCC recurrence after liver resection is important in making further therapeutic options, such as salvage liver transplantation. In this study, we utilized microRNA expression profiling to assess the risk of HCC recurrence after liver resection. Methods: We examined microRNA expression profiling in paired tumor and non-tumor liver tissues from 73 HCC patients who satisfied the Milan Criteria. We constructed prediction models of recurrence-free survival using the Cox proportional hazard model and principal component analysis. The prediction efficiency was assessed by the leave-one-out crossvalidation method, and the time-averaged area under the ROC curve (ta-AUROC). Results: The univariate Cox analysis identified 13 and 56 recurrence-related microRNAs in the tumor and non-tumor tissues, such as miR-96. The number of recurrence-related microRNAs was significantly larger in the non-tumor-derived microRNAs (N-miRs) than in the tumor-derived microRNAs (T-miRs, P, 0.0001). The best ta-AUROC using the whole dataset, T-miRs, NmiRs, and clinicopathological dataset were 0.8281, 0.7530, 0.7152, and 0.6835, respectively. The recurrence-free survival curve of the low-risk group stratified by the best model was significantly better than that of the high-risk group (Log-rank: P = 0.00029). The T-miRs tend to predict early recurrence better than late recurrence, whereas N-miRs tend to predict late recurrence better (P, 0.0001). This finding supports the concept of early recurrence by the dissemination of primary tumor cells and multicentric late recurrence by the ‘field effect’. Conclusion: microRNA profiling can predict HCC recurrence in Milan criteria cases