Correction: ShRNA-Targeted COMMD7 Suppresses Hepatocellular Carcinoma Growth.

[This corrects the article DOI: 10.1371/journal.pone.0045412.].

Effects of AFP-activated PI3K/Akt signaling pathway on cell proliferation of liver cancer.

This study aims to investigate effects of alpha-fetoprotein (AFP)-activated phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) signaling pathway on hepatocellular carcinoma cell proliferation. Active cirrhosis patients after hepatitis B infection (n = 20) and viral hepatitis patients with hepatocellular carcinoma (HCC) (n = 20) were selected as the subjects of the present study. Another 20 healthy subjects were selected as the control group. The serum AFP expression and liver tissue PI3K and Akt gene mRNA expression were detected. The hepatoma cell model HepG2 which had a stable expression of AFP gene was used. Real-time quantitative PCR and Western blot and other methods were used to analyze the intracellular PI3K and Akt protein levels. Compared with control group and cirrhosis group, the serum AFP levels in HCC group significantly increased, and the tissue PI3K and Akt mRNA expression also significantly increased. HepG2 cells were intervened using AFP, in which the PIK and Akt protein expression significantly increased. After intervention by use of AFP monoclonal antibodies or LY294002 inhibitor, the PIK and Akt protein expression in HepG2 cell was significantly decreased (P < 0.05). AFP can promote the proliferation of hepatoma cells via activation of PI3K/Akt signaling pathway.

[Expression and roles of the epithelial mesenchymal transition markers E-cadherin and vimentin in hepatocellular carcinoma].

OBJECTIVE: To determine the differential protein expressions of epithelial mesenchymal transition (EMT) markers E-cadherin and vimentin in hepatocellular carcinorma (HCC) and to investigate their correlation to the molecular mechanisms of metastasis to explore their potential utility as prognostic indicators of HCC. METHODS: Tumor tissues and patient-matched adjacent non-tumor tissues were collected from individuals diagnosed with HCC. E-cadherin and vimentin protein expressions in the tissue specimens were quantified by western blot with densitometry of fluorescence emission and comparatively analyzed to determine the associations with molecular and clinical features. The expressions of E-cadherin and vimentin, as well as the other EMT-related protein Twist, were also detected in the tissue specimens by immunohistochemistry. Statistical analyses were carried out by paired-samples t-test, Mann-Whitney test, and Spearman rank correlation analysis. RESULTS: E-cadherin expression was significantly lower in tumor tissues (0.082 +/- 0.063 vs. adjacent non-tumor tissues: 0.226 +/- 0.215, t = -4.050, P less than 0.01), lower in patients with portal vein tumor thrombus (vs. non-thrombic HCC patients, P = 0.001), and correlated with TNM stage (III/IV > I/II, P = 0.003). Vimentin expression was significantly higher in tumor tissues (vs. adjacent non-tumor tissues, P = 0.002), negatively correlated with E-cadherin expression (t = -0.509, P = 0.004), and closely associated with some clinical parameters, such as portal vein tumor thrombus (P less than 0.01), TNM stage (P less than 0.01), and Milan criteria (P = 0.005). Immunohistochemistry showed that E-cadherin expression was very weak in tumors but very strong in the cell membranes of non-tumor tissues, and that vimentin and Twist expressions were strong in tumors but undetectable in non-tumor tissue. CONCLUSION: Expression levels of the EMT markers E-cadherin and vimentin in HCC are related to clinical parameters, including portal vein tumor thrombus and TNM stage, and may represent useful prognostic markers of metastasis.

Bioinformatics analysis reveals potential candidate drugs for HCC.

In our study, we used the GSE17967 series to identify differentially expressed genes between cirrhosis and hepatocellular carcinoma, aiming to analyse the mechanism of the progression of cirrhosis to hepatocellular carcinoma and identify the sub-pathways closely related to this progression, and find the small molecule drugs to interfere this progression. From the result of our study, we find that many small molecule drugs closely related with carcinoma have been linked by our method. We also find some new small molecule drugs related to this progression. It is demonstrated that bioinformatics analysis is useful in identification of the candidate drugs in hepatocellular carcinoma.

Development of QSAR-Improved Statistical Potential for the Structure-Based Analysis of ProteinPeptide Binding Affinities.

Proteinpeptide interactions have recently been found to play an essential role in constructing intracellular signaling networks. Understanding the molecular mechanism of such interactions and identification of the interacting partners would be of great value for developing peptide therapeutics against many severe diseases such as cancer. In this study, we describe a structure-based, general-purpose strategy for fast and reliably predicting proteinpeptide binding affinities. This strategy combines unsupervised knowledge-based statistical potential derived from 505 interfacially diverse, non-redundant proteinpeptide complex structures and supervised quantitative structure-activity relationship (QSAR) modeling trained by 250 proteinpeptide interactions with known structure and affinity data. The built partial least squares (PLS) model is confirmed to have high stability and predictive power by using internal 5-fold cross-validation and rigorous Monte Carlo cross-validation (MCCV). The model is further employed to analyze two large groups of HLA- and SH3-binding peptides based upon computationally modeled structures. Satisfactorily, although the PLS model is originally trained with dissociation constants (Kd ) of proteinpeptide binding, it shows a good correlation with other two affinity qualities, i.e. SPOT signal intensities (BLU) and half maximal competitive concentrations (IC50 ). Furthermore, we perform systematic comparisons of our method with several widely used, representative affinity predictors, including molecular mechanics-based MM-PB/SA, knowledge-based DFIRE and docking score HADDOCK, on a small panel of elaborately selected proteinpeptide systems. It is demonstrated that (i) the QSAR-improved statistical potential exhibits a comparable predictive performance with but can work faster than these traditional methods, and (ii) the crystal structure-derived statistical potential also supports the modeled and solution structures of proteinpeptide complexes. We expect that this hybrid method can be exploited as a new scoring tool to facilitate, for example, peptide docking and virtual screening.

ShRNA-targeted COMMD7 suppresses hepatocellular carcinoma growth.

BACKGROUND: COMMD7 is a newly identified gene overexpressed in hepatocellular carcinoma (HCC) and associated with tumor invasion and poor prognosis. We aim to examine the biological function of COMMD7 in HCC by shRNA silencing. METHODS: COMMD7 expressions were examined in human HCC cell lines HepG2, Huh7, Hep3B, HLE, HLF, SK-Hep-1 and PLC/PRF/5 cells. Recombinant pGenesil-COMMD7-shRNA was transfected into COMMD7-abundant HepG2 cells to silence COMMD7 expression. The effects of COMMD7 silencing on HepG2 cell proliferation in vitro and xenograft tumor growth in vivo were evaluated. Flow cytometry profiling was used to detect the presence of apoptosis in COMMD7-silenced HepG2 cells and to differentiate cell cycle distribution. Electrophoretic mobility shift assay and luciferase reporter assays to examine the activities of nuclear factor-kappaB (NF-κB) signaling pathways in response to tumor necrosis factor (TNF)-α in COMMD7-silenced HepG2 cells. RESULTS: COMMD7 expression level was abundance in HepG2 and SK-Hep-1 cells. COMMD7 was aberrantly overexpressed in HepG2 cells, whilst pGenesil-COMMD7-shRNA exhibited a maximal inhibition rate of 75%. COMMD7 silencing significantly reduced HepG2 cell proliferation and colony formation. The knockdown of COMMD7 resulted in an increased apoptosis and cell cycle arrest at S-phase. COMMD7 knockdown also exhibited an antineoplastic effect in vivo, which manifested as tumor xenograft growth retardation. COMMD7 silencing also suppressed the responsiveness of NF-κB signaling pathway to the stimulation with TNF-α in vitro. Moreover, the similar suppressive effects of COMMD7 silence on SK-Hep-1 cells were also observed. CONCLUSIONS: COMMD7 contributes to HCC progression by reducing cell apoptosis and overcoming cell cycle arrest. The proliferative and antiapoptotic effects of COMMD7 may be mediated by NF-κB signaling pathway.