Hypoxia up-regulates SERPINB3 through HIF-2\u3b1 in human liver cancer cells.

SERPINB3 is a cysteine-proteases inhibitor up-regulated in a significant number of cirrhotic patients carrying hepatocellular carcinoma (HCC) and recently proposed as a prognostic marker for HCC early recurrence. SERPINB3 has been reported to stimulate proliferation, inhibit apoptosis and, similar to what reported for hypoxia, to trigger epithelial-to-mesenchymal transition (EMT) and increased invasiveness in liver cancer cells. This study has investigated whether SERPINB3 expression is regulated by hypoxia-related mechanisms in liver cancer cells. Exposure of HepG2 and Huh7 cells to hypoxia up-regulated SERPINB3 transcription, protein synthesis and release in the extracellular medium. Hypoxia-dependent SERPINB3 up-regulation was selective (no change detected for SERPINB4) and operated through hypoxia inducible factor (HIF)-2\u3b1 (not HIF-1\u3b1) binding to SERPINB3 promoter, as confirmed by chromatin immuno-precipitation assay and silencing experiments employing specific siRNAs. HIF-2\u3b1-mediated SERPINB3 up-regulation under hypoxic conditions required intracellular generation of ROS. Immuno-histochemistry (IHC) and transcript analysis, performed in human HCC specimens, revealed co-localization of the two proteins in liver cancer cells and the existence of a positive correlation between HIF-2\u3b1 and SERPINB3 transcript levels, respectively. Hypoxia, through HIF-2\u3b1-dependent and redox-sensitive mechanisms, up-regulates the transcription, synthesis and release of SERPINB3, a molecule with a high oncogenic potential

Viral Kinetics Suggests a Reconciliation of the Disparate Observations of the Modulation of Claudin-1 Expression on Cells Exposed to Hepatitis C Virus

The tight junction protein claudin-1 (CLDN1) is necessary for hepatitis C virus (HCV) entry into target cells. Recent studies have made disparate observations of the modulation of the expression of CLDN1 on cells following infection by HCV. In one study, the mean CLDN1 expression on cells exposed to HCV declined, whereas in another study HCV infected cells showed increased CLDN1 expression compared to uninfected cells. Consequently, the role of HCV in modulating CLDN1 expression, and hence the frequency of cellular superinfection, remains unclear. Here, we present a possible reconciliation of these disparate observations. We hypothesized that viral kinetics and not necessarily HCV-induced receptor modulation underlies these disparate observations. To test this hypothesis, we constructed a mathematical model of viral kinetics in vitro that mimicked the above experiments. Model predictions provided good fits to the observed evolution of the distribution of CLDN1 expression on cells following exposure to HCV. Cells with higher CLDN1 expression were preferentially infected and outgrown by cells with lower CLDN1 expression, resulting in a decline of the mean CLDN1 expression with time. At the same time, because the susceptibility of cells to infection increased with CLDN1 expression, infected cells tended to have higher CLDN1 expression on average than uninfected cells. Our study thus presents an explanation of the disparate observations of CLDN1 expression following HCV infection and points to the importance of considering viral kinetics in future studies of receptor expression on cells exposed to HCV

Development of Mathematical Models for the Analysis of Hepatitis Delta Virus Viral Dynamics

BACKGROUND: Mathematical models have shown to be extremely helpful in understanding the dynamics of different virus diseases, including hepatitis B. Hepatitis D virus (HDV) is a satellite virus of the hepatitis B virus (HBV). In the liver, production of new HDV virions depends on the presence of HBV. There are two ways in which HDV can occur in an individual: co-infection and super-infection. Co-infection occurs when an individual is simultaneously infected by HBV and HDV, while super-infection occurs in persons with an existing chronic HBV infection. METHODOLOGY/PRINCIPAL FINDINGS: In this work a mathematical model based on differential equations is proposed for the viral dynamics of the hepatitis D virus (HDV) across different scenarios. This model takes into consideration the knowledge of the biology of the virus and its interaction with the host. In this work we will present the results of a simulation study where two scenarios were considered, co-infection and super-infection, together with different antiviral therapies. Although, in general the predicted course of HDV infection is similar to that observed for HBV, we observe a faster increase in the number of HBV infected cells and viral load. In most tested scenarios, the number of HDV infected cells and viral load values remain below corresponding predicted values for HBV. CONCLUSIONS/SIGNIFICANCE: The simulation study shows that, under the most commonly used and generally accepted therapy approaches for HDV infection, such as lamivudine (LMV) or ribavirine, peggylated alpha-interferon (IFN) or a combination of both, LMV monotherapy and combination therapy of LMV and IFN were predicted to more effectively reduce the HBV and HDV viral loads in the case of super-infection scenarios when compared with the co-infection. In contrast, IFN monotherapy was found to reduce the HDV viral load more efficiently in the case of super-infection while the effect on the HBV viral load was more pronounced during co-infection. The results suggest that there is a need for development of high efficacy therapeutic approaches towards the specific inhibition of HDV replication. These approaches may additionally be directed to the reduction of the half-life of infected cells and life-span of newly produced circulating virions

Ribavirin-Induced Anemia in Hepatitis C Virus Patients Undergoing Combination Therapy

The current standard of care for hepatitis C virus (HCV) infection – combination therapy with pegylated interferon and ribavirin – elicits sustained responses in only ∼50% of the patients treated. No alternatives exist for patients who do not respond to combination therapy. Addition of ribavirin substantially improves response rates to interferon and lowers relapse rates following the cessation of therapy, suggesting that increasing ribavirin exposure may further improve treatment response. A key limitation, however, is the toxic side-effect of ribavirin, hemolytic anemia, which often necessitates a reduction of ribavirin dosage and compromises treatment response. Maximizing treatment response thus requires striking a balance between the antiviral and hemolytic activities of ribavirin. Current models of viral kinetics describe the enhancement of treatment response due to ribavirin. Ribavirin-induced anemia, however, remains poorly understood and precludes rational optimization of combination therapy. Here, we develop a new mathematical model of the population dynamics of erythrocytes that quantitatively describes ribavirin-induced anemia in HCV patients. Based on the assumption that ribavirin accumulation decreases erythrocyte lifespan in a dose-dependent manner, model predictions capture several independent experimental observations of the accumulation of ribavirin in erythrocytes and the resulting decline of hemoglobin in HCV patients undergoing combination therapy, estimate the reduced erythrocyte lifespan during therapy, and describe inter-patient variations in the severity of ribavirin-induced anemia. Further, model predictions estimate the threshold ribavirin exposure beyond which anemia becomes intolerable and suggest guidelines for the usage of growth hormones, such as erythropoietin, that stimulate erythrocyte production and avert the reduction of ribavirin dosage, thereby improving treatment response. Our model thus facilitates, in conjunction with models of viral kinetics, the rational identification of treatment protocols that maximize treatment response while curtailing side effects

The mechanisms by which polyamines accelerate tumor spread

Increased polyamine concentrations in the blood and urine of cancer patients reflect the enhanced levels of polyamine synthesis in cancer tissues arising from increased activity of enzymes responsible for polyamine synthesis. In addition to their de novo polyamine synthesis, cells can take up polyamines from extracellular sources, such as cancer tissues, food, and intestinal microbiota. Because polyamines are indispensable for cell growth, increased polyamine availability enhances cell growth. However, the malignant potential of cancer is determined by its capability to invade to surrounding tissues and metastasize to distant organs. The mechanisms by which increased polyamine levels enhance the malignant potential of cancer cells and decrease anti-tumor immunity are reviewed. Cancer cells with a greater capability to synthesize polyamines are associated with increased production of proteinases, such as serine proteinase, matrix metalloproteinases, cathepsins, and plasminogen activator, which can degrade surrounding tissues. Although cancer tissues produce vascular growth factors, their deregulated growth induces hypoxia, which in turn enhances polyamine uptake by cancer cells to further augment cell migration and suppress CD44 expression. Increased polyamine uptake by immune cells also results in reduced cytokine production needed for anti-tumor activities and decreases expression of adhesion molecules involved in anti-tumor immunity, such as CD11a and CD56. Immune cells in an environment with increased polyamine levels lose anti-tumor immune functions, such as lymphokine activated killer activities. Recent investigations revealed that increased polyamine availability enhances the capability of cancer cells to invade and metastasize to new tissues while diminishing immune cells' anti-tumor immune functions