The current anti-hepatitis C virus (HCV) therapy, based on pegylated-interferon alpha and ribavirin, has limited success rate and is accompanied by several side effects. The aim of this study was to identify protein profiles in pretreatment liver biopsies of HCV patients correlating with the outcome of antiviral therapy. Cytosolic or membrane/organelle-enriched protein extracts from liver biopsies of eight HCV patients were analyzed by two-dimensional fluorescence difference gel electrophoresis and mass spectrometry. Overall, this analysis identified 21 proteins whose expression levels correlate with therapy response. These factors are involved in interferon-mediated antiviral activity, stress response, and energy metabolism. Moreover, we found that post-translational modifications of dihydroxyacetone kinase were also associated with therapy outcome. Differential expression of the five best performing markers (STAT1, Mx1, DD4, DAK, and PD-ECGF) was confirmed by immunoblotting assays in an independent group of HCV patients. Finally, we showed that a prediction model based on the expression levels of these markers classifies responder and nonresponder patients with an accuracy of 85.7%. These results provide evidence that the analysis of pretreatment liver protein profiles is valuable for discriminating between responder and nonresponder HCV patients, and may contribute to reduce the number of nonresponder patients exposed to therapy-associated risks.
The current anti-hepatitis C virus (HCV) therapy, based on pegylated-interferon alpha and ribavirin, has limited success rate and is accompanied by several side effects. The aim of this study was to identify protein profiles in pretreatment liver biopsies of HCV patients correlating with the outcome of antiviral therapy. Cytosolic or membrane/organelle-enriched protein extracts from liver biopsies of eight HCV patients were analyzed by two-dimensional fluorescence difference gel electrophoresis and mass spectrometry. Overall, this analysis identified 21 proteins whose expression levels correlate with therapy response. These factors are involved in interferon-mediated antiviral activity, stress response, and energy metabolism. Moreover, we found that post-translational modifications of dihydroxyacetone kinase were also associated with therapy outcome. Differential expression of the five best performing markers (STAT1, Mx1, DD4, DAK, and PD-ECGF) was confirmed by immunoblotting assays in an independent group of HCV patients. Finally, we showed that a prediction model based on the expression levels of these markers classifies responder and nonresponder patients with an accuracy of 85.7%. These results provide evidence that the analysis of pretreatment liver protein profiles is valuable for discriminating between responder and nonresponder HCV patients, and may contribute to reduce the number of nonresponder patients exposed to therapy-associated risks.
Liver protein profiling in chronic hepatitis C: identification of potential predictive markers for interferon therapy outcome.
CORAZZARI, MARCO;
2012-01-01
Abstract
The current anti-hepatitis C virus (HCV) therapy, based on pegylated-interferon alpha and ribavirin, has limited success rate and is accompanied by several side effects. The aim of this study was to identify protein profiles in pretreatment liver biopsies of HCV patients correlating with the outcome of antiviral therapy. Cytosolic or membrane/organelle-enriched protein extracts from liver biopsies of eight HCV patients were analyzed by two-dimensional fluorescence difference gel electrophoresis and mass spectrometry. Overall, this analysis identified 21 proteins whose expression levels correlate with therapy response. These factors are involved in interferon-mediated antiviral activity, stress response, and energy metabolism. Moreover, we found that post-translational modifications of dihydroxyacetone kinase were also associated with therapy outcome. Differential expression of the five best performing markers (STAT1, Mx1, DD4, DAK, and PD-ECGF) was confirmed by immunoblotting assays in an independent group of HCV patients. Finally, we showed that a prediction model based on the expression levels of these markers classifies responder and nonresponder patients with an accuracy of 85.7%. These results provide evidence that the analysis of pretreatment liver protein profiles is valuable for discriminating between responder and nonresponder HCV patients, and may contribute to reduce the number of nonresponder patients exposed to therapy-associated risks.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
