GeVaDSs - decision support system for novel Genetic Vaccine development process.

BACKGROUND: The lack of a uniform way for qualitative and quantitative evaluation of vaccine candidates under development led us to set up a standardized scheme for vaccine efficacy and safety evaluation. We developed and implemented molecular and immunology methods, and designed support tools for immunization data storage and analyses. Such collection can create a unique opportunity for immunologists to analyse data delivered from their laboratories. RESULTS: We designed and implemented GeVaDSs (Genetic Vaccine Decision Support system) an interactive system for efficient storage, integration, retrieval and representation of data. Moreover, GeVaDSs allows for relevant association and interpretation of data, and thus for knowledge-based generation of testable hypotheses of vaccine responses. CONCLUSIONS: GeVaDSs has been tested by several laboratories in Europe, and proved its usefulness in vaccine analysis. Case study of its application is presented in the additional files. The system is available at: http://gevads.cs.put.poznan.pl/preview/(login: viewer, password: password).

Hepatitis C virus quasispecies in chronically infected children subjected to interferon-ribavirin therapy.

Accumulating evidence suggests that certain features of hepatitis C virus (HCV), especially its high genetic variability, might be responsible for the low efficiency of anti-HCV treatment. Here, we present a bioinformatic analysis of HCV-1a populations isolated from 23 children with chronic hepatitis C (CHC) subjected to interferon-ribavirin therapy. The structures of the viral quasispecies were established based on a 132-amino-acid sequence derived from E1/E2 protein, including hypervariable region 1 (HVR1). Two types of HCV populations were identified. The first type, found in non-responders, contained a small number of closely related variants. The second type, characteristic for sustained responders, was composed of a large number of distantly associated equal-rank variants. Comparison of 445 HVR1 sequences showed that a significant number of variants present in non-responding patients are closely related, suggesting that certain, still unidentified properties of the pathogen may be key factors determining the result of CHC treatment.

[The clinical consequences of changes occurring in HCV population during the first weeks of chronic hepatitis C treatment with interferon and ribavirin]. / Znaczenie kliniczne zmian w populacji HCV w pierwszych tygodniach leczenia przewleklego zapalenia watroby typu C interferonem i rybawiryna.

Hepatitis C virus (HCV) is an extremely dangerous human pathogen. It is widespread all over the world and often leads to the development of chronic hepatitis C (CHC), which can eventually result in cirrhosis a hepatocellular carcinoma. The efficiency of the current applied methods of treatment of HCV infection remains unsatisfactory. The main course of development of CHC and of therapeutic problems is the genetic polymorphism of HCV. The conducted analysis of the structure of the virus' population permits are conclude that the degree of diversity it presents is a crucial agent in the prediction of the outcome of IFN and ribavirin therapy.

Towards prediction of HCV therapy efficiency.

We investigate a correlation between genetic diversity of hepatitis C virus population and the level of viral RNA accumulation in patient blood. Genetic diversity is defined as the mean Hamming distance between all pairs of virus RNA sequences representing the population. We have found that a low Hamming distance (i.e. low genetic diversity) correlates with a high RNA level; symmetrically, high diversity corresponds to a low RNA level. We contend that the obtained correlation strength justifies the use of the viral RNA level as a measure enabling prediction of efficiency of an established therapy. We also propose that patient qualification for therapy, based on viral RNA level, improves its efficiency.