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Digital archive of theses discussed at the University of Pisa


Thesis etd-10222012-014241

Thesis type
Tesi di dottorato di ricerca
email address
Thesis title
Academic discipline
Course of study
tutor Prof. Bonino, Ferruccio
tutor Dott. Brunetto, Maurizia Rossana
controrelatore Prof. Dotta, Francesco
controrelatore Prof. Romanelli, Roberto Giulio
  • Allele Specific
  • Bioinformatic
  • Database
  • Eminested
  • HBV
  • HCV
  • Hepatitis
  • PCR
  • Resistance
  • Sequencing
  • Treatment
  • Virus
  • Web
Graduation session start date
Hepatitis viruses are among the most infectious pathogen for human causing severe liver disease like acute or chronic hepatitis. Hepatitis B virus (HBV) and Hepatitis C virus (HCV) can chronically infect the host liver replicating persistently in the hepatocyte. To date more than five hundred million of people worldwide are living with HBV or HCV chronic infection with high risk of developing liver fibrosis, cirrhosis and hepatocellular carcinoma.
Anti-viral therapy is necessary to avoid or slow down the liver disease and it includes different agents like the interferons family, acting as immune modulators, or the direct acting anti-viral (DAAs), small molecules able to interfere with viral enzymes at different stages of the replication path.
Unfortunately therapy may fail in some patient because of viral and/or host factors. When an end-stage liver disease is reached, the organ transplantation is the only therapy available (life-saving).
Viral heterogeneity affect the anti-viral therapy outcome since particular type of viral variants are frequently found associated to therapy failure, both in HBV and HCV infection cases.
Since no new drugs for HBV infection treatment have been developed and approved from 4 years, all the primary HBV resistant associated variants (RVs) have been already identified today, locating in the HBV polymerase / retrotranscriptase gene and mainly at codons rtA181 and rtM204. Some other codons have been identified in resistant HBV strains but always associated to the primary ones and classified as secondary / compensatory mutations for their role in restoring the wild-type replication level. Despite these information the HBV RVs biological role is still not clear and the in-vitro systems are far away from a real in vivo condition mimicking, with a concrete risk to provide misleading information.
New high sensitive technologies like Real-Time PCR and Ultra Deep Pyrosequencing could detect RVs as minor viral population in naïve patient but they were not set up to work in low levels of total viraemia condition (<10E+04 UI/ml), a possible on-treatment situation, particularly found in no responding or immunocompromised patients.
Differently from HBV, the first HCV resistant associated variants have been identified few time ago and others are probably still to come because of the many anti-HCV drugs in development or ready to be approved for the HCV infection treatment.
Hence, in this thesis we wanted to develop biomolecular and bioinformatic methods to identify the anti-viral resistant variants and study their dynamics before and on treatment in the attempt to contribute to the understanding of hepatitis viruses resistance associated variants.
In particular, we combined allele specific Polymerase Chain Reaction (PCR) method with eminested PCR method to obtain a high sensitive and specific assay detecting HBV resistant associated variants in low viraemia condition (ASRVPCR).
A sera panel including pre- and on-treatment samples from 15 chronic HBV infected patients (n=5 complete viral response, CVR; n=4 incomplete viral response, IVR; n=6 resistance after complete viral response, RACVR) treated with lamivudine (LAM), the first direct acting anti-viral approved for HBV infection treatment, was used for clinical validation of the assay and to study the early dynamics of HBV RVs.
The Allele Specific PCRs for HBV rtA181 and rtM204 codons showed no RVs in 5 complete viral response patients. On the contrary, resistance variants were amplified before the treatment start in sera of 7 out of 10 patients who experienced therapy failure (IVR + RACVR). Particularly, resistant variants were found in 3 out of 6 RACVR pts and in all the 4 IVR pts, showing a different distribution among the different groups of patients.
To further improve our method we decided to applied the sequencing method to the ASRVPCR products of 5 pts (2 RACVR + 3 IVR). The addition of the rtL180M secondary / compensatory mutation to the rtM204 variants during the follow-up was observed in 4 out of 5 pts. The fifth pt showed the rtL180M from the pre-treatment till the EOF samples. These data suggest that, in our cohort, the RVs as primary resistant mutations can circulate in CHB naive patients and their presence can affect the LAM treatment, particularly when the rtL180M is acquired.
Until 2 years ago the HCV heterogeneity affecting the treatment was at genotype level as the Standard of Care (SOC, Interferon + ribavirine) for the HCV infection treatment is high effective in all the patients but those infected with genotype 1 and 4. Thus, web access databases allowing phylogenetic analysis like sequence alignment, genotyping, subtyping were considered enough for HCV.
The arising DAAs era in the HCV treatment is now the driving force for the development of new databases and bioinformatic tools HCV dedicated including not only analisys for genotype/subtype prediction but also resistance variants identification.
Despite the new interest in creating HCV web access databases, few of them are actually including the necessary informations and tools for a correct identification of resistance. None of the available Databases is intended to be a real updated diagnosis instrument helping the clinician in taking therapy decision.
In 2010, a joint collaboration was established between the Victorian Infectious Diseases Reference Laboratory (VIDRL) of Melbourne Health, Australia and the Hepatitis C Virus Research Laboratory of the Institute of Medical and Veterinary Science (IMVS), Australia to develop a web assessable sequence analysis tool (SeqHepC) for the management of patients with resistance to the DAAs for chronic hepatitis C.
The project needed at first to collect a limited and manageable number of full length reference sequences from all the major HCV genotypes and subtypes.
We used the HCV Los Alamos Database and the tools included for query selection of a large number of full length HCV sequences. A total of 228 sequences were selected by unique submition, confirmed genotypes/subtypes by Simmonds consensus proposal and by naïve status. An unrooted tree was generated to confirm genotype/subtype of the 228 sequences and among them, 32 strains were chosen from the main branches of the tree.
The big skimming prompet us to proceed to the next phase of our project: to focus on HCV NS3 protease and NS5B polymerase to start off with how useful would these genes be for subtyping and if useful, what would be the minimum region for subtyping.
The NS3 and NS5B regions were both found to be useful for genotyping and subtyping. We succeeded in identifying a minimal region of 543 nucleotides located in the NS3 sequence including all the identified protease inhibitor resistant mutations. Such a minimal region was also useful for genotyping and even subtyping as showed by the phylogenetic tree and divergence data.
A working version of SeqHepC is currently undergoing alpha testing. The program is designed to enable genotyping and mutational analysis of HCV sequences, which can be submitted either as a nucleotide sequence or deduced amino acid sequence. The input sequence would be compared to the 32 full length HCV reference sequences to determine the genotype, followed by comparison with the reference sequence of an equivalent genotype for the assessment of drug-resistance associated amino acid substitutions. Reports generated are date and time stamped, and will display data including the HCV genome region covered by the submitted sequence, a list of clinically significant amino acid substitutions, and predicted DAAs susceptibility.
In conclusion, we aimed to develop biomolecular assay and bioinformatic system to study and identify known resistant variants (in case of HBV) as well as new ones (in case of HCV) in the field of hepatitis viruses. We succeeded setting up a high sensitive and specific method for HBV RVs that could be useful in the future to better understand the meaning of the RVs and also to predict the LAM therapy failure in patient that still may benefit from this cost effective treatment. We also succeeded in the contribution to HCV RVs study collaborating to the set up of a web access database for the genotyping / subtyping and RVs prediction. Such an instrument will be necessary in the next future for the good clinical practice of the HCV infected patients and the management of the new complex therapies.