Hepatitis C Virus resistance screening and phenotypic NS3-PI-Resistance characterization. Arevir Meeting, 08./09.05.

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1 Hepatitis C Virus resistance screening and phenotypic NS3-PI-Resistance characterization Arevir Meeting, 08./ Daniel Rupp

2 HCV prevalence million patients world wide Ca. 75% of infections cannot be cleared Genotype-distribution varies dependent on the country Adapted from Hajarizadeh, B. et al. (2013) Nat. Rev. Gastroenterol. Hepatol.

3 Chronic HCV infection is a serious health burden HE-stain healthy liver tissue Trichrome stain liver cirrhosis depts.washington.edu/hepstudy/definitions en.wikipedia.org

4 Milestones in HCV research Michael P. Manns and Thomas von Hahn, Nat Rev Drug Discov, 2013

5 Milestones in HCV research Michael P. Manns and Thomas von Hahn, Nat Rev Drug Discov, 2013

6 Genomic organization of HCV single ORF flanked by non-translated regions polyprotein posttranslationally processed by cellular and viral proteases adapted from Rupp and Bartenschlager, Seminars in Liver Disease, 2014

7 HCV replication cycle 1. entry 2. polyprotein synthesis and processing 3. membrane remodeling 4. RNA replication 5. virion assembly and release adapted from Rupp and Bartenschlager, Seminars in Liver Disease, 2014

8 Milestones in HCV research Michael P. Manns and Thomas von Hahn, Nat Rev Drug Discov, 2013

9 Development of antiviral HCV therapy Michael P. Manns and Thomas von Hahn, Nat Rev Drug Discov, 2013

10 Development of antiviral HCV therapy Michael P. Manns and Thomas von Hahn, Nat Rev Drug Discov, 2013

11 Milestones in HCV research Harvoni Michael P. Manns and Thomas von Hahn, Nat Rev Drug Discov, 2013

12 Aims of the PEPSI-project 1. Generation of lab protocols for HCV subtyping and DAAsresistance determination (genotypic and phenotypic) NS5B, NS5A, NS3 regions of HCV 2. Development of geno2pheno [HCV] a free online tool, to predict DAA-containing therapy outcome

13 RT-PCR and sequencing protocols NS3 Boceprevir, Telaprevir, Simeprevir NS5A Daclatasvir, Ledipasvir, Ombitasvir NS5B Sub-Genotyping and Resistance to Sofosbuvir and Dasabuvir in cooperation with Joerg Timm, Andreas Walker, Martin Däumer, Alex Thielen, Martin Obermeier, Hauke Walter

14 Patients enrolled in the PEPSI study N of enrolled patients FIG. 1: Number of patients enrolled in the PEPSI Study With the release of the new DAAs 2014, the amount of patients starting HCV treatment increased. TVR and BOC had been approved in 2011.

15 Presence of Q80K in the PEPSI cohort 40 GT 1a Clade I Clade II Y= number of patients from the PEPSI-cohort

16 Phenotypic characterization - aims Characterization of Resistance Associated Mutations (RAM) - Influence of RAMs, polymorphisms and fitness on drug susceptibility in an in vitro model - Characterization of novel RAMs - Obtained data help improving bioinformatic prediction algorithms (e.g. geno2pheno)

17 Experimental concept

18 Experimental concept Introduce unique restriction sites and delete a large proportion of the NS3-protease

19 Experimental concept Introduce unique restriction sites and delete a large proportion of the NS3-protease Introduce patient derived NS3-protease sequences and restore replication competence

20 Workflow: genotypic and phenotypic characterization

21 Workflow: genotypic and phenotypic characterization

22 Workflow: genotypic and phenotypic characterization

23 Via site directed mutagenesis generated RAMs show considerable IC50 shifts Introduction of Resistance Associatd Mutations (RAMs) into the replicon sequence impair replication fitness compared to wildtype

24 Via site directed mutagenesis generated RAMs show considerable IC50 shifts Telaprevir Boceprevir Titration experiments show a considderable shift of IC50 values

25 Via site directed mutagenesis generated RAMs show considerable IC50 shifts Telaprevir Boceprevir Titration experiments show a considderable shift of IC50 values

26 Possible applications for phenotypic characterization 1. Characterize interesting mutation patterns detected in patients 2. Characterize possible new RAMs 3. Evaluate prognostic value of phenptyping and check for possible influence of comorbidities

27 Characterize interesting mutation patterns detected in patients

28 Characterize interesting mutation patterns detected in patients

29 Characterize interesting mutation patterns detected in patients Most samples show concordant IC50 fold-change values in the G2P-prediction and the phenotypic characterization No possible new RAMs identified in samples with resistance in phenotypic assay but not in the G2P prediction Rare RAMs detected via deep sequencing do not contribute to actual resistance profile too low frequency?

30 Characterize possible new RAMs Experimental Faldaprevir treatment (orange) Q80L present in 1% of viruses prior to treatment and in 100% post treatment

31 Characterize possible new RAMs Fitness No impairment of replication fitness Overlapping titration curves for BOC and TVR No cross-resistance Telaprevir Boceprevir

32 Evaluate prognostic value of phenptyping SVR (n=54) failure (n=33) Phenotypic characterization of baseline Prediction of therapy outcome?

33 Evaluate prognostic value of phenptyping Telaprevir Boceprevir n.s. ** p = Whitney-Mann-U-Test p = Whitney-Mann-U-Test Telaprevir susceptibility prior to treatment does not allow prediction of therapy outcome patients achieving SVR do show higher IC50 fold change values for Boceprevir compared to those failing therapy

34 Evaluate prognostic value of phenptyping gt1a Telaprevir Boceprevir n.s. * p = p = gt1b n.s. * p = p = Same trend persists if samples are sorted by HCV genotype

35 and check for possible influence of comorbidities Telaprevir Boceprevir ** *** p = Whitney-Mann-U-Test p = Whitney-Mann-U-Test Replicon libraries from patients with cirrhosis show lower IC50-FC values

36 and check for possible influence of comorbidities cirrhosis Telaprevir Boceprevir n.s. * No cirrhosis p = p = n.s. n.s. p = p = Similar distribution of IC50 FC values of patients with same comorbidity

37 Outlook Prepare replicon system to characterize patient-derived NS5Asequences Characterize genotype-specific RAMs Evaluate susceptibility/resistance profile of libraries for different NS3-protease inhibitors Simeprevir Paritaprevir

38 Summary Bulk sequencing in most cases concordant with phenotypic characterization Deep sequencing overestimates actual resistance profile Phenotypic resistance characterization can identify/exclude newly discovered Resistance Associated Mutations Phenotypic resistance characterization of baseline samples prior to treatment alone is not suitable to predict therapy outcome Comorbidities seem to influence the resistance profile of the HCV quasispecies pool

39 Acknowledgements Ralf Bartenschlager Kevin Lu Ulrike Protzer Hanaa Gaber Thomas Pietschmann Richard J. P. Brown Rolf Kaiser Saleta Sierra-Aragón Thomas von Hahn Christoph Sarrazin Sandra Ciesek Julia Dietz Anna Marie Sikorski Arevir Meeting, Cologne 04./