چکیده انگلیسی:
Background: Even with the fantastic successes of direct-acting antivirals (DAA) in the treatment of Hepatitis C Virus (HCV) infection, natural drug resistance remains a challenging obstacle for their impacts. The data regarding protease inhibitors (PIs) resistance in Iran population are limited. The aim of this study was to investigate the variations in NS3 protease of HCV from non-responder patients. Methods: In this cross-sectional study, 14 HCV infected patients with genotype 1(N=5) and 3(N=9) who have not responded to Interferon-related regime were enrolled from Liver Clinic, Shiraz. The NS3 protease region was amplified by Nested-PCR followed by product gel extraction. Besides, some amplified protease regions were cloned into a cloning vector to improve the sensitivity of mutation detection. Both crude and cloned sequences were then introduced into sequencing. The obtained sequences were compared with the NS3 reference sequences and analyzed by Geno2pheno available software to find possible substitutions. In the end, the phylogenetic tree was constructed. Results: Among variations responsible for PIs resistance, only one out of 14 (7%) sample who was infected with genotype 1a, harbored R117C+N174S double mutation, which causes reduced susceptibility to Telaprevir. Any another resistance mutation was not found among the studied population. The most frequent substitutions were determined as I52M(N=9), S102A(N=9), S166A(8) and V170I(8) for genotype 3a, and F147S/A(4) for genotype 1. However, some uncharacterized substitutions on scored position, including I132L(N=1), I170V(N=3) and N174S(N=2) were also determined among sequences. Phylogenetic analysis demonstrated that the protease region has enough power to correctly classify enrolled samples into relevant clusters on the tree. There were 2, 3 and 9 cases of sub-genotypes 1a, 1b, and 3a, respectively. Conclusion: A low frequency of PIs resistance mutations in our HCV infected population is a hopeful point of starting these drugs in HCV infected patients.
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