Next-generation sequencing analysis of hepatitis C virus resistance–associated substitutions in direct-acting antiviral failure in South Korea

Abstract

Background/Aims: We analyzed resistance-associated substitutions (RAS) and retreatment outcomes in patients with chronic hepatitis C virus (HCV) infection who failed direct-acting antiviral agent (DAA) treatment in South Korea using next-generation sequencing (NGS).Methods: Using prospectively collected data from the Korea HCV cohort study, 36 patients who failed DAA treatment were recruited from 10 centers between 2007 and 2020; 29 blood samples were available from 24 patients. RASs were analyzed using NGS.Results: RAS was analyzed for 13 patients with genotype 1b, ten with genotype 2, and one with genotype 3a. The unsuccessful DAA regimens were daclatasvir+asunaprevir (n=11), sofosbuvir+ribavirin (n=9), ledipasvir/sofosbuvir (n=3), and glecaprevir/pibrentasvir (n=1). In patients with genotype 1b, NS3, NS5A, and NS5B RASs were detected in eight, seven, and seven out of ten patients at baseline and in four, six, and two out of six patients after DAA failure, respectively. Among ten patients with genotype 2, the only baseline RAS was NS3 Y56F, detected in one patient. NS5A F28C was detected after DAA failure in a patient with genotype 2 infection erroneously treated with daclatasvir+asunaprevir. After retreatment 16 patients had a 100% sustained virological response rate.Conclusions: NS3 and NS5A RASs were commonly present at baseline, and there was an increasing trend of NS5A RAS after failed DAA treatment in genotype 1b. However, RAS was rarely present in patients with genotype 2 treated with sofosbuvir plus ribavirin. Despite baseline or treatment-emergent RAS, retreatment with pan-genotypic DAA was highly successful in Korea, encouraging active retreatment for unsuccessful DAA treatment.

Correspondence on Letter regarding “Toward hepatitis C virus elimination using artificial intelligence”

“…may simultaneously affect the efficacy of DAA. [3][4][5][6] A combination of multi-omics in the AI model may enhance the predictive accuracy of the validation datasets in the future. Furthermore, all the subjects were enrolled from a single ethnic population.…”

“…The diversity of host genetics, cytokine dynamics, immunity, metabolism, baseline or treatment-emergent resistance-associated substitutions of HCV, etc. may simultaneously affect the efficacy of DAA [ 3 - 6 ]. A combination of multi-omics in the AI model may enhance the predictive accuracy of the validation datasets in the future.…”