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Ruihong Wu,1 Dongfeng Geng,2 Xiumei Chi,1 Xiaomei Wang,1 Xiuzhu Gao,1 Hongqin Xu,1 Ying Shi,1 Yazhe Guan,1 Yang Wang,1 Jinglan Jin,1 Yanhua Ding,3 Junqi Niu1 1Department of Hepatology, First Hospital of Jilin University, Changchun, Jilin Province 130021, People’s Republic of China; 2Centre for Reproductive Medicine, Centre for Prenatal Diagnosis, First Hospital of Jilin University, Changchun, Jilin Province 130021, People’s Republic of China; 3Phase I Clinical Research Center, The First Hospital of Jilin University, Changchun, Jilin Province 130021, People’s Republic of ChinaCorrespondence: Yanhua DingPhase I Clinical Research Center, The First Hospital of Jilin University, Changchun, Jilin Province 130021, People’s Republic of ChinaTel +86 4 318 878 2168Email dingyanhua2003@126.comJunqi NiuDepartment of Hepatology, The First Hospital of Jilin University, Changchun, Jilin Province 130021, People’s Republic of ChinaTel +86 4 318 187 5101Email junqiniu@aliyun.comBackground and objective: Direct-acting antivirals (DAA) facing resistance continue to be used in some areas worldwide. Thus, identifying hepatitis C virus (HCV) genotypes/subtypes and loci with certain prevalent resistance-associated substitutions (RASs) deserves attention. We investigated the global and regional frequencies of naturally occurring RASs among all confirmed HCV subtypes (n=86) and explored co-occurring and mutually exclusive RAS pairs within and between genes NS3, NS5A, and NS5B.Methods: A total of 213,908 HCV sequences available as of July 10, 2019 were retrieved from the NCBI nucleotide database. After curation, 17,312 NS3, 8,478 NS5A, and 25,991 NS5B sequence fragments from DAA-naïve patients were screened for RASs. MEGA 6.0 was used to translate aligned nucleotide sequences into amino acid sequences, and RAS pairs were identified by hypergeometric analysis.Results: RAS prevalence varied significantly among HCV subtypes. For example, D168E, highly resistanct to all protease inhibitors except voxilaprevir, was nearly absent in all subtypes except in 43.48% of GT5a sequences. RASs in NS3 exhibiting significantly different global distribution included Q80K in GT1a with the highest frequency in North America (54.49%), followed by in Europe (22.66%), Asia (6.98%), Oceania (6.62%), and South America (1.03%). The prevalence of NS3 S122G in GT1b was highest in Asia (26.6%) and lowest in Europe (2.64%). NS5A L28M, R30Q, and Y93H in GT1b, L31M in GT2b, and NS5B C316N in GT1b was most prevalent in Asia. A150V in GT3a, associated with sofosbuvir treatment failure, was most prevalent in Asia (44.09%), followed by Europe (31.19%), Oceania (24.29%), and North America (19.05%). Multiple mutually exclusive or co-occurring RAS pairs were identified, including Q80K+R155K and R155K+D168G in GT1a and L159F+C316N and R30Q (NS5A)+C316N (NS5B) in GT1b.Conclusion: Our data may be of special relevance for those countries where highly effective antivirals might not be available. Considering the specific RASs prevalence will help the clinicians to make optimal treatment choices. The RASs pairs would benefit anti-HCV drug development.Keywords: hepatitis C virus, direct-acting antiviral, resistance-associated substitution, subtype

Miaoxia Liu,1,2,* Ruihong Wu,1,3,* Xu Liu,1 Hongqin Xu,1 Xiumei Chi,1,3 Xiaomei Wang,1 Mengru Zhan,1 Bao Wang,1 Fei Peng,1 Xiuzhu Gao,1,3 Ying Shi,1 Xiaoyu Wen,1 Yali Ji,2 Qinglong Jin,1 Junqi Niu1 1Department of Hepatology, First Hospital of Jilin University, Changchun, Jilin Province 130021, People’s Republic of China; 2Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou 510515, People’s Republic of China; 3Phase I Clinical Research Center, First Hospital of Jilin University, Changchun, Jilin Province 130021, People’s Republic of China*These authors contributed equally to this workCorrespondence: Qinglong JinDepartment of Hepatology, First Hospital of Jilin University, 71 Xin Min Street, Changchun 130021, People’s Republic of ChinaTel/Fax +86-431-81875103Email jinql2016@163.comPurpose: GALAD is a statistical model for estimating the likelihood of having hepatocellular carcinoma (HCC) based on gender, age, AFP, AFP-L3, and PIVKA-II. We aimed to assess its performance and build new models in China, where hepatitis B virus (HBV) is the leading etiology of HCC.Patients and Methods: We built the GALAD-C model with the same five variables in GALAD, and the GAAP model with gender, age, AFP, and PIVKA-II, using logistic regression based on 242 patients with HCC and 283 patients with chronic liver disease (CLD). We also collected 50 patients with other malignant liver tumors (OMTs) and 50 healthy controls (HCs). A test dataset (169 patients with HCC and 139 with CLD) was used to test the performance of GAAP.Results: The GALAD-C and GAAP models achieved comparable performance (area under the receiver operating characteristic curve [AUC], 0.922 vs 0.914), and both were superior to GALAD, PIVKA-II, AFP, and AFP-L3% (AUCs, 0.891, 0.869, 0.750, and 0.711) for discrimination of HCC from CLD for the entire dataset. The AUCs of the GALAD, GALAD-C and GAAP models were excellent for the hepatitis C virus (HCV) subgroup (0.939, 0.958 and 0.954), and for discrimination HCC from HCs (0.988, 0.982, and 0.979), but were relatively lower for the HBV subgroup (0.855, 0.904, and 0.894), and for HCC within Milan Criteria (0.810, 0.841, and 0.840). They were not superior to AFP (0.873) for discrimination of HCC from OMT (0.873, 0.809, and 0.823). GAAP achieved an AUC of 0.922 in the test dataset.Conclusion: GALAD was excellent for discrimination of HCC from CLD in the HCV subgroup of a cohort of Chinese patients. The GAAP and GALAD-C models achieved better performance compared with GALAD. These three models exhibited better performance in patients with an HCV etiology than those with HBV.Keywords: hepatocellular carcinoma, alpha-fetoprotein, PIVKA-II, GALAD