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Deep sequencing of HBV pre-S region reveals high heterogeneity of HBV genotypes and associations of word pattern frequencies with HCC.

ABSTRACT: Hepatitis B virus (HBV) infection is a common problem in the world, especially in China. More than 60-80% of hepatocellular carcinoma (HCC) cases can be attributed to HBV infection in high HBV prevalent regions. Although traditional Sanger sequencing has been extensively used to investigate HBV sequences, NGS is becoming more commonly used. Further, it is unknown whether word pattern frequencies of HBV reads by Next Generation Sequencing (NGS) can be used to investigate HBV genotypes and predict HCC status. In this study, we used NGS to sequence the pre-S region of the HBV sequence of 94 HCC patients and 45 chronic HBV (CHB) infected individuals. Word pattern frequencies among the sequence data of all individuals were calculated and compared using the Manhattan distance. The individuals were grouped using principal coordinate analysis (PCoA) and hierarchical clustering. Word pattern frequencies were also used to build prediction models for HCC status using both K-nearest neighbors (KNN) and support vector machine (SVM). We showed the extremely high power of analyzing HBV sequences using word patterns. Our key findings include that the first principal coordinate of the PCoA analysis was highly associated with the fraction of genotype B (or C) sequences and the second principal coordinate was significantly associated with the probability of having HCC. Hierarchical clustering first groups the individuals according to their major genotypes followed by their HCC status. Using cross-validation, high area under the receiver operational characteristic curve (AUC) of around 0.88 for KNN and 0.92 for SVM were obtained. In the independent data set of 46 HCC patients and 31 CHB individuals, a good AUC score of 0.77 was obtained using SVM. It was further shown that 3000 reads for each individual can yield stable prediction results for SVM. Thus, another key finding is that word patterns can be used to predict HCC status with high accuracy. Therefore, our study shows clearly that word pattern frequencies of HBV sequences contain much information about the composition of different HBV genotypes and the HCC status of an individual.

SUBMITTER: Bai X

PROVIDER: S-EPMC5841821 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Deep sequencing of HBV pre-S region reveals high heterogeneity of HBV genotypes and associations of word pattern frequencies with HCC.

Bai Xin X Jia Jian-An JA Fang Meng M Chen Shipeng S Liang Xiaotao X Zhu Shanfeng S Zhang Shuqin S Feng Jianfeng J Sun Fengzhu F Gao Chunfang C

PLoS genetics 20180223 2

Hepatitis B virus (HBV) infection is a common problem in the world, especially in China. More than 60-80% of hepatocellular carcinoma (HCC) cases can be attributed to HBV infection in high HBV prevalent regions. Although traditional Sanger sequencing has been extensively used to investigate HBV sequences, NGS is becoming more commonly used. Further, it is unknown whether word pattern frequencies of HBV reads by Next Generation Sequencing (NGS) can be used to investigate HBV genotypes and predict ...[more]

PMID: 29474353

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Project description:BackgroundHepatitis B virus (HBV) is one of the most prominent risk factors for hepatocellular carcinoma (HCC) development and virus-mediated cases represents more than 80% of HCC in East Asia, where it is endemic. Currently, the HBV status of pathological HCC is not fully clarified, especially by comparison to nontumorous tissues. Lack of clinicopathological animal models of HCC impedes clinical application of antiviral treatment in the field.Materials and methodsA cohort sample of 14 HCC and corresponding stroma tissues were analyzed for pathological patterns of HBV antigens using immunohistochemistry; 10 fresh primary tumor tissues were inoculated into NOD/SCID mice and risk factors for patient-derived xenograft (PDX) model were identified by the univariate F test. Consistency of HBV features and cellular biomarkers between patient tissues and tumor grafts were examined.ResultsIn HCC, HBV surface antigen (HBsAg) was mainly absent. Only 9.9% of samples showed HBsAg positivity in the tumor tissue that was limited to benign hepatocytes. In contrast, HBV core antigen (HBcAg) exhibited positive staining in all HCC tissues, located mainly in the cytoplasm of tumor cells. Of 14 HCC cases, three were diagnosed as occult infection of HBV based on HBcAg expression. The successful rate for the PDX model was 20% (2/10). Tumor lesions on hepatic lobes of V and VI, severe liver dysfunction and higher CA125 showed p-values of 0.01, 0.035, and 0.01, respectively. HBsAg absence in original tumors of #6 and 8 patients were faithfully reproduced by engraftments. Mixed distribution of HBcAg in cellular compartments of original tumor cells was also observed in mice. ki67 was dramatically increased in tumor grafts.ConclusionWe delineated pathological HBV profiles of HCC specimens and perilesional areas, which provided evidence for virus-based therapy in the future. PDX mice may phenocopy virological and cellular features of patient tissues, which is novel in the virus-related hepatocarcinogenesis field.

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Deep sequencing of HBV pre-S region reveals high heterogeneity of HBV genotypes and associations of word pattern frequencies with HCC.

Publications

Deep sequencing of HBV pre-S region reveals high heterogeneity of HBV genotypes and associations of word pattern frequencies with HCC.

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