Department of Laboratory Medicine, Eastern Hepatobiliary Surgery Hospital, Navy Military Medical University, Shanghai, 200438, China.
Department of Laboratory Medicine, The 901th Hospital of Joint Logistics Support Force of Chinese People's Liberation Army, Hefei, 230031, China.
Virol J. 2022 Jun 28;19(1):114. doi: 10.1186/s12985-022-01836-9.
Chronic infection with hepatitis B virus (HBV) has been proved highly associated with the development of hepatocellular carcinoma (HCC).
The purpose of the study is to investigate the association between HBV preS region quasispecies and HCC development, as well as to develop HCC diagnosis model using HBV preS region quasispecies.
A total of 104 chronic hepatitis B (CHB) patients and 117 HBV-related HCC patients were enrolled. HBV preS region was sequenced using next generation sequencing (NGS) and the nucleotide entropy was calculated for quasispecies evaluation. Sparse logistic regression (SLR) was used to predict HCC development and prediction performances were evaluated using receiver operating characteristic curves.
Entropy of HBV preS1, preS2 regions and several nucleotide points showed significant divergence between CHB and HCC patients. Using SLR, the classification of HCC/CHB groups achieved a mean area under the receiver operating characteristic curve (AUC) of 0.883 in the training data and 0.795 in the test data. The prediction model was also validated by a completely independent dataset from Hong Kong. The 10 selected nucleotide positions showed significantly different entropy between CHB and HCC patients. The HBV quasispecies also classified three clinical parameters, including HBeAg, HBVDNA, and Alkaline phosphatase (ALP) with the AUC value greater than 0.6 in the test data.
Using NGS and SLR, the association between HBV preS region nucleotide entropy and HCC development was validated in our study and this could promote the understanding of HCC progression mechanism.
乙型肝炎病毒（HBV）慢性感染已被证实与肝细胞癌（HCC）的发生高度相关。
本研究旨在探讨 HBV preS 区准种与 HCC 发生发展的关系，并利用 HBV preS 区准种建立 HCC 诊断模型。
共纳入 104 例慢性乙型肝炎（CHB）患者和 117 例 HBV 相关 HCC 患者。采用下一代测序（NGS）对 HBV preS 区进行测序，并计算核苷酸熵以评估准种。稀疏逻辑回归（SLR）用于预测 HCC 发生，采用受试者工作特征曲线（ROC）评估预测性能。
HBV preS1、preS2 区和几个核苷酸点的熵在 CHB 和 HCC 患者之间存在显著差异。使用 SLR，在训练数据中 HCC/CHB 组的分类平均 ROC 曲线下面积（AUC）为 0.883，在测试数据中为 0.795。该预测模型还通过来自香港的完全独立数据集进行了验证。10 个选定的核苷酸位置在 CHB 和 HCC 患者之间的熵差异具有统计学意义。HBV 准种也可将 HBeAg、HBV DNA 和碱性磷酸酶（ALP）这三个临床参数分类，在测试数据中的 AUC 值大于 0.6。
本研究通过 NGS 和 SLR 验证了 HBV preS 区核苷酸熵与 HCC 发生发展之间的关系，这有助于深入了解 HCC 的发生机制。
