基于突变积累的乙型肝炎向肝细胞癌的预警转变点识别用于HB

StephenW

基于突变积累的乙型肝炎向肝细胞癌的预警转变点识别用于HBV-HCC的早期诊断和潜在的药物治疗
徐飞 1 , 清康 1 , 冯武 2 , 王亚坤 1 , 杨文君 1 , 云彤 1 , 刘磊 1 , 陈秀杰 1
隶属关系
隶属关系

    1
    哈尔滨医科大学生物信息科学与技术学院药物基因组学系, 哈尔滨 150081
    2
    哈尔滨医科大学第二附属医院骨外科, 哈尔滨 150001

    PMID：36105485 PMCID：PMC9467738 DOI：10.1155/2022/3472179

抽象的

多个基因突变的积累在乙型肝炎诱发的肝细胞癌（HBV-HCC）的发生和发展过程中必不可少，但了解它们的协同作用并确定从乙型肝炎到HCC的预警转变点是一项挑战。在患者特异性蛋白质-蛋白质相互作用 (ps-PPI) 网络中对 HBV-HCC 患者体细胞突变的基因组分析中，我们发现突变影响可以沿着 ps-PPI 网络传播。因此，在本文中，我们使用 Random Walks with Restarts 算法将突变簇作为一个新的研究单元，该算法用于描述突变影响的有效边界。突变簇的连接导致HCC对应的信号通路失调，而失调的信号通路逐渐积累并经历一个从量变到质变的过程，包括一个关键的突变簇，称为从乙型肝炎到HCC的过渡点（TP）。此外，根据 TP 确定了两种预后不同的 HCC 患者亚型及其相应的生物学和临床特征。预后不良的 HCC 亚型与显着的代谢途径失调和较低的免疫细胞浸润有关，同时我们还确定了几种预防性药物来阻止乙型肝炎向肝细胞癌的转化。网络级研究整合了多组学数据，不仅显示了多个体细胞突变的序列及其协同效应，而且确定了每位患者 HCC 肿瘤发生的预警转变点。我们的研究为探索肝脏慢性炎症性恶性肿瘤的协同分子机制提供了新的视角，为开发早期预测和诊断肝细胞癌和个体化靶向治疗的新方法奠定了基础。

版权所有 © 2022 徐飞等。
利益冲突声明

作者没有需要声明的利益冲突。

StephenW

Identification of Warning Transition Points from Hepatitis B to Hepatocellular Carcinoma Based on Mutation Accumulation for the Early Diagnosis and Potential Drug Treatment of HBV-HCC
Fei Xu  1 , Qingkang Meng  1 , Feng Wu  2 , Yakun Wang  1 , Wenjun Yang  1 , Yun Tong  1 , Lei Liu  1 , Xiujie Chen  1
Affiliations
Affiliations

    1
    Department of Pharmacogenomics, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
    2
    Department of Orthopedic Surgery, The 2nd Affiliated Hospital of Harbin Medical University, Harbin 150001, China.

    PMID: 36105485 PMCID: PMC9467738 DOI: 10.1155/2022/3472179

Abstract

The accumulation of multiple genetic mutations is essential during the occurrence and development of hepatocellular carcinoma induced by hepatitis B (HBV-HCC), but understanding their cooperative effects and identifying the warning transition point from hepatitis B to HCC are challenges. In the genomic analysis of somatic mutations of the patient with HBV-HCC in a patient-specific protein-protein interaction (ps-PPI) network, we find mutation influence can propagate along the ps-PPI network. Therefore, in the article, we got the mutation cluster as a new research unit using the Random Walks with Restarts algorithm that is used to describe the efficient boundary of mutation influences. The connection of mutation cluster leads to dysregulation of signaling pathways corresponding to HCC, while dysregulated signaling pathways accumulate gradually and experience a process from quantitative to qualitative changes including a critical mutation cluster called transition point (TP) from hepatitis B to HCC. Moreover, two subtypes of HCC patients with different prognosis and their corresponding biological and clinical characteristics were identified according to TP. The poor prognosis HCC subtype was associated with significant metabolic pathway dysregulation and lower immune cell infiltration, while we also identified several preventive drugs to block the transformation of hepatitis B to hepatocellular carcinoma. The network-level study integrated multiomics data not only showed the sequence of multiple somatic mutations and their cooperative effect but also identified the warning transition point in HCC tumorigenesis for each patient. Our study provides new insight into exploring the cooperative molecular mechanism of chronic inflammatory malignancy in the liver and lays the foundation for the development of new approaches for early prediction and diagnosis of hepatocellular carcinoma and personalized targeted therapy.

Copyright © 2022 Fei Xu et al.
Conflict of interest statement

The authors have no conflicts of interest to declare.

StephenW

https://downloads.hindawi.com/journals/omcl/2022/3472179.pdf