肝硬化和肝细胞癌血液lncRNA签名的鉴定和分析

StephenW

Identification and Analysis of the Blood lncRNA Signature for Liver Cirrhosis and Hepatocellular Carcinoma
Qi Xia  1   2   3 , Zheyue Shu  4   3 , Ting Ye  3 , Min Zhang  4   3
Affiliations
Affiliations

    1
    Department of Infectious Disease, State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
    2
    Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China.
    3
    Zhejiang University, Hangzhou, China.
    4
    Key Lab of Combined Multi-Organ Transplantation, Ministry of Public Health, Hangzhou, China.

    PMID: 33365048 PMCID: PMC7750531 DOI: 10.3389/fgene.2020.595699

Abstract

As one of the most common malignant tumors, hepatocellular carcinoma (HCC) is the fifth major cause of cancer-associated mortality worldwide. In 90% of cases, HCC develops in the context of liver cirrhosis and chronic hepatitis B virus (HBV) infection is an important etiology for cirrhosis and HCC, accounting for 53% of all HCC cases. To understand the underlying mechanisms of the dynamic chain reactions from normal to HBV infection, from HBV infection to liver cirrhosis, from liver cirrhosis to HCC, we analyzed the blood lncRNA expression profiles from 38 healthy control samples, 45 chronic hepatitis B patients, 46 liver cirrhosis patients, and 46 HCC patients. Advanced machine-learning methods including Monte Carlo feature selection, incremental feature selection (IFS), and support vector machine (SVM) were applied to discover the signature associated with HCC progression and construct the prediction model. One hundred seventy-one key HCC progression-associated lncRNAs were identified and their overall accuracy was 0.823 as evaluated with leave-one-out cross validation (LOOCV). The accuracies of the lncRNA signature for healthy control, chronic hepatitis B, liver cirrhosis, and HCC were 0.895, 0.711, 0.870, and 0.826, respectively. The 171-lncRNA signature is not only useful for early detection and intervention of HCC, but also helpful for understanding the multistage tumorigenic processes of HCC.

Keywords: hepatitis B virus; hepatocellular carcinoma; liver cirrhosis; lncRNA; support vector machine.

Copyright © 2020 Xia, Shu, Ye and Zhang.

StephenW

肝硬化和肝细胞癌血液lncRNA签名的鉴定和分析
栖霞1 2 3，折月书4 3，婷婷3，张敏4 3
隶属关系
隶属关系

    1个
    浙江大学医学院附属第一医院传染病诊治国家重点实验室传染病国家重点实验室，国家传染病临床研究中心，传染病诊治合作创新中心
    2
    浙江大学生物医学工程教育部重点实验室，杭州
    3
    浙江大学，杭州，中国。
    4
    公共卫生部组合式多器官移植重点实验室，杭州。

    PMID：33365048 PMCID：PMC7750531 DOI：10.3389 / fgene.2020.595699

抽象

肝细胞癌（HCC）作为最常见的恶性肿瘤之一，是全世界与癌症相关的死亡率的第五大主要原因。在90％的病例中，肝癌在肝硬化的背景下发展，慢性乙型肝炎病毒（HBV）感染是肝硬化和HCC的重要病因，占所有HCC病例的53％。为了了解从正常到HBV感染，从HBV感染到肝硬化，从肝硬化到HCC的动态链反应的潜在机制，我们分析了38例健康对照样本，45例慢性乙型肝炎患者，46例肝脏的血液lncRNA表达谱肝硬化患者和46例HCC患者。应用先进的机器学习方法，包括蒙特卡洛特征选择，增量特征选择（IFS）和支持向量机（SVM），以发现与HCC进展相关的特征并构建预测模型。鉴定了一百一十一种与HCC进展相关的关键lncRNA，经留一法交叉验证（LOOCV）评估，其总体准确性为0.823。健康对照，慢性乙型肝炎，肝硬化和HCC的lncRNA签名准确性分别为0.895、0.711、0.870和0.826。 171-lncRNA签名不仅可用于肝癌的早期检测和干预，而且有助于理解肝癌的多阶段致瘤过程。

关键词：乙型肝炎病毒；肝细胞癌；肝硬化lncRNA;支持向量机。

版权所有©2020 Xia，Shu，Ye和Zhang。

StephenW

https://www.frontiersin.org/arti ... ene.2020.595699/pdf