Identification and Analysis of the Blood lncRNA Signature for Liver Cirrhosis and Hepatocellular Carcinoma

Frontiers in Genetics

Min Zhang³  Zheyue Shu³  Qi Xia⁵  Ting Ye⁵ 

[1] Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China;Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China;Key Laboratory of Combined Multi-Organ Transplantation, Ministry of Public Health, Hangzhou, China;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, College of Medicine, Zhejiang University, Hangzhou, China;Zhejiang University, Hangzhou, China;

关键词: hepatocellular carcinoma;    hepatitis B virus;    lncRNA;    liver cirrhosis;    support vector machine;   

DOI  :  10.3389/fgene.2020.595699

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown