HBV-infected hepatocellular carcinoma can be robustly classified into three clinically relevant subgroups by a novel analytical protocol

Author:

Cheng Zhiwei12ORCID,Li Leijie12,Zhang Yuening12,Ren Yongyong2,Gu Jianlei3,Wang Xinbo12,Zhao Hongyu3,Lu Hui124

Affiliation:

1. Shanghai Jiao Tong University State Key Lab of Microbial Metabolism, Joint International Research Laboratory of Metabolic Developmental Sciences, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology,

2. Shanghai Jiao Tong University SJTU-Yale Joint Center of Biostatistics and Data Science, National Center for Translational Medicine,

3. Yale University Department of Biostatistics, , New Haven, CT, United States

4. Affiliated to Shanghai Jiao Tong University School of Medicine Department of General Surgery, Xinhua Hospital, , Shanghai, China

Abstract

AbstractLiver cancer is the third leading cause of cancer-related death worldwide, and hepatocellular carcinoma (HCC) accounts for a relatively large proportion of all primary liver malignancies. Among the several known risk factors, hepatitis B virus (HBV) infection is one of the important causes of HCC. In this study, we demonstrated that the HBV-infected HCC patients could be robustly classified into three clinically relevant subgroups, i.e. Cluster1, Cluster2 and Cluster3, based on consistent differentially expressed mRNAs and proteins, which showed better generalization. The proposed three subgroups showed different molecular characteristics, immune microenvironment and prognostic survival characteristics. The Cluster1 subgroup had near-normal levels of metabolism-related proteins, low proliferation activity and good immune infiltration, which were associated with its good liver function, smaller tumor size, good prognosis, low alpha-fetoprotein (AFP) levels and lower clinical stage. In contrast, the Cluster3 subgroup had the lowest levels of metabolism-related proteins, which corresponded with its severe liver dysfunction. Also, high proliferation activity and poor immune microenvironment in Cluster3 subgroup were associated with its poor prognosis, larger tumor size, high AFP levels, high incidence of tumor thrombus and higher clinical stage. The characteristics of the Cluster2 subgroup were between the Cluster1 and Cluster3 groups. In addition, MCM2–7, RFC2–5, MSH2, MSH6, SMC2, SMC4, NCPAG and TOP2A proteins were significantly upregulated in the Cluster3 subgroup. Meanwhile, abnormally high phosphorylation levels of these proteins were associated with high levels of DNA repair, telomere maintenance and proliferative features. Therefore, these proteins could be identified as potential diagnostic and prognostic markers. In general, our research provided a novel analytical protocol and insights for the robust classification, treatment and prevention of HBV-infected HCC.

Funder

Innovative Research Team of High-Level Local Universities in Shanghai

SJTU-Yale Collaborative Research Seed Fund

The Neil Shen’s SJTU Medical Research Fund

National Key R&D Program of China

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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