Prediction of hepatocellular carcinoma risk in patients with chronic liver disease from dynamic modular networks

Yinying Chen,Wei Yang,Jun Liu,Dongfeng Li,Qiong Liu,Yehui Peng,Xiaodong Li,Huikun Wu,Shibing Su,Jie Wang,Xinghua Xiang,Zhong Wang,Qilong Chen,Bing Li,Yingying Zhang,Jingyi Nan

doi:10.1186/s12967-021-02791-9

Abstract

BackgroundDiscovering potential predictive risks in the super precarcinomatous phase of hepatocellular carcinoma (HCC) without any clinical manifestations is impossible under normal paradigm but critical to control this complex disease.MethodsIn this study, we utilized a proposed sequential allosteric modules (AMs)-based approach and quantitatively calculated the topological structural variations of these AMs.ResultsWe found the total of 13 oncogenic allosteric modules (OAMs) among chronic hepatitis B (CHB), cirrhosis and HCC network used SimiNEF. We obtained the 11 highly correlated gene pairs involving 15 genes (r > 0.8, P < 0.001) from the 12 OAMs (the out-of-bag (OOB) classification error rate < 0.5) partial consistent with those in independent clinical microarray data, then a three-gene set (cyp1a2-cyp2c19-il6) was optimized to distinguish HCC from non-tumor liver tissues using random forests with an average area under the curve (AUC) of 0.973. Furthermore, we found significant inhibitory effect on the tumor growth of Bel-7402, Hep 3B and Huh7 cell lines in zebrafish treated with the compounds affected those three genes.ConclusionsThese findings indicated that the sequential AMs-based approach could detect HCC risk in the patients with chronic liver disease and might be applied to any time-dependent risk of cancer.

Highlights

Discovering potential predictive risks in the super precarcinomatous phase of hepatocellular carcinoma (HCC) without any clinical manifestations is impossible under normal paradigm but critical to control this complex disease
We found that the two-gene set appeared in the same oncogenic allosteric modules (OAMs) (AMOCHB 11-HCC6)
Sequential allosteric modules (AMs) contributed to revealing the dynamic evolution from chronic hepatitis B (CHB) to cirrhosis and Hepatocellular carcinoma (HCC) The clinical pathway of most hepatitis B virus (HBV)-related HCC may follow the four states: healthy, hepatitis, cirrhosis, and HCC

Summary

Introduction

Discovering potential predictive risks in the super precarcinomatous phase of hepatocellular carcinoma (HCC) without any clinical manifestations is impossible under normal paradigm but critical to control this complex disease. Hepatocellular carcinoma (HCC) is the most common primary liver cancer with poor prognosis. Some serum or tissue biomarkers for the diagnosis of HCC have been successfully identified [7]. Previous research has focused on identifying risk of preclinical HCC for screening the early. Despite progress in diagnostics and treatment of HCC, its prognosis remains poor [9, 10]. Can we identify predictive risk for HCC at an earlier stage?

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Discussion

Conclusion