Dataset Information

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

ABSTRACT:

Background

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.

Methods

In this study, we utilized a proposed sequential allosteric modules (AMs)-based approach and quantitatively calculated the topological structural variations of these AMs.

Results

We 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.

Conclusions

These 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.

SUBMITTER: Chen Y

PROVIDER: S-EPMC7989040 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Publications

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

Chen Yinying Y Yang Wei W Chen Qilong Q Liu Qiong Q Liu Jun J Zhang Yingying Y Li Bing B Li Dongfeng D Nan Jingyi J Li Xiaodong X Wu Huikun H Xiang Xinghua X Peng Yehui Y Wang Jie J Su Shibing S Wang Zhong Z

Journal of translational medicine 20210323 1

<h4>Background</h4>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.<h4>Methods</h4>In this study, we utilized a proposed sequential allosteric modules (AMs)-based approach and quantitatively calculated the topological structural variations of these AMs.<h4>Results</h4>We found the total of 13 oncogenic allosteric modules ...[more]

PMID: 33757544

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Project description:Hepatocellular carcinoma (HCC) is a worldwide health problem. HCC patients show a 50% mortality within two years of diagnosis. To better understand the molecular pathogenesis at the level of lipid metabolism, untargeted UPLC MS-QTOF lipidomics data were acquired from resected human HCC tissues and their paired nontumor hepatic tissues (n = 46). Blood samples of the same HCC subjects (n = 23) were compared to chronic liver disease (CLD) (n = 15) and healthy control (n = 15) blood samples. The participants were recruited from the National Liver Institute in Egypt. The lipidomics data yielded 604 identified lipids that were divided into six super classes. Five-hundred and twenty-four blood lipids were found as significantly differentiated (p < 0.05 and qFDR p < 0.1) between the three study groups. In the blood of CLD patients compared to healthy control subjects, almost all lipid classes were significantly upregulated. In CLD patients, triacylglycerides were found as the most significantly upregulated lipid class at qFDR p = 1.3 × 10-56, followed by phosphatidylcholines at qFDR p = 3.3 × 10-51 and plasmalogens at qFDR p = 1.8 × 10-46. In contrast, almost all blood lipids were significantly downregulated in HCC patients compared to CLD patients, and in HCC tissues compared to nontumor hepatic tissues. Ceramides were found as the most significant lipid class (qFDR p = 1 × 10-14) followed by phosphatidylglycerols (qFDR p = 3 × 10-9), phosphatidylcholines and plasmalogens. Despite these major differences, there were also common trends in the transitions between healthy controls, CLD and HCC patients. In blood, several mostly saturated triacylglycerides showed a continued increase in the trajectory towards HCC, accompanied by reduced levels of saturated free fatty acids and saturated lysophospatidylcholines. In contrast, the largest overlaps of lipid alterations that were found in both HCC tissue and blood comparisons were decreased levels of phosphatidylglycerols and sphingolipids. This study highlights the specific impact of HCC tumors on the circulating lipids. Such data may be used to target lipid metabolism for prevention, early detection and treatment of HCC in the background of viral-related CLD etiology.

Dataset Information

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

Background

Methods

Results

Conclusions

Publications

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

Similar Datasets

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