Abstract

Developing predictive biomarkers that can detect the tipping point before metastasis of hepatocellular carcinoma (HCC), is critical to prevent further irreversible deterioration. To discover such early-warning signals or biomarkers of pulmonary metastasis in HCC, we analyse time-series gene expression data in spontaneous pulmonary metastasis mice HCCLM3-RFP model with our dynamic network biomarker (DNB) method, and identify CALML3 as a core DNB member. All experimental results of gain-of-function and loss-of-function studies show that CALML3 could indicate metastasis initiation and act as a suppressor of metastasis. We also reveal the biological role of CALML3 in metastasis initiation at a network level, including proximal regulation and cascading influences in dysfunctional pathways. Our further experiments and clinical samples show that DNB with CALML3 reduced pulmonary metastasis in liver cancer. Actually, loss of CALML3 predicts shorter overall and relapse-free survival in postoperative HCC patients, thus providing a prognostic biomarker and therapy target in HCC.

Details

Title
Dynamic network biomarker indicates pulmonary metastasis at the tipping point of hepatocellular carcinoma
Author
Yang, Biwei 1 ; Li, Meiyi 2 ; Tang, Wenqing 1 ; Liu, Weixin 3 ; Zhang, Si 4 ; Chen, Luonan 3 ; Xia, Jinglin 5 

 Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China 
 Minhang Branch, Zhongshan Hospital, Fudan University/Institute of Fudan-Minhang Academic Health System, Minhang Hospital, Fudan University, Shanghai, China; Key Laboratory of Systems Biology, CAS Center for Excellence in Molecular Cell Science, CAS Center for Excellence in Animal Evolution and Genetics, Innovation Center for Cell Signaling Network, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, China 
 Key Laboratory of Systems Biology, CAS Center for Excellence in Molecular Cell Science, CAS Center for Excellence in Animal Evolution and Genetics, Innovation Center for Cell Signaling Network, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, China; School of Life Science and Technology, ShanghaiTech University, Shanghai, China 
 Key Laboratory of Glycoconjugate Research Ministry of Public Health, Department of Biochemistry and Molecular Biology, Shanghai Medical College, Fudan University, Shanghai, China 
 Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China; Minhang Branch, Zhongshan Hospital, Fudan University/Institute of Fudan-Minhang Academic Health System, Minhang Hospital, Fudan University, Shanghai, China 
Pages
1-14
Publication year
2018
Publication date
Feb 2018
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2002200636
Copyright
© 2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.