Min-Cheng Yu1, Ji-Xiang Liu2, Xiao-Lu Ma3, Bo Hu1, Pei-Yao Fu1, Hai-Xiang Sun1, Wei-Guo Tang4, Zhang-Fu Yang1, Shuang-Jian Qiu1, Jian Zhou1,5,6, Jia Fan1,5,6, Yang Xu1. 1. Department of Liver Surgery & Transplantation, Zhongshan Hospital, Fudan University; Key Laboratory of Carcinogenesis & Cancer Invasion (Fudan University), Ministry of Education, Shanghai 200032, PR China. 2. Shanghai Center for Bioinformation Technology & Shanghai Engineering Research Center of Pharmaceutical Translation, Shanghai Industrial Technology Institute, 1278 Keyuan Road, Shanghai 201203, PR China. 3. Department of Laboratory Medicine, Shanghai Cancer Center, Fudan University, Shanghai 200032, PR China. 4. Institute of Fudan-Minhang Academic Health System, Minhang Hospital, Fudan University, Shanghai 201199, PR China. 5. State Key Laboratory of Genetic Engineering, Fudan University, Shanghai 200032, PR China. 6. Institute of Biomedical Sciences, Fudan University, Shanghai 200032, PR China.
Abstract
Aim: To elucidate the integrative combinational gene regulatory network landscape of hepatocellular carcinoma (HCC) molecular carcinogenesis from diverse background. Materials & methods: Modified gene regulatory network analysis was used to prioritize differentially regulated genes and links. Integrative comparisons using bioinformatics methods were applied to identify potential critical molecules and pathways in HCC with different backgrounds. Results: E2F1 with its surrounding regulatory links were identified to play different key roles in the HCC risk factor dysregulation mechanisms. Hsa-mir-19a was identified as showed different effects in the three HCC differential regulation networks, and showed vital regulatory role in HBV-related HCC. Conclusion: We describe in detail the regulatory networks involved in HCC with different backgrounds. E2F1 may serve as a universal target for HCC treatment.
Aim: To elucidate the integrative combinational gene regulatory network landscape of hepatocellular carcinoma (HCC) molecular carcinogenesis from diverse background. Materials & methods: Modified gene regulatory network analysis was used to prioritize differentially regulated genes and links. Integrative comparisons using bioinformatics methods were applied to identify potential critical molecules and pathways in HCC with different backgrounds. Results:E2F1 with its surrounding regulatory links were identified to play different key roles in the HCC risk factor dysregulation mechanisms. Hsa-mir-19a was identified as showed different effects in the three HCC differential regulation networks, and showed vital regulatory role in HBV-related HCC. Conclusion: We describe in detail the regulatory networks involved in HCC with different backgrounds. E2F1 may serve as a universal target for HCC treatment.