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Research Article

Differential Network Analysis Depicts Regulatory Mechanisms for Hepatocellular Carcinoma from Diverse Backgrounds

ORCID Icon, , , , , , , , , , & show all
Pages 3917-3934 | Received 13 May 2019, Accepted 30 Sep 2019, Published online: 15 Nov 2019
 

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.

Supplementary data

To view the supplementary data that accompany this paper please visit the journal website at: www.tandfonline.com/doi/suppl/10.2217/fon-2019-0275

Author contributions

X Yang conceived and designed the present study. MC Yu and JX Liu performed the experiments and analyzed the data. JX Liu validated and improved the computational approach in this study. XL Ma and MC Yu wrote the manuscript. All authors read and approved the final manuscript.

Financial & competing interests disclosure

The current study was supported by National Key Research and Development Program (grant number: 2016YFC0902400, 2018YFC0910500), National Science and Technology Major Project (grant number: 2017ZX10203204-006-002), National Natural Science Funds of China (grant number: 81802364, 81372317, 81572884,81672736), Shanghai Hospital Development Center (grant number: SHDC12015104) Zhongshan Hospital Science Foundation (2018ZSQN28), Shanghai Municipal Science and Technology Major Project (2017SHZDZX01), Shanghai Municipal Commission of Science and Technology (14DZ2252000). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

No writing assistance was utilized in the production of this manuscript.

Availability of data & materials

All data generated or analyzed during this study are included in this published article.

Additional information

Funding

The current study was supported by National Key Research and Development Program (grant number: 2016YFC0902400, 2018YFC0910500), National Science and Technology Major Project (grant number: 2017ZX10203204-006-002), National Natural Science Funds of China (grant number: 81802364, 81372317, 81572884,81672736), Shanghai Hospital Development Center (grant number: SHDC12015104) Zhongshan Hospital Science Foundation (2018ZSQN28), Shanghai Municipal Science and Technology Major Project (2017SHZDZX01), Shanghai Municipal Commission of Science and Technology (14DZ2252000). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. No writing assistance was utilized in the production of this manuscript.

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