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Bioinformatics analysis revealed hub genes and pathways involved in sorafenib resistance in hepatocellular carcinoma

Department of Pharmacy, The Fifth People’s Hospital of Shanghai, Fudan University, Shanghai 200240, China

Special Issues: Advanced Big Data Analysis for Precision Medicine

Hepatocellular carcinoma (HCC) is increasingly known as a serious, worldwide public health concern. Sorafenib resistance is the main challenge faced by many advanced HCC patients. The specific mechanisms of sorafenib resistance remind unclear. In the current study, GEO2R was conducted to identify differentially expressed genes (DEGs) between sorafenib-resistant samples and the control group by using RNA-sequence analysis and analyzing dataset GSE109211. Next, protein-protein interaction (PPI) network was built to explore key targets proteins in sorafenib-resistant HCC. Furthermore, gene ontology (GO) analysis was used to research the underlying roles of key proteins. Moreover, the Kaplan-Meier survival analysis was performed to display the effect of key proteins on overall survival in HCC. Western blotting was performed to detected resistance-related proteins and CCK-8 assay was employed to measured cell viability. In the present research, 164 sorafenib resistance-related DEGs in HCC were identified by using RNA-sequence analysis and analyzing the dataset GSE109211. GO analysis revealed DEGs were involved in regulating multiple biological processes and molecular functions. DYNLL2, H2AFJ, SHANK2, ZWILCH, CDC14A, IFT20, MTA3, SERPINA1 and TCF4 were confirmed as key genes in this process. Moreover, our study showed Akt signaling was aberrantly activated and inhibition of Akt signaling enhanced anti-tumor capacity of sorafenib in sorafenib-resistant HCC cells. Identification of the DEGs in sorafenib resistant HCC cells may further provide the new insights of underlying sorafenib-resistant mechanisms and offer latent targets for early diagnosis and new therapies to improve clinical efficacy for sorafenib-resistant HCC patients.
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© 2019 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

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