J Cancer 2019; 10(26):6526-6534. doi:10.7150/jca.33666

Research Paper

Bioinformatics analysis of differentially expressed genes in hepatocellular carcinoma cells exposed to Swertiamarin

Haoran Tang1*, Yang Ke2*, Zongfang Ren3*, Xuefen Lei4*, Shufeng Xiao2*, Tianhao Bao5*, Zhitian Shi2, Renchao Zou2, Tiangen Wu2, Jian Zhou2, Chang-An Geng6, Lin Wang2✉, Jijun Chen6✉

1. Department of Gastroenterological Surgery, the Second Affiliated Hospital of Kunming Medical University, Kunming, China.
2. Department of Hepatobiliary Surgery, the Second Affiliated Hospital of Kunming Medical University, Kunming, China.
3. Department of Critical Care Medicine, the Second Affiliated Hospital of Kunming Medical University, Kunming, China.
4. Department of Oncology, the Second Affiliated Hospital of Kunming Medical University, Kunming, China.
5. Mental Health Center, Kunming Medical University, Kunming, China.
6. State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, PR China.
* These authors share the first authorship.

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Citation:
Tang H, Ke Y, Ren Z, Lei X, Xiao S, Bao T, Shi Z, Zou R, Wu T, Zhou J, Geng CA, Wang L, Chen J. Bioinformatics analysis of differentially expressed genes in hepatocellular carcinoma cells exposed to Swertiamarin. J Cancer 2019; 10(26):6526-6534. doi:10.7150/jca.33666. Available from http://www.jcancer.org/v10p6526.htm

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Abstract

Aim: To explore gene expression profiling in hepatocellular carcinoma (HCC) cells exposed to swertiamarin.

Methods: Cell viability, apoptosis and invasion were examined in HepG2 cells after swertiamarin treatment. Tumor growth of SK-Hep-1 cells xenografted in nude mice was monitored after swertiamarin treatment. Total RNA was isolated from HepG2 cells treated with swertiamarin for microarray analysis. The data of microarray were analyzed by bioinformatics.

Results: Swertiamarin treatment decreased the viability and invasion while increased the apoptosis of HepG2 cells, and significantly inhibited the growth of SK-Hep-1 cells xenografted in nude mice. Pathway and biological process analysis of differentially expressed genes (DEGs) in swertiamarin treated HepG2 cells showed that PI3k-Akt was the most significant regulated pathway. 47 targets of swertiamarin were predicted by CGBVS while 21 targets were predicted by 3NN. Notably, 8 targets were predicted as the targets of swertiamarin by both programs, including two prominent targets JUN and STAT3. A large range of DEGs induced by swertiamarin could be regulated by JUN and STAT3.

Conclusion: Swertiamarin treatment led to significant changes in the expression of a variety of genes that modulate cell survival, cell cycle progression, apoptosis, and invasion. Moreover, most of these genes can be clustered into pathway networks such as PI3K, JUN, STAT3, which are predicted targets of swertiamarin. Further confirmation of these targets will reveal the anti-tumor mechanisms of swertiamarin and facilitate the development of swertiamarin as a novel agent for cancer prevention and treatment.

Keywords: swertiamarin, microarray, HepG2 cells, hepatocellular cancer, Jun, Stat3