Screening and bioinformatics analysis of circular RNA expression profiles in hepatitis B-related hepatocellular carcinoma

Article type: Research Article

Authors: Wang, Shanshan^{a; d; 1} | Cui, Shichang^{b; 1} | Zhao, Wenming^a | Qian, Zhiling^b | Liu, Hui^c | Chen, Yuhan^a | Lv, Fudong^c | Ding, Hui-Guo^{b; *}

Affiliations: [a] Department of Hepatology and Gastroenterology, Beijing You’an Hospital, Capital Medical University, Beijing 100069, China | [b] Interventional Center for Oncology, Beijing You’an Hospital, Capital Medical University, Beijing 100069, China | [c] Department of Pathology, Beijing You’an Hospital, Capital Medical University, Beijing 100069, China | [d] Beijing Institute of Hepatology, Beijing 100069, China

Correspondence: [*] Corresponding author: Hui-Guo Ding, Department of Gastroenterology and Hepatology, Beijing You’an Hospital, affiliated with Capital Medical University, Fengtai District, Beijing 100069, China. Tel.: +86 10 83997155; Fax: +86 10 63295525; E-mail: [email protected].

Note: [1] Co-first authors.

Abstract: BACKGROUND: Circular RNAs (circRNAs) play an important role in pathogenesis and development of hepatocellular carcinoma (HCC). However, circRNA expression profiles in hepatitis B Virus (HBV)-related HCC remain to be studied. METHODS: Total 13 HBV-related HCC patients were enrolled for study. Three HCC and 3 paired adjacent non-tumorous (NT) tissues from 3 patients were performed for microarray. Ten pairs of HCC tissues were used to verify the identified up-regulated and down-regulated circRNAs obtained from the microarray data by quantitative real-time reverse transcription PCR (qRT-PCR). Total RNA was isolated and treated with Rnase R to remove linear RNA, then hybridized to the array to screen for circRNAs. Bioinformatics analyses including clustering, differential expression, annotation of circRNA/microRNA (miRNA) interactions, Go analysis and KEGG pathway analysis, were performed. RESULTS: Based on the microarray data, we found significantly up-regulation of 24 circRNAs and down-regulation of 23 circRNAs in the HCC samples compared to NT samples (fold change ⩾ 2.0 and P< 0.05). Of them, 6 candidate circRNAs (hsa_circRNA_102814, 100381, 103489, 101764, 100327, and 103361) were verified by qRT-PCR. Of them, hsa_circRNA 100381, 103489 up-regulation and 101764 down-regulation were found to be significantly different in the 10 validation HCC tissue. Clusters of circRNAs were aberrantly expressed in HCC compared with NT samples. CircRNA_101764 was the largest nodes in circRNA/microRNA co-expression network, especially co-expression with hsa-miR-181 family, which plays an important role in cell network. Annotation of circRNA/miRNA interactions indicated that the biological effects of circRNA may be achieved by binding of miRNAs. GO analysis revealed that numerous target genes were involved in the biological processes, cellular component and molecular function. There was nearly 30 target genes enrichment on KEGG pathways analysis, PI3K-Akt signaling pathway which the most number of genes involved. CONCLUSION: In this study, we comprehensively explored the expression of differentially expressed circRNAs in HBV-related HCC, and our results indicate that circRNA_101764 may play an important role in the development of HCC.

Keywords: Hepatocellular carcinoma, HBV, circular RNA, microarray

DOI: 10.3233/CBM-170910

Journal: Cancer Biomarkers, vol. 22, no. 4, pp. 631-640, 2018