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MicroRNA profiles in various hepatocellular carcinoma cell lines

Authors :
Teppei Sakamoto
Hirohito Yoneyama
Takashi Himoto
Tsutomu Masaki
Asahiro Morishita
Koji Fujita
Shintaro Fujihara
Hisaaki Miyoshi
Joji Tani
Hisakazu Iwama
Source :
Oncology Letters
Publication Year :
2016
Publisher :
Spandidos Publications, 2016.

Abstract

Hepatocellular carcinoma (HCC) is one of the most common causes of cancer-associated mortality worldwide. Although surgery is considered the most effective treatment for patients with HCC, its indication is restricted by limited criteria and a high relapse rate following surgery; therefore, systemic chemotherapy is required for patients with advanced-stage HCC to prolong their survival. MicroRNAs (miRNAs) are endogenous non-coding RNAs of 18-22 nucleotides in length. It has been reported that aberrant expression of miRNAs is a feature shared by various types of human cancer. Previous studies have indicated that the modulation of non-coding RNAs, particularly miRNAs, may be a valuable therapeutic target for HCC. The aim of the present study was to elucidate the miRNA profiles associated with differentiation and hepatitis B virus (HBV) infection observed in HCC cell lines. The human Alex, Hep3B, HepG2, HuH1, HuH7, JHH1, JHH2, JHH5, JHH6, HLE, HLF and Li-7 HCC cell lines were used for an miRNA array. Replicate data were analyzed following their classification into: i) Poorly- and well-differentiated human HCC cells and ii) HBV-positive and -negative human HCC cells. Out of the 1,719 miRNAs, 4 were found to be significantly upregulated and 52 significantly downregulated in the poorly-differentiated cells, as compared with the well-differentiated cells. Conversely, in the HBV-positive cells 125 miRNAs were found to be upregulated and 2 downregulated, as compared with the HBV-negative cells. Unsupervised hierarchical clustering analysis with Pearson's correlation revealed that the miRNA expression levels were clustered both together and separately in each group. In conclusion, miRNA profile characterization based on various parameters may be a novel approach to determine the etiology of HCC.

Details

ISSN :
17921082 and 17921074
Volume :
12
Database :
OpenAIRE
Journal :
Oncology Letters
Accession number :
edsair.doi.dedup.....6ef6b4ff66da7118bb0f9859e9b24c24
Full Text :
https://doi.org/10.3892/ol.2016.4853