Gene expression profile analysis of human hepatocellular carcinoma using SAGE and LongSAGE.
BACKGROUND
Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide and the second cancer killer in China. The initiation and malignant transformation of cancer result from accumulation of genetic changes in the sequences or expression level of cancer-related genes. It is of particular importance to determine gene expression profiles of cancers on a global scale. SAGE and LongSAGE have been developed for this purpose.


METHODS
We performed SAGE in normal liver and HCC samples as well as the liver cancer cell line HepG2. Meanwhile, the same HCC sample was simultaneously analyzed using LongSAGE. Computational analysis was carried out to identify differentially expressed genes between normal liver and HCC which were further validated by real-time quantitative RT-PCR.


RESULTS
Approximately 50,000 tags were sequenced for each of the four libraries. Analysis of the technical replicates of HCC indicated that excluding the low abundance tags, the reproducibility of SAGE data is high (R = 0.97). Compared with the gene expression profile of normal liver, 224 genes related to biosynthesis, cell proliferation, signal transduction, cellular metabolism and transport were identified to be differentially expressed in HCC. Overexpression of some transcripts selected from SAGE data was validated by real-time quantitative RT-PCR. Interestingly, sarcoglycan-epsilon (SGCE) and paternally expressed gene (PEG10) which is a pair of close neighboring genes on chromosome 7q21, showed similar enhanced expression patterns in HCC, implicating that a common mechanism of deregulation may be shared by these two genes.


CONCLUSIONS
Our study depicted the expression profile of HCC on a genome-wide scale without the restriction of annotation databases, and provided novel candidate genes that might be related to HCC.
Dong
Hui
H
Department of Microbiology and Microbial Engineering, School of Life Sciences, Fudan University, Shanghai 200433, PR China. dongh@chgc.sh.cn
Ge
Xijin
X
Shen
Yan
Y
Chen
Linlei
L
Kong
Yalin
Y
Zhang
Hongyi
H
Man
Xiaobo
X
Tang
Liang
L
Yuan
Hong
H
Wang
Hongyang
H
Zhao
Guoping
G
Jin
Weirong
W