Suitable reference genes for real-time PCR in human HBV-related hepatocellular carcinoma with different clinical prognoses
Open Access
- 6 February 2009
- journal article
- research article
- Published by Springer Nature in BMC Cancer
- Vol. 9 (1) , 49
- https://doi.org/10.1186/1471-2407-9-49
Abstract
Housekeeping genes are routinely used as endogenous references to account for experimental differences in gene expression assays. However, recent reports show that they could be de-regulated in different diseases, model animals, or even under varied experimental conditions, which may lead to unreliable results and consequently misinterpretations. This study focused on the selection of suitable reference genes for quantitative PCR in human hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) with different clinical outcomes. We evaluated 6 commonly used housekeeping genes' expression levels in 108 HBV-related HCCs' matched tumor and non-tomor tissue samples with different clinical outcomes and 26 normal liver specimens by real-time PCR. The expression stability of the 6 genes was compared using the software programs geNorm and NormFinder. To show the impact of reference genes on data analysis, we took PGK1 as a target gene normalized by each reference gene, and performed one-way ANOVA and the equivalence test. With the geNorm and NormFinder software programs, analysis of TBP and HPRT1 showed the best stability in all tissue samples, while 18s and ACTB were less stable. When 18s or ACTB was used for normalization, no significant difference of PGK1 expression (p > 0.05) was found among HCC tissues with and without metastasis, and normal liver specimens; however, dramatically differences (p < 0.001) were observed when either TBP or the combination of TBP and HPRT1 were selected as reference genes. TBP and HPRT1 are the most reliable reference genes for q-PCR normalization in HBV-related HCC specimens. However, the well-used ACTB and 18S are not suitable, which actually lead to the misinterpretation of the results in gene expression analysis.Keywords
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