Hepatocellular carcinoma (HCC) has a high rate of cancer recurrence (up to 70%) in patients who undergo surgical resection. We investigated prognostic gene signatures for predicting HCC recurrence using in silico gene expression analysis. Recurrence-associated gene candidates were chosen by a comparative analysis of gene expression profiles from two independent whole-transcriptome datasets in patients with HCC who underwent surgical resection. Five promising candidate genes, CETN2, HMGA1, MPZL1, RACGAP1, and SNRPB were identified, and the expression of these genes was evaluated using quantitative reverse transcription PCR in the validation set (n = 57). The genes CETN2, HMGA1, RACGAP1, and SNRPB, but not MPZL1, were upregulated in patients with recurrent HCC. In addition, the combination of HMGA1 and MPZL1 demonstrated the best area under the curve (0.807, 95% confidence interval [CI] = 0.681–0.899) for predicting HCC recurrence. In terms of clinicopathological correlation, CETN2, MPZL1, RACGAP1, and SNRPB were upregulated in patients with microvascular invasion, and the expression of MPZL1 and SNRPB was increased in proportion to the Edmonson tumor differentiation grade. Additionally, overexpression of CETN2, HMGA1, and RACGAP1 correlated with poor overall survival (OS) and disease-free survival (DFS) in the validation set. Finally, Cox regression analysis showed that the expression of serum alpha-fetoprotein and RACGAP1 significantly affected OS, whereas platelet count, microvascular invasion, and HMGA1 expression significantly affected DFS. In conclusion, HMGA1 and RACGAP1 may be potential prognostic biomarkers for predicting the recurrence of HCC after surgical resection.

Reverse transcription-quantitative (RT-q) PCR is the most feasible and useful technique for identifying and evaluating cancer biomarkers; however, the method requires suitable reference genes for gene expression analysis. The aim of the present study was to identify the most suitable reference gene for the normalization of relative gene expression in human hepatocellular carcinoma (HCC) tissue and blood samples. First, 14 candidate reference genes were selected through a systematic literature search. The expression levels of these genes ( ACTB, B2M, GAPDH, GUSB, HMBS, HPRT1, PGK1, PPIA, RPLP0, RPL13A, SDHA, TBP, TFRC and YWHAZ ) were evaluated using human multistage HCC transcriptome data (dataset GSE114564), which included normal liver (n=15), chronic hepatitis (n=20), liver cirrhosis (n=10), and early (n=18) and advanced HCC (n=45). From the 14 selected genes, five genes, whose expression levels were stable in all liver disease statuses ( ACTB, GAPDH, HMBS, PPIA and RPLP0 ), were further assessed using RT-qPCR in 40 tissues (20 paired healthy tissues and 20 tissues from patients with HCC) and 40 blood samples (20 healthy controls and 20 samples from patients with HCC). BestKeeper statistical algorithms were used to identify the most stable reference genes, of which HMBS was found to be the most stable in both HCC tissues and blood samples. Therefore, the results of the present study suggest HMBS as a promising reference gene for the normalization of relative RT-qPCR techniques in HCC-related studies.