BACKGROUND: Hepatocellular carcinoma (HCC) is not frequently diagnosed until the late stage due to its concealed symptoms. Therefore, the identification of biomarkers that have effective diagnostic performance and act as potential key therapeutic targets for HCC becomes urgent.

MATERIAL AND METHODS: Comprehensive analysis of accumulated data downloaded from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases was used to obtain more reliable potential diagnostic biomarkers of HCC and to explore related molecular mechanisms. Meta-analysis and summary receiver operating characteristic (SROC) curve analysis were performed to evaluate the differential expression of SUCO gene in HCC and identify the capability of SUCO in distinguishing HCC-tissues from normal liver-tissues.

RESULTS: SUCO was found to be upregulated in HCC-tissues and exhibited a favorable value in diagnosing HCC. Bioinformatics analysis showed that SUCO might play important roles in HCC progression, and was significantly related to cell cycle, cell metabolism, and proliferation.

CONCLUSIONS: This study was the first to demonstrate that SUCO was overexpressed in HCC-tissues, and that high expression of SUCO was significantly related to poor overall survival in HCC patients. SUCO might be a potential diagnostic biomarker for HCC patients, which promotes the tumorigenesis and progression of HCC.

Keywords: Biological Markers, Carcinoma, Hepatocellular, Tissue Array Analysis, Biomarkers, Tumor, Computational Biology, Databases, Genetic, Disease Progression, Liver Neoplasms, Membrane Proteins, ROC Curve