Abstract
Hepatocellular carcinoma (HCC) is a lethal malignancy with high morbidity and mortality rates worldwide. The identification of prognosis‑associated biomarkers is crucial to improve HCC patient survival. The present study aimed to explore potential predictive biomarkers for HCC. Differentially expressed genes (DEGs) were analyzed in the GSE36376 dataset using GEO2R. Hub genes were identified and further investigated for prognostic value in HCC patients. A risk score model and nomogram were constructed to predict HCC prognosis using the prognosis‑associated genes and clinical factors. Pearson's correlation was employed to show interactions among hub genes. Gene enrichment analysis was performed to identify detailed biological processes and pathways. A total of 71 DEGs were obtained and seven (ADH4, CYP2C8, CYP2C9, CYP8B1, SLC22A1, TAT and HSD17B13, all adjusted P≤0.05) of the 10 hub genes were identified as prognosis‑related genes for survival analysis in HCC patients, including alcohol dehydrogenase 4 (class II), pi polypeptide (ADH4), cytochrome p450 family 2 subfamily C member 8 (CYP2C8), cytochrome P450 family 2 subfamily C member 9 (CYP2C9), cytochrome P450 family 8 subfamily B member 1 (CYP8B1), solute carrier family 22 member 1 (SLC22A1), tyrosine aminotransferase (TAT) and hydroxysteroid 17‑β dehydrogenase 13 (HSD17B13). The risk score model could predict HCC prognosis and the nomogram visualized gene expression and clinical factors of probability for HCC prognosis. The majority of genes showed significant Pearson's correlations with others (41 Pearson correlations P≤0.01, four Pearson correlations P>0.05). GO analysis revealed that terms such as 'chemical carcinogenesis' and 'drug metabolism‑cytochrome P450' were enriched and may prove helpful to elucidate the mechanisms of hepatocarcinogenesis. Hub genes ADH4, CYP2C8, CYP2C9, CYP8B1, SLC22A1, TAT and HSD17B13 may be useful as predictive biomarkers for HCC prognosis.