Objective: To offer new prognostic evaluations by exploring potentially distinctive genetic features of hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC).
Methods: There were 12 samples for gene expression profiling processes in this study. These included three HCC lesion samples and their matched adjacent nontumor liver tissues obtained from patients with HCC, as well as three ICC samples and their controls collected similarly. In addition to the expression matrix generated on our own, profiles of other cohorts from The Cancer Genome Atlas (TCGA) program and the Gene Expression Omnibus (GEO) were also employed in later bioinformatical analyses. Differential analyses, functional analyses, protein interaction network analyses, and gene set variation analyses were used to identify key genes. To establish the prognostic models, univariate/multivariate Cox analyses and subsequent stepwise regression were applied, with the Akaike information criterion evaluating the goodness of fitness.
Results: The top three pathways enriched in HCC were all metabolism-related; they were fatty acid degradation, retinol metabolism, and arachidonic acid metabolism. In ICC, on the other hand, additional pathways related to fat digestion and absorption and cholesterol metabolism were identified. Consistent characteristics of such a metabolic landscape were observed across different cohorts. A prognostic risk score model for calculating HCC risk was constructed, consisting of ADH4, ADH6, CYP2C9, CYP4F2, and RDH16. This signature predicts the 3-year survival with an AUC area of 0.708 (95%CI = 0.644 to 0.772). For calculating the risk of ICC, a prognostic risk score model was built upon the expression levels of CYP26A1, NAT2, and UGT2B10. This signature predicts the 3-year survival with an AUC area of 0.806 (95% CI = 0.664 to 0.947).
Conclusion: HCC and ICC share commonly abrupted pathways associated with the metabolism of fatty acids, retinol, arachidonic acids, and drugs, indicating similarities in their pathogenesis as primary liver cancers. On the flip side, these two types of cancer possess distinctive promising biomarkers for predicting overall survival or potential targeted therapies.
Copyright © 2022 Linchao Ding et al.