Identification of novel lipid biomarkers in xmrk- and Myc-induced models of hepatocellular carcinoma in zebrafish

Abstract

Abstract Background Hepatocellular carcinoma (HCC) is the predominant form of liver cancer and is accompanied by complex dysregulation of lipids. Increasing evidence suggests that particular lipid species are associated with HCC progression. Here, we aimed to identify lipid biomarkers of HCC associated with the induction of two oncogenes, xmrk, a zebrafish homolog of the human epidermal growth factor receptor (EGFR), and Myc, a regulator of EGFR expression during HCC. Methods We induced HCC in transgenic xmrk, Myc, and xmrk/Myc zebrafish models. Liver specimens were histologically analyzed to characterize the HCC stage, Oil-Red-O stained to detect lipids, and liquid chromatography/mass spectrometry analyzed to assign and quantify lipid species. Quantitative real-time polymerase chain reaction was used to measure lipid metabolic gene expression in liver samples. Lipid species data was analyzed using univariate and multivariate logistic modeling to correlate lipid class levels with HCC progression. Results We found that induction of xmrk, Myc and xmrk/Myc caused different stages of HCC. Lipid deposition and class levels generally increased during tumor progression, but triglyceride levels decreased. Myc appears to control early HCC stage lipid species levels in double transgenics, whereas xmrk may take over this role in later stages. Lipid metabolic gene expression can be regulated by either xmrk, Myc, or both oncogenes. Our computational models showed that variations in total levels of several lipid classes are associated with HCC progression. Conclusions These data indicate that xmrk and Myc can temporally regulate lipid species that may serve as effective biomarkers of HCC progression.

Keywords

• Zebrafish
• Cancer
• Liver
• Lipids
• Lipidomics
• Hepatocarcinoma