Phospholipids are A Potentially Important Source of Tissue Biomarkers for Hepatocellular Carcinoma: Results of a Pilot Study Involving Targeted Metabolomics

Abstract

Background: Hepatocellular carcinoma (HCC) pathogenesis involves the alteration of multiple liver-specific metabolic pathways. We systematically profiled cancer-and liver-related classes of metabolites in HCC and adjacent liver tissues and applied supervised machine learning to compare their potential yield for HCC biomarkers. Methods: Tumor and corresponding liver tissue samples were profiled as follows: Bile acids by ultra-performance liquid chromatography (LC) coupled to tandem mass spectrometry (MS), phospholipids by LC-MS/MS, and other small molecules including free fatty acids by gas chromatography-time of flight MS. The overall classification performance of metabolomic signatures derived by support vector machine (SVM) and random forests machine learning algorithms was then compared across classes of metabolite. Results: For each metabolite class, there was a plateau in classification performance with signatures of 10 metabolites. Phospholipid signatures consistently showed the highest discrimination for HCC followed by signatures derived from small molecules, free fatty acids, and bile acids with area under the receiver operating characteristic curve (AUC) values of 0.963, 0.934, 0.895, 0.695, respectively, for SVM-generated signatures comprised of 10 metabolites. Similar classification performance patterns were observed with signatures derived by random forests. Conclusion: Membrane phospholipids are a promising source of tissue biomarkers for discriminating between HCC tumor and liver tissue.

Comparing DESI-MSI and MALDI-MSI Mediated Spatial Metabolomics and Their Applications in Cancer Studies

“…Abliz’s group’s study set the example of using MTCS model combined with MALDI-MSI to investigate the detailed metabolic profiles or drug distribution patterns in tumor tissues. Lastly, it is worth mentioning that the glutamine, creatine, and malic acid distribution trends were also observed in recent studies on hepatocellular carcinoma ( 66 , 67 ). Therefore, much metabolic reprogramming may be conserved across different types of cancers.…”

Exploring Optimal Biomarker Sources: A Comparative Analysis of Exosomes and Whole Plasma in Fasting and Non-Fasting Conditions for Liquid Biopsy Applications

“…We checked a total of 513 metabolites, including 329 Lipid species, 35 bile acids (BAs), 55 triacylglycerol (TGs), 25 diacylglycerol (DGs), 39 fatty acids, and 30 amino acids. The lipidomic and metabolomic concentration measurement were conducted following the protocol published in reference [ 70 ]. To distinguish between fasting/non-fasting states, we focused on TGs and DGs.…”

Metabolomics for Clinical Biomarker Discovery and Therapeutic Target Identification

“…Mass spectrometry analysis of seven metabolites exhibited higher diagnostic and discriminating capacity [70]. Membrane phospholipid signatures are promising biomarkers, revealing the highest discrimination between hepatocellular carcinoma tumors and liver tissue [71].…”