Metabolomic profiling of cerebrospinal fluid reveals an early diagnostic model for central nervous system involvement in acute lymphoblastic leukaemia

A metabolomics approach reveals metabolic disturbance of human cholangiocarcinoma cells after parthenolide treatment

ETHNOPHARMACOLOGICAL RELEVANCE

Tanacetum parthenium (L.) Schultz-Bip, commonly known as feverfew, has been traditionally used to treat fever, migraines, rheumatoid arthritis, and cancer. Parthenolide (PTL), the main bioactive ingredient isolated from the shoots of feverfew, is a sesquiterpene lactone with anti-inflammatory and antitumor properties. Previous studies showed that PTL exerts anticancer activity in various cancers, including hepatoma, cholangiocarcinoma, acute myeloid leukemia, breast, prostate, and colorectal cancer. However, the metabolic mechanism underlying the anticancer effect of PTL remains poorly understood.

AIM OF THE STUDY

To explore the anticancer activity and underlying mechanism of PTL in human cholangiocarcinoma cells.

MATERIAL AND METHODS

In this investigation, the effects and mechanisms of PTL on human cholangiocarcinoma cells were investigated via a liquid chromatography/mass spectrometry (LC/MS)-based metabolomics approach. First, cell proliferation and apoptosis were evaluated using cell counting kit-8 (CCK-8), flow cytometry analysis, and western blotting. Then, LC/MS-based metabolic profiling along with orthogonal partial least-squares discriminant analysis (OPLS-DA) has been constructed to distinguish the metabolic changes between the negative control group and the PTL-treated group in TFK1 cells. Next, enzyme-linked immunosorbent assay (ELISA) was applied to investigate the changes of metabolic enzymes associated with significantly alerted metabolites. Finally, the metabolic network related to key metabolic enzymes, metabolites, and metabolic pathways was established using MetaboAnalyst 5.0 and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Database.

RESULTS

PTL treatment could induce the proliferation inhibition and apoptosis of TFK1 in a concentration-dependent manner. Forty-three potential biomarkers associated with the antitumor effect of PTL were identified, which primarily related to glutamine and glutamate metabolism, alanine, aspartate and glutamate metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, arginine biosynthesis, arginine and proline metabolism, glutathione metabolism, nicotinate and nicotinamide metabolism, pyrimidine metabolism, fatty acid metabolism, phospholipid catabolism, and sphingolipid metabolism. Pathway analysis of upstream and downstream metabolites, we found three key metabolic enzymes, including glutaminase (GLS), γ-glutamyl transpeptidase (GGT), and carnitine palmitoyltransferase 1 (CPT1), which mainly involved in glutamine and glutamate metabolism, glutathione metabolism, and fatty acid metabolism. The changes of metabolic enzymes associated with significantly alerted metabolites were consistent with the levels of metabolites, and the metabolic network related to key metabolic enzymes, metabolites, and metabolic pathways was established. PTL may exert its antitumor effect against cholangiocarcinoma by disturbing metabolic pathways. Furthermore, we selected two positive control agents that are considered as first-line chemotherapy standards in cholangiocarcinoma therapy to verify the reliability and accuracy of our metabolomic study on PTL.

CONCLUSION

This research enhanced our comprehension of the metabolic profiling and mechanism of PTL treatment on cholangiocarcinoma cells, which provided some references for further research into the anti-cancer mechanisms of other drugs.

Characterisation of Aberrant Metabolic Pathways in Hepatoblastoma Using Liquid Chromatography and Tandem Mass Spectrometry (LC-MS/MS)

Hepatoblastoma (HB) is a rare childhood tumour with an evolving molecular landscape. We present the first comprehensive metabolomic analysis using untargeted and targeted liquid chromatography coupled to high-resolution tandem mass spectrometry (LC-MS/MS) of paired tumour and non-tumour surgical samples in HB patients (n = 8 pairs). This study demonstrates that the metabolomic landscape of HB is distinct from that of non-tumour (NT) liver tissue, with 35 differentially abundant metabolites mapping onto pathways such as fatty acid transport, glycolysis, the tricarboxylic acid (TCA) cycle, branched-chain amino acid degradation and glutathione synthesis. Targeted metabolomics demonstrated reduced short-chain acylcarnitines and a relative accumulation of branched-chain amino acids. Medium- and long-chain acylcarnitines in HB were similar to those in NT. The metabolomic changes reported are consistent with previously reported transcriptomic data from tumour and non-tumour samples (49 out of 54 targets) as well as metabolomic data obtained using other techniques. Gene set enrichment analysis (GSEA) from RNAseq data (n = 32 paired HB and NT samples) demonstrated a downregulation of the carnitine metabolome and immunohistochemistry showed a reduction in CPT1a (n = 15 pairs), which transports fatty acids into the mitochondria, suggesting a lack of utilisation of long-chain fatty acids in HB. Thus, our findings suggest a reduced metabolic flux in HB which is corroborated at the gene expression and protein levels. Further work could yield novel insights and new therapeutic targets.

Metabolic profiling reveals metabolic features of consolidation therapy in pediatric acute lymphoblastic leukemia

Acute lymphoblastic leukemia (ALL) and its treatment continue to pose substantial risks. To understand ALL more deeply, the metabolome in fasting plasma of 27 ALL patients before and after high-dose methotrexate therapies (consolidation therapy) including methotrexate and 6-mercaptopurine (6-MP) was investigated. Plasma metabolites were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS). Orthogonal projections to latent structures discriminant analysis and significance analysis of microarrays were used to evaluate the metabolic changes. Pathway enrichment and co-expression network analyses were performed to identify clusters of molecules, and 2826 metabolites were identified. Among them, 38 metabolites were identified by univariate analysis, and 7 metabolites that were altered by conditioning therapy were identified by multivariate analysis. The Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used for pathway enrichment analysis. Among the enriched KEGG pathways, the 3 significantly altered metabolic pathways were pyrimidine metabolism; phenylalanine, tyrosine, and tryptophan biosynthesis; and phenylalanine metabolism. In addition, L-phenylalanine was significantly correlated with blood urea nitrogen (BUN), and palmitoylcarnitine was correlated with aspartate aminotransferase (AST). In summary, consolidation therapy significantly affected pyrimidine- and phenylalanine-associated metabolic pathways in pediatric ALL patients. These findings may provide an insight into the role of metabolic profiling in consolidation treatment and as a potential for pediatric ALL patients.

Implications of the Essential Role of Small Molecule Ligand Binding Pockets in Protein-Protein Interactions

Protein-protein interactions (PPIs) and protein-metabolite interactions play a key role in many biochemical processes, yet they are often viewed as being independent. However, the fact that small molecule drugs have been successful in inhibiting PPIs suggests a deeper relationship between protein pockets that bind small molecules and PPIs. We demonstrate that 2/3 of PPI interfaces, including antibody-epitope interfaces, contain at least one significant small molecule ligand binding pocket. In a representative library of 50 distinct protein-protein interactions involving hundreds of mutations, >75% of hot spot residues overlap with small molecule ligand binding pockets. Hence, ligand binding pockets play an essential role in PPIs. In representative cases, evolutionary unrelated monomers that are involved in different multimeric interactions yet share the same pocket are predicted to bind the same metabolites/drugs; these results are confirmed by examples in the PDB. Thus, the binding of a metabolite can shift the equilibrium between monomers and multimers. This implicit coupling of PPI equilibria, termed "metabolic entanglement", was successfully employed to suggest novel functional relationships among protein multimers that do not directly interact. Thus, the current work provides an approach to unify metabolomics and protein interactomics.