Dropwort-induced metabolic reprogramming restrains YAP/TAZ/TEAD oncogenic axis in mesothelioma.

BACKGROUND: Over the past decade, newly designed cancer therapies have not significantly improved the survival of patients diagnosed with Malignant Pleural Mesothelioma (MPM). Among a limited number of genes that are frequently mutated in MPM several of them encode proteins that belong to the HIPPO tumor suppressor pathway. METHODS: The anticancer effects of the top flower standardized extract of Filipendula vulgaris (Dropwort) were characterized in "in vitro" and "in vivo" models of MPM. At the molecular level, two "omic" approaches were used to investigate Dropwort anticancer mechanism of action: a metabolomic profiling and a phosphoarray analysis. RESULTS: We found that Dropwort significantly reduced cell proliferation, viability, migration and in vivo tumor growth of MPM cell lines. Notably, Dropwort affected viability of tumor-initiating MPM cells and synergized with Cisplatin and Pemetrexed in vitro. Metabolomic profiling revealed that Dropwort treatment affected both glycolysis/tricarboxylic acid cycle as for the decreased consumption of glucose, pyruvate, succinate and acetate, and the lipid metabolism. We also document that Dropwort exerted its anticancer effects, at least partially, promoting YAP and TAZ protein ubiquitination. CONCLUSIONS: Our findings reveal that Dropwort is a promising source of natural compound(s) for targeting the HIPPO pathway with chemo-preventive and anticancer implications for MPM management.

(1)H NMR Metabolomic Footprinting Analysis for the In Vitro Screening of Potential Chemopreventive Agents.

Metabolomics is the quantification and analysis of the concentration profiles of low-molecular-weight compounds present in biological samples. In particular metabolic footprinting analysis, based on the monitoring of metabolites consumed from and secreted into the growth medium, is a valuable tool for the study of pharmacological and toxicological effects of drugs. Mass spectrometry and nuclear magnetic resonance (NMR) are the two main complementary techniques used in this field. Although less sensitive, NMR gives a direct fingerprint of the system, and the spectra obtained contain metabolic information that can be distilled by chemometric techniques. In this chapter, we present how metabolomic footprinting can be used to assess in vitro a potential chemopreventive molecule as metformin.

Dissecting drug and vehicle metabolic effects in rats by a metabonomic approach.

A combined application of high resolution (1)H NMR spectroscopy and multivariate statistical techniques focused on establishing a consistent statistical approach to metabonomic studies was tested. The data reduction, which is preliminary to the application of multivariate analysis to NMR spectra, was carried out by means of two complementary methods: pure Pattern Recognition (PR) and Assigned Signal Analysis (ASA). The simultaneous use of both approaches allowed us to obtain additional information in the analysis of metabonomic data, compared to the use of PR alone. This additional information consists in the possibility of a biochemical interpretation of the effects induced by treatment with xenobiotics, such as drugs or drug vehicles, on the metabolic networks of the systems under investigation. This approach allowed us to ascertain that a single-dose treatment with ST1959 vehicled by Sesame oil affects the production of hepatic glucose associated to an increment of the amino acid ketogenic process.