A framework for large-scale metabolome drug profiling links coenzyme A metabolism to the toxicity of anti-cancer drug dichloroacetate

Abstract

Metabolic profiling of cell line collections has become an invaluable tool to study disease etiology, drug modes of action and to select personalized treatments. However, large-scale in vitro dynamic metabolic profiling is limited by time-consuming sampling and complex measurement procedures. By adapting a mass spectrometry-based metabolomics workflow for high-throughput profiling of diverse adherent mammalian cells, we establish a framework for the rapid measurement and analysis of drug-induced dynamic changes in intracellular metabolites. This methodology is scalable to large compound libraries and is here applied to study the mechanism underlying the toxic effect of dichloroacetate in ovarian cancer cell lines. System-level analysis of the metabolic responses revealed a key and unexpected role of CoA biosynthesis in dichloroacetate toxicity and the more general importance of CoA homeostasis across diverse human cell lines. The herein-proposed strategy for high-content drug metabolic profiling is complementary to other molecular profiling techniques, opening new scientific and drug-discovery opportunities.

Metabolic profiling of cancer cells reveals genome-wide crosstalk between transcriptional regulators and metabolism

“…1b), that are hence amenable to accurate relative quantification. Moreover, by integrating MS readouts at multiple cell densities and time points, the resulting estimates of relative metabolite abundances are invariant to cultivation time and cell densities, enabling the direct comparison between different cell lines and conditions 18 . In the second step, a subset of metabolites identified to report on cell volume, mostly intermediates of fatty acid metabolism, were used to correct for differences in total volume of sampled cultures (see Methods section and Supplementary Fig.…”

“…To this end, we developed a combined experimental and computational framework that overcomes important limitations in large-scale metabolome screenings, including (i) the limited throughput and laborious sample preparation of classical metabolomics approaches in mammalian cell cultures, (ii) the lack of scalable methods to adequately normalize metabolomics data across morphologically diverse cell types, and (iii) the need for systematic data integration strategies. The herein-proposed workflow for large-scale metabolome profiling is directly applicable to the study of dynamic metabolic responses to external stimuli 18 , and can scale to larger cohorts that are now within reach of other molecular profiling platforms 61 .…”

Dichloroacetate Affects Mitochondrial Function and Stemness-Associated Properties in Pancreatic Cancer Cell Lines

“…It must be taken into account that DCA can target other cellular pathways in addition to PDK. Indeed, it has been reported that DCA affects the CoA biosynthetic pathway [42], activates the AMPK signaling pathway [43], antagonizes with acetate [44], and disturbs the tyrosine catabolism [45]. Moreover, comparison of the metabolite profiles in cells treated with DCA or more selective novel inhibitors of PDK resulted in different outcomes [46].…”

Dichloroacetate and PX-478 Exhibit Strong Synergistic Effects in a Various Number of Cancer Cell Lines.

“…Additionally, DCA positively regulates p53 activity (17) and is approved for therapy of hereditary lactic acidosis (18). In the other hand, different groups have identi ed off-target effects of DCA, such as activation of the AMPK signalling pathway, antagonization of acetate and disruption of tyrosine catabolism (19)(20)(21)(22)(23).…”