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Thermodynamic Genome-Scale Metabolic Modeling of Metallodrug Resistance in Colorectal Cancer.
Herrmann, Helena A; Rusz, Mate; Baier, Dina; Jakupec, Michael A; Keppler, Bernhard K; Berger, Walter; Koellensperger, Gunda; Zanghellini, Jürgen.
Afiliación
  • Herrmann HA; Department of Analytical Chemistry, University of Vienna, 1090 Vienna, Austria.
  • Rusz M; Department of Analytical Chemistry, University of Vienna, 1090 Vienna, Austria.
  • Baier D; Institute of Inorganic Chemistry, University of Vienna, 1090 Vienna, Austria.
  • Jakupec MA; Institute of Inorganic Chemistry, University of Vienna, 1090 Vienna, Austria.
  • Keppler BK; Institute of Inorganic Chemistry, University of Vienna, 1090 Vienna, Austria.
  • Berger W; Research Cluster Translational Cancer Therapy Research, University of Vienna and Medical University of Vienna, 1090 Vienna, Austria.
  • Koellensperger G; Institute of Inorganic Chemistry, University of Vienna, 1090 Vienna, Austria.
  • Zanghellini J; Research Cluster Translational Cancer Therapy Research, University of Vienna and Medical University of Vienna, 1090 Vienna, Austria.
Cancers (Basel) ; 13(16)2021 Aug 17.
Article en En | MEDLINE | ID: mdl-34439283
BACKGROUND: Mass spectrometry-based metabolomics approaches provide an immense opportunity to enhance our understanding of the mechanisms that underpin the cellular reprogramming of cancers. Accurate comparative metabolic profiling of heterogeneous conditions, however, is still a challenge. METHODS: Measuring both intracellular and extracellular metabolite concentrations, we constrain four instances of a thermodynamic genome-scale metabolic model of the HCT116 colorectal carcinoma cell line to compare the metabolic flux profiles of cells that are either sensitive or resistant to ruthenium- or platinum-based treatments with BOLD-100/KP1339 and oxaliplatin, respectively. RESULTS: Normalizing according to growth rate and normalizing resistant cells according to their respective sensitive controls, we are able to dissect metabolic responses specific to the drug and to the resistance states. We find the normalization steps to be crucial in the interpretation of the metabolomics data and show that the metabolic reprogramming in resistant cells is limited to a select number of pathways. CONCLUSIONS: Here, we elucidate the key importance of normalization steps in the interpretation of metabolomics data, allowing us to uncover drug-specific metabolic reprogramming during acquired metal-drug resistance.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Cancers (Basel) Año: 2021 Tipo del documento: Article País de afiliación: Austria

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Cancers (Basel) Año: 2021 Tipo del documento: Article País de afiliación: Austria