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Identifying metabolic adaptations characteristic of cardiotoxicity using paired transcriptomics and metabolomics data integrated with a computational model of heart metabolism.
Dougherty, Bonnie V; Moore, Connor J; Rawls, Kristopher D; Jenior, Matthew L; Chun, Bryan; Nagdas, Sarbajeet; Saucerman, Jeffrey J; Kolling, Glynis L; Wallqvist, Anders; Papin, Jason A.
Afiliación
  • Dougherty BV; Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.
  • Moore CJ; Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.
  • Rawls KD; Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.
  • Jenior ML; Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.
  • Chun B; Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.
  • Nagdas S; Department of Microbiology, Immunology, and Cancer Biology, University of Virginia Health System, Charlottesville, Virginia, United States of America.
  • Saucerman JJ; Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.
  • Kolling GL; Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.
  • Wallqvist A; Department of Medicine, Division of Infectious Diseases and International Health, University of Virginia, Charlottesville, Virginia, United States of America.
  • Papin JA; Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fort Detrick, Maryland, United States of America.
PLoS Comput Biol ; 20(2): e1011919, 2024 Feb.
Article en En | MEDLINE | ID: mdl-38422168
ABSTRACT
Improvements in the diagnosis and treatment of cancer have revealed long-term side effects of chemotherapeutics, particularly cardiotoxicity. Here, we present paired transcriptomics and metabolomics data characterizing in vitro cardiotoxicity to three compounds 5-fluorouracil, acetaminophen, and doxorubicin. Standard gene enrichment and metabolomics approaches identify some commonly affected pathways and metabolites but are not able to readily identify metabolic adaptations in response to cardiotoxicity. The paired data was integrated with a genome-scale metabolic network reconstruction of the heart to identify shifted metabolic functions, unique metabolic reactions, and changes in flux in metabolic reactions in response to these compounds. Using this approach, we confirm previously seen changes in the p53 pathway by doxorubicin and RNA synthesis by 5-fluorouracil, we find evidence for an increase in phospholipid metabolism in response to acetaminophen, and we see a shift in central carbon metabolism suggesting an increase in metabolic demand after treatment with doxorubicin and 5-fluorouracil.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Cardiotoxicidad / Acetaminofén Límite: Humans Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Cardiotoxicidad / Acetaminofén Límite: Humans Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos