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Systems biology of ferroptosis: A modeling approach.
Konstorum, Anna; Tesfay, Lia; Paul, Bibbin T; Torti, Frank M; Laubenbacher, Reinhard C; Torti, Suzy V.
Afiliação
  • Konstorum A; Center for Quantitative Medicine, UConn Health, 263 Farmington Ave., Farmington, CT, United States of America. Electronic address: konstorum@uchc.edu.
  • Tesfay L; Department of Molecular Biology and Biophysics, UConn Health, 263 Farmington Ave., Farmington, CT, United States of America.
  • Paul BT; Department of Molecular Biology and Biophysics, UConn Health, 263 Farmington Ave., Farmington, CT, United States of America.
  • Torti FM; Department of Medicine, UConn Health, 263 Farmington Ave., Farmington, CT, United States of America.
  • Laubenbacher RC; Center for Quantitative Medicine, UConn Health, 263 Farmington Ave., Farmington, CT, United States of America; Jackson Laboratory for Genomic Medicine, 263 Farmington Ave., Farmington, CT, United States of America.
  • Torti SV; Department of Molecular Biology and Biophysics, UConn Health, 263 Farmington Ave., Farmington, CT, United States of America.
J Theor Biol ; 493: 110222, 2020 05 21.
Article em En | MEDLINE | ID: mdl-32114023
Ferroptosis is a recently discovered form of iron-dependent regulated cell death (RCD) that occurs via peroxidation of phospholipids containing polyunsaturated fatty acid (PUFA) moieties. Activating this form of cell death is an emerging strategy in cancer treatment. Because multiple pathways and molecular species contribute to the ferroptotic process, predicting which tumors will be sensitive to ferroptosis is a challenge. We thus develop a mathematical model of several critical pathways to ferroptosis in order to perform a systems-level analysis of the process. We show that sensitivity to ferroptosis depends on the activity of multiple upstream cascades, including PUFA incorporation into the phospholipid membrane, and the balance between levels of pro-oxidant factors (reactive oxygen species, lipoxogynases) and antioxidant factors (GPX4). We perform a systems-level analysis of ferroptosis sensitivity as an outcome of five input variables (ACSL4, SCD1, ferroportin, transferrin receptor, and p53) and organize the resulting simulations into 'high' and 'low' ferroptosis sensitivity groups. We make a novel prediction corresponding to the combinatorial requirements of ferroptosis sensitivity to SCD1 and ACSL4 activity. To validate our prediction, we model the ferroptotic response of an ovarian cancer stem cell line following single- and double-knockdown of SCD1 and ACSL4. We find that the experimental outcomes are consistent with our simulated predictions. This work suggests that a systems-level approach is beneficial for understanding the complex combined effects of ferroptotic input, and in predicting cancer susceptibility to ferroptosis.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Ferroptose Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Ferroptose Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article