Mitigating temozolomide resistance in glioblastoma via DNA damage-repair inhibition

Inmaculada C. Sorribes, Samuel K. Handelman, Harsh V. Jain

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Glioblastomas are among the most lethal cancers, with a 5 year survival rate below 25%. Temozolomide is typically used in glioblastoma treatment; however, the enzymes alkylpurine-DNA-N-glycosylase (APNG) and methylguanine-DNA-methyltransferase (MGMT) efficiently mediate the repair of DNA damage caused by temozolomide, reducing treatment efficacy. Consequently, APNG and MGMT inhibition has been proposed as a way of overcoming chemotherapy resistance. Here, we develop a mechanistic mathematical model that explicitly incorporates the effects of chemotherapy on tumour cells, including the processes of DNA damage induction, cell arrest and DNA repair. Our model is carefully parametrized and validated, and then used to virtually recreate the response of heteroclonal glioblastomas to dual treatment with temozolomide and inhibitors of APNG/MGMT. Using our mechanistic model, we identify four combination treatment strategies optimized by tumour cell phenotype, and isolate the strategy most likely to succeed in a pre-clinical and clinical setting. If confirmed in clinical trials, these strategies have the potential to offset chemotherapy resistance in patients with glioblastoma and improve overall survival.

Original languageEnglish (US)
Article number20190722
JournalJournal of the Royal Society Interface
Volume17
Issue number162
DOIs
StatePublished - Jan 1 2020
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2020 The Author(s) Published by the Royal Society. All rights reserved.

Keywords

  • Alkylpurine-DNA-N-glycosylase
  • Glioblastoma
  • Mathematical model
  • Methylguanine-DNA-methyltransferase
  • Temozolomide

Fingerprint

Dive into the research topics of 'Mitigating temozolomide resistance in glioblastoma via DNA damage-repair inhibition'. Together they form a unique fingerprint.

Cite this