Analysis of temozolomide resistance in low‐grade gliomas using a mechanistic mathematical model. (24th January 2017)

• Record Type: Journal Article
• Authors: Ollier, Edouard; Mazzocco, Pauline; Ricard, Damien; Kaloshi, Gentian; Idbaih, Ahmed; Alentorn, Agusti; Psimaras, Dimitri; Honnorat, Jérôme; Delattre, Jean‐Yves; Grenier, Emmanuel; Ducray, François; Samson, Adeline
• Is Part Of: Fundamental & clinical pharmacology. Volume 31:Number 3(2017:Jun.)
• Page Start: 347
• Page End: 358
• Publication Date: 2017-01-24
• Subjects: low‐grade glioma -- mathematical model -- resistance -- temozolomide -- tumor growth inhibition; Pharmacology -- Periodicals; 615.1
• DOI: 10.1111/fcp.12259
• Languages: English
• ISSNs: 0767-3981

Abstract

Abstract: Understanding how tumors develop resistance to chemotherapy is a major issue in oncology. When treated with temozolomide (TMZ), an oral alkylating chemotherapy drug, most low‐grade gliomas (LGG) show an initial volume decrease but this effect is rarely long lasting. In addition, it has been suggested that TMZ may drive tumor progression in a subset of patients as a result of acquired resistance. Using longitudinal tumor size measurements from 121 patients, the aim of this study was to develop a semi‐mechanistic mathematical model to determine whether resistance of LGG to TMZ was more likely to result from primary and/or from chemotherapy‐induced acquired resistance that may contribute to tumor progression. We applied the model to a series of patients treated upfront with TMZ ( n = 109) or PCV (procarbazine, CCNU, vincristine) chemotherapy ( n = 12) and used a population mixture approach to classify patients according to the mechanism of resistance most likely to explain individual tumor growth dynamics. Our modeling results predicted acquired resistance in 51% of LGG treated with TMZ. In agreement with the different biological effects of nitrosoureas, none of the patients treated with PCV were classified in the acquired resistance group. Consistent with the mutational analysis of recurrent LGG, analysis of growth dynamics using mathematical modeling suggested that in a subset of patients, TMZ might paradoxically contribute to tumor progression as a result of chemotherapy‐induced resistance. Identification of patients at risk of developing acquired resistance is warranted to better define the role of TMZ in LGG.