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Biology subjects

Mahon, F.-X.

Publications and source records attributed to Mahon, F.-X..

2 recordsLinked to original sources

ANTIMETABOLIC COOPERATIVITY WITH THE CLINICALLY APPROVED KIDROLASE AND TYROSINE KINASE INHIBITORS TO ERADICATE CML STEM CELLS

Long-term treatment with tyrosine kinase inhibitors (TKI) represents an effective treatment for chronic myeloid leukemia (CML) and discontinuation of TKI therapy is now proposed to patient with deep molecular responses. However, evidence demonstrating that TKI are unable to fully eradicate dormant leukemic stem cells indicate that new therapeutic strategies are needed to prevent molecular relapses. We investigated the metabolic pathways responsible for CML surviving to Imatinib exposure and its potential therapeutic utility to improve the efficiency of TKI against CML stem cells. Using complementary cell-based techniques, we demonstrated that TKI suppressed glycolysis in a large panel of BCR-ABL1 + cell lines as well as in primary CD34+ stem-like cells from CML patients. However, compensatory glutamine-dependent mitochondrial oxidation supported ATP synthesis and CML cell survival. Glutamine metabolism was inhibited by L-asparaginases such as Kidrolase without inducing predominant CML cell death. Clinically relevant concentrations of TKI render CML progenitors and stem cells susceptible to Kidrolase. The combination of TKI with L-asparaginase reactivated the intinsic apoptotic pathway leading to efficient CML cell death. Thus, targeting glutamine metabolism with the clinically-approved drug Kidrolase, in combination with TKI that suppress glycolysis represents an effective and widely applicable therapeutic strategy for eradicating CML stem cells.

cancer biology↗

Inferring immunological control mechanisms from TKI dose alterations in CML patients

Recent clinical findings in chronic myeloid leukemia (CML) patients suggest that the risk of molecular recurrence after stopping tyrosine kinase inhibitors (TKI) treatment substantially depend on an individual, leukemia-specific immune response. However, it is still not possible to prospectively identify patients that will most likely remain in a long-term treatment free remission (TFR). Here, we use a mathematical model for CML, which explicitly includes an anti-leukemic (presumably immunological) effect and apply it to a set of patients (n=60) for whom BCR-ABL/ABL time courses had been quantified before and after TKI stop. We demonstrate that such a feedback control is conceptually necessary to explain long-term remission as observed in about half of the patients. Based on simulation results we classify the patient data sets into three different groups according to their predicted immune system configuration. While one class of patients requires a complete CML eradication to achieve TFR, other patients are able to control the leukemia after treatment cessation. Among them, we identified a third class of patients, which only maintains TFR if an optimal balance between leukemia abundance and immunological activation is achieved before treatment cessation. Further, we demonstrate that the immune response classification of the patients cannot be obtained solely from BCR-ABL measurements before treatment cessation. However, our results strongly suggest that changes in the BCR-ABL dynamics arising after system perturbations, such as TKI dose reduction, holds the information to predict the individual outcome after treatment cessation.

systems biology↗