Author Affiliations
- 1Instituto de Matemática e Computação, Universidade Federal de Itajubá, Brazil
- 2Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Germany
- 3National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany
- Correspondence:
ingmar.glauche{at}tu-dresden.de
Data supplements
Fassoni et al. Graphical Abstract
Fassoni et al. Graphical Abstract
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Fassoni et al. Supplementary Appendix
Fassoni et al. Supplementary appendix provided by the authors.
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Disclosures and Contributions
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ARTICLE FIGURES & DATA
Figures
- Figure 1.
Mathematical model for chronic myeloid leukemia (CML) treatment and mechanistic interpretation of the bi-phasic decline. (A) Schematic model representation with three cell types: quiescent (X, blue) and proliferating (Y, red, turnover with rate pY) leukemic stem cells (LSCs), and differentiated leukemic cells (LCs), denoted by W (green, generated with rate pW, decaying with rate rW). The model assumes (i) mechanisms of activation/deactivation of quiescent/proliferating LSCs with rates pXY and pYX and (ii) a cytotoxic effect of TKI on proliferating LSCs with intensity eTKI. (B) The mechanistic model parameters [(TKI net effect (q=eTKI−pY), activation rate of quiescent LSCs (pXY), deactivation rate of proliferating LSCs (pYX)] were fitted to individual patient data from the IRIS and CML-IV trials.18,19 The resulting distributions reveal an intrinsic scaling between them, which are dispersed over different orders of magnitude. (C) Model simulation with median parameter values obtained from IRIS and CML-IV data illustrating the equivalence between tumor load (in terms of BCR-ABL1 levels) in the peripheral blood (green) and within the proliferating LSCs (red). Values on the y-axis indicate the relative abundance of BCR-ABL1 positive cells in each specific cell compartment [see equation (SE1) in Online Supplementary Text S1], which corresponds to the tumor load in terms of PCR-based measurements of the BCR-ABL1/ABL1 ratio. We adopted this scheme for all corresponding figures throughout the manuscript. Using the intrinsic scaling (B), the slopes in the bi-exponential decline of the BCR-ABL1 levels simplify to α≈−q and β≈−pXY. The abundance of quiescent LSCs follows a monophasic decline approximated by β≈−pXY. See Online Supplementary Text S3 for parameter values used in all model simulations. (D) During the initial phase (upper panel, “1st slope”), eradication of the proliferating LSCs (red) with effective rate q is the dominating process (large black arrow). After the strong initial reduction, few proliferating cells remain (lower panel, “2nd slope”) and eradication is now limited by the activation rate pXY (small black arrow) of quiescent LSCs (blue). Normal cells are shown in gray. See also Online Supplementary Figure S2.
- Figure 2.
Model predictions on dose de-escalation and dose escalation. (A) The long-term treatment efficiency, defined as the magnitude of the second slope β, is shown as a function of the dose reduction. The threshold for optimal favorable reduction, fOPT (≈25% in this example, i.e. using median parameters as in Figure 1C) indicates how much the standard dose can be reduced without losing treatment efficiency. fOPT can be calculated for each patient (see main text). Any other favorable dose reductions (dose fraction f>fOP, green region) also retain the long-term treatment efficiency, while unfavorable dose reductions (dose fraction f<fOPT, red region) are predicted to lead to a severe decrease in the long-term treatment efficiency. (B-E) Simulations of favorable (B), optimal favorable (C) and unfavorable (D and E) dose reductions after 36 months under standard dose. After favorable dose reductions, a transient increase in proliferating leukemic stem cells (LSCs) (red) is followed by a return to the original decrease rate β≈−pXY, while the dynamics of quiescent LSCs remains unchanged (blue lines). In the case of unfavorable reduction, an impaired scenario is observed. See also Online Supplementary Figures S3–S6. (F) dose escalation to f=200% after three years of treatment; although a deeper level is reached in the BCR-ABL1 levels of proliferating LSCs, the dynamics of quiescent LSCs remains unchanged.
- Figure 3.
Step-wise treatment optimization. (A) Step 1: initial treatment with standard dose until the patient shows a clearly identifiable second slope (approx. 18 months) and determination of the bi-exponential parameters (A, B, α, β). (B) Step 2: reduction of tyrosine kinase inhibitor (TKI) dose by half and continuous monitoring of the treatment response until the new intercept B′ can be inferred (approx. 18 months). (C) Step 3: reduction to the optimal dose calculated from values of the identified parameters (A, B, B’, α, β; see main text). (D) The long-term follow up using optimal dose shows that the response to this adaptive treatment adheres to the original slope β for the eradication of residual leukemic stem cells (LSCs) as standard dose treatment. Although the adapted treatment leads to a delay in the reduction of BCR-ABL1 levels in proliferating LSCs and, therefore also in the peripheral blood, the treatment dynamics in the residual quiescent LSCs are unaltered while drug intake is drastically reduced.
- Figure 4.
Model predictions on dose de-escalation and comparison with clinical data. (A) Comparison of DESTINY interim results with model simulations of 50% dose de-escalation applied to IRIS and CML-IV patient data (assuming the same protocol and patient selection criteria of DESTINY). We simulated dose de-escalation starting from the individually predicted remission level at the time of the last BCR-ABL1 measurement of each patient, and evaluated the fraction of patients above MR3 one year after de-escalation. Error bars indicate 90% confidence intervals. (B) Model estimates of the risk of losing MR3 within one year after de-escalation, depending on the patient’s individual predicted remission level just before de-escalation. Patients with remission level above MR3.5 are very likely to lose MR3 at least transiently. (C) Model simulation illustrating the transient relapse above MR3 three months after de-escalation (highlighted time interval). De-escalation of 50% was implemented for a hypothetical patient of the DESTINY trial one year after reaching MR3. The simulation of a continuing half-dose regimen predicts that after about nine months the BCR-ABL1 levels fall below MR3 and the response regains the original slope β. (D) Simulation results showing the predicted relative increase/decrease in the number of patients without molecular relapse two years after cessation. We use the standard treatment scenario (full-dose for one year) as the reference (corresponding to the dashed line at 0%) to compare it with: i) half-dose for one year (the DESTINY protocol; red), and ii) half-dose for two years (blue). Relapse is defined as loss of MR3.
Vol 103 Issue 11
