Abstract
The development and clinical testing of drug combinations for the treatment of Non-Hodgkin Lymphoma (NHL) and other cancers has recently shown great promise. However, determining the optimum combination and its associated dosages for maximum efficacy and minimum side effects is still a challenge. This paper describes a parametric analysis of the dynamics of malignant B-cells and the effects of an anti-sense oligonucleotide targeted to BCL-2 (as-bcl-2), anti-CD-20 (rituximab) and their combination, for a SCID mouse human lymphoma xenograft model of NHL. Our parametric model is straightforward. Several mechanisms of malignant B-cell birth and death in the nodal micro-environment are simulated. Cell death is accelerated by hypoxia and starvation induced by tumor scale, by modification of anti-apoptosis with as-bcl-2, and by direct kill effects of rituximab (cell kill by cytotoxic immune cells is not included, due to the absence of an immune system in the corresponding experiments). We show that the cell population dynamics in the control animals are primarily determined by K*, the ratio of rate constants for malignant cell death, Kd, and cell birth, Kb. Tumor growth with independent treatments is reproduced by the model, and is used to predict their effect when administered in combination. Malignant cell lifetimes are derived to provide a quantitative comparison of the efficacy of these treatments. Future experimental and clinical applications of the model are discussed.
Highlights
The development and clinical testing of drug combinations for the treatment of non-Hodgkin Lymphoma (NHL) and other cancers has recently shown great promise [1]
This study addresses several questions: 1. Can a parametric model quantitatively simulate the separate effects of as-bcl-2 and anti-CD-20 compared to the control?
The model does not accurately predict the combination treatment data. This is because the value of K9 (0.09) for the as-bcl-2 data is slightly less than that of K* (0.11) derived for the control, which is the opposite of the anticipated effect
Summary
The development and clinical testing of drug combinations for the treatment of non-Hodgkin Lymphoma (NHL) and other cancers has recently shown great promise [1]. Determining the optimum combination and its associated dosages for maximum efficacy and minimum side effects is still a challenge. Can a parametric model quantitatively simulate the separate effects of as-bcl-2 and anti-CD-20 compared to the control?. 2. Can the benefits of each therapy relative to the control be quantitatively measured in terms of reduced malignant cell lifetimes?. 3. Can the model quantitatively simulate the combined effects of these therapies without introduction of additional parameters?. 4. Can the model use the independently determined key parameters for individual therapies to predict their combined efficacy?
Published Version (Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have