Experimental data.

<p>A: Data for tumor growth. B: Data for stem cell percentage. This data plot was redrawn from Figs 1B and 1C in [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005920#pcbi.1005920.ref008" target="_blank">8</a>], where they generated tumor xenografts by transplanting primary human cancer stem-like cells in SCID mice without human endothelial cells.</p

Variables related to anti-IL-6R treatment model.

<p>Variables related to anti-IL-6R treatment model.</p

Impact of the amplification factor, <i>A</i>_<i>in</i> and the differentiated cell death rate, <i>δ</i>_<i>D</i> on tumor growth.

<p>Model predictions of the tumor volume vs. time for the control cases as well as for treatment with 1 or 5 mg/kg TCZ when A: the amplification factor, <i>A</i>_<i>in</i>, is slightly increased from its baseline value and when C: the differentiated cell death rate, <i>δ</i>_<i>D</i> is slightly decreased from baseline. Model predictions of the CSC percentage vs time for the control cases as well as for treatment with 1 or 5 mg/kg TCZ when B: the amplification factor, <i>A</i>_<i>in</i>, is slightly increased and when D: the differentiated cell death rate, <i>δ</i>_<i>D</i> is slightly decreased (D).</p

A mathematical model for IL-6-mediated, stem cell driven tumor growth and targeted treatment

<div><p>Targeting key regulators of the cancer stem cell phenotype to overcome their critical influence on tumor growth is a promising new strategy for cancer treatment. Here we present a modeling framework that operates at both the cellular and molecular levels, for investigating IL-6 mediated, cancer stem cell driven tumor growth and targeted treatment with anti-IL6 antibodies. Our immediate goal is to quantify the influence of IL-6 on cancer stem cell self-renewal and survival, and to characterize the subsequent impact on tumor growth dynamics. By including the molecular details of IL-6 binding, we are able to quantify the temporal changes in fractional occupancies of bound receptors and their influence on tumor volume. There is a strong correlation between the model output and experimental data for primary tumor xenografts. We also used the model to predict tumor response to administration of the humanized IL-6R monoclonal antibody, tocilizumab (TCZ), and we found that as little as 1mg/kg of TCZ administered weekly for 7 weeks is sufficient to result in tumor reduction and a sustained deceleration of tumor growth.</p></div

IL-6R sensitivity/PRCC values for the parameters using the fractional occupancy of IL-6R on CSCs as the output of interest.

<p>IL-6R sensitivity/PRCC values for the parameters using the fractional occupancy of IL-6R on CSCs as the output of interest.</p

IL-6R occupancy post-treatment.

<p>A: Model prediction of the fraction of IL-6 receptors on CSCs over time that are occupied by IL-6, <i>ϕ</i>_<i>S</i>, for the control case (no treatment, blue), 1 mg/kg TCZ (red), and 5 mg/kg TCZ (yellow). B: Model prediction of the fraction of IL-6 receptors on CSCs over time that are occupied by TCZ, <i>ϕ</i>_<i>I</i>, for doses of 1 mg/kg TCZ (blue), and 5 mg/kg TCZ (red).</p

Numerical simulations of pre-treatment tumor growth, CSC percentage, and IL-6R fractional occupancy.

<p>A: Best fit of the mathematical model prediction of tumor volume over time to the IL-6+/+ data for primary tumors implanted without human endothelial cells in [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005920#pcbi.1005920.ref008" target="_blank">8</a>]. The green curve in (A) shows the special case in which the tumor cells are not producing IL-6, <i>ρ</i> = 0. B: Comparison of the experimentally measured percentage of CSCs in primary tumors (brown), the experimentally measured percentage of CSCs on day 121 for tumors grown in IL-6 +/+ mice (blue), and the mathematical model prediction percentage of CSCs on day 121 (red). C: Model prediction of the temporal changes in the fractional occupancy of IL-6 receptors on CSCs, <i>ϕ</i>_<i>S</i>. D: Model prediction of the stem cell percentage over time.</p

Impact of dose frequency.

<p>Model predictions of the tumor volume vs. time for the control case (no treatment) as well as for treatment with 1 mg/kg TCZ administered every 7, 14, 21 and 28 days. The line shows the first day of the final dose for each treatment schedule.</p

List of model variables.

<p>List of model variables.</p

Parameter values taken from the literature and their sources.

<p>Parameter values taken from the literature and their sources.</p