Abstract 925: In silico models accurately predict in vivo response for IL-6 blockade in head and neck cancer

Abstract

Abstract The purpose of this study is to create and validate a mathematical model describing the effect of interleukin-6 (IL-6) on head and neck cancer growth and cancer stem cell fraction. Head and Neck Squamous Cell Carcinoma (HNSCC) is the seventh most-common solid tumor with about 55,000 new cases diagnosed every year. Malignant features of HNSCC cells are derived from a shift towards more stem-like features, as postulated by the cancer stem cell (CSC) hypothesis. CSCs encompass a unique cellular subpopulation characterized by multipotency, uniquely high tumorigenic potential, and self-renewal. These cells function as putative drivers of tumor initiation, therapeutic evasion, metastasis, and recurrence. Though they are an appealing conceptual target, CSC directed cancer therapies remain scarce. High levels of both serum IL-6 and tumor IL-6 receptor (IL-6R) expression are strongly correlated with poor patient survival. Endothelial cell-secreted IL-6 enhances the tumorigenic potential and self-renewal of head and neck CSCs. Furthermore, interruption of the IL-6 pathway results in a decreased fraction of HNSCC CSCs. Efficacy and optimal administration of the FDA approved rheumatoid arthritis IL-6R antibody Tocilizumab in HNSCC is not known. Here we used a multi-scale mathematical model that operates at the intracellular, molecular, and tissue level to investigate the impacts of endothelial cell-secreted IL-6 signaling on the crosstalk between tumor cells and ECs during tumor growth. This endothelial cell - tumor cell (EC-TC) model was used to study the effect of tocilizumab treatment on HNSCC, and particularly the CSC fraction. Our ordinary differential equation model is the first of its kind to include full occupancy dynamics between endothelial-cell produced IL-6, IL-6R, and the competitive IL-6R inhibitor Tocilizumab. In order to biologically validate the utility of our mathematical model, we performed a series of in-vivo experiments using HNSCC cell lines and human endothelial cells co-embedded in a porous scaffold and implanted in SCID mice flank. Tumor volumes were measured serially. CSC fraction was determined in HNSCC cell lines using flow cytometry for aldehyde dehydrogenase (ALDH) high/CD44 high proportion. Without artificial tuning to the laboratory data, our model provided superb predictive agreement to the decrease in tumor volumes observed in TCZ treated mice (r = 0.947, p < 0.0001), as well as a decrease in CSC fraction. This predictive in-silico framework can serve to rapidly evaluate dosing strategies for IL-6 pathway modulation, as well as providing the basis for proposing combination treatments with IL-6 blockade and cytotoxic or other targeted therapies. Citation Format: Fereshteh Nazari, Alexandra E. Oklejas, Jacques E. Nör, Alexander T. Pearson, Trachette L. Jackson. In silico models accurately predict in vivo response for IL-6 blockade in head and neck cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 925.