In silico experimentation of glioma microenvironment development and anti-tumor therapy

Abstract

Tumor cells do not develop in isolation, but co-evolve with stromal cells and tumor-associated immune cells in a tumor microenvironment mediated by an array of soluble factors, forming a complex intercellular signaling network. Herein, we report an unbiased, generic model to integrate prior biochemical data and the constructed brain tumor microenvironment in silico as characterized by an intercellular signaling network comprising 5 types of cells, 15 cytokines, and 69 signaling pathways. The results show that glioma develops through three distinct phases: pre-tumor, rapid expansion, and saturation. We designed a microglia depletion therapy and observed significant benefit for virtual patients treated at the early stages but strikingly no therapeutic efficacy at all when therapy was given at a slightly later stage. Cytokine combination therapy exhibits more focused and enhanced therapeutic response even when microglia depletion therapy already fails. It was further revealed that the optimal combination depends on the molecular profile of individual patients, suggesting the need for patient stratification and personalized treatment. These results, obtained solely by observing the in silico dynamics of the glioma microenvironment with no fitting to experimental/clinical data, reflect many characteristics of human glioma development and imply new venues for treating tumors via selective targeting of microenvironmental components.

Figure 1. Stochastic population dynamics of glioma cells, glioma stem cells, astrocytes, and microglial cells.

(a) Schematic representation of the intercellular signaling network in GBM. The network comprises 5 types of cells and a panel of 15 cytokines. The processes involving cytokine or chemokine mediation are described by solid lines, while the other processes representing changes of cell states are depicted by dashed lines. A detailed description of the ODEs and parameter settings are in Supporting Text S1. (b) One-year evolution of five types of cells showing three distinct phases: pre-tumor phase (I), rapid expansion phase (II), and malignant phase (III). (c) Dynamics of stem cell activation. (d) Dynamics of microglia cells. (e) Temporal change of total cell concentration. (f) Snapshots of temporal progression of tumor from a 3D Monte Carlo simulation. Supporting Video S1 is the complete video showing the one-year evolution. QSC, quiescent stem-like cell. ASC, activated stem-like cell.

Figure 2. Cytokine dynamics.

(a) Change of concentrations for all 15 cytokines in the microenvironment over a period of one year. (b) Normalized cytokine concentration change over a period of one year. It shows three types of cytokine dynamics based upon the temporal traces. TNF-α peaks at the end of phase I. IL10 and PGE2 show constant increase regardless the growth phases of glioma cells. Other cytokines are apparently correlated to the three-phase growth dynamics.

Figure 3. Microglia depletion therapy.

This therapy was given to three randomly designed virtual patients (Supporting Table S5) and administered at different stages corresponding to glioma cell (GC) concentration ∼5×10⁴/ml, 2×10⁵/ml, and 1×10⁶/ml, respectively. (a) Response of patient 1 to therapies given at different stages. (b) Response of patient 2 to therapies given at different stages. (c) Response of patient 3 to therapies given at different stages. (d) Snapshots of a 3D simulation showing the evolution of tumor microenvironment in patient 1 in response to microglia depletion therapy. Supporting Video S2 shows the full video.

Figure 4. Cytokine combination therapy.

This was given to the same three virtual patients (Supporting Table S5) and administered at different stages, corresponding to glioma cell (GC) concentration ∼1×10⁶/ml, 5×10⁶/ml, 1×10⁷/ml, and 2×10⁷/ml, respectively. (a) Sensitivity analyses reveal the pro-tumorigenic potential of each cytokine in the examined tumor microenvironment. Supporting Table S7 summarizes all the parameters (u1–u29), surface receptor expression level. (b) Comparison of therapeutic efficacy between single-target and combination therapies. The combination therapy results in a striking synergistic effect to suppress tumor progression whereas any single target treatment does not show appreciable benefit. (c) Reponses of three patients to the same combination therapy, which is tailored to give optimum response for patient 1 based upon sensitivity analysis. (d) Snapshots showing tumor development in patient 1 with or without combination therapy. The therapy is give at a single dose when the glioma cell density reaches 1×10⁶/ml or 5×10⁶/ml. Supporting Video S3 is the complete video showing the one-year evolution.