Why one-size-fits-all vaso-modulatory interventions fail to control glioma invasion: in silico insights

Abstract

Gliomas are highly invasive brain tumours characterised by poor prognosis and limited response to therapy. There is an ongoing debate on the therapeutic potential of vaso-modulatory interventions against glioma invasion. Prominent vasculature-targeting therapies involve tumour blood vessel deterioration and normalisation. The former aims at tumour infarction and nutrient deprivation induced by blood vessel occlusion/collapse. In contrast, the therapeutic intention of normalising the abnormal tumour vasculature is to improve the efficacy of conventional treatment modalities. Although these strategies have shown therapeutic potential, it remains unclear why they both often fail to control glioma growth. To shed some light on this issue, we propose a mathematical model based on the migration/proliferation dichotomy of glioma cells in order to investigate why vaso-modulatory interventions have shown limited success in terms of tumour clearance. We found the existence of a critical cell proliferation/diffusion ratio that separates glioma responses to vaso-modulatory interventions into two distinct regimes. While for tumours, belonging to one regime, vascular modulations reduce the front speed and increase the infiltration width, for those in the other regime, the invasion speed increases and infiltration width decreases. We discuss how these in silico findings can be used to guide individualised vaso-modulatory approaches to improve treatment success rates.

The biology and mathematical modelling of glioma invasion: a review

“…This model also supported previous findings in suggesting that glioma growth and invasion depend on a non-trivial trade-off between the proliferation and migration switching rates. More recently, the overall effects of vasoocclusive events and vascular normalization on the glioma front speed and infiltration width were investigated by Alfonso et al [32]. The existence of critical parameter regimes that distinguish between different glioma invasive patterns with respect to variations in the vaso-occlusion rate was predicted as an emergent consequence of the 'Go-or-Grow' plasticity.…”

“…Although the proposed mathematical model replicates clinical and therapeutic features of glioblastoma, the simulation results do not necessarily disprove the 'Goor-Grow' mechanism of glioma cells. Previous 'Go-or-Grow' models consider local cell density-dependent diffusive migration of glioma cells [28,31,32,168]. The 'Go-or-Grow' model of Scribner et al [167] assumes a different cell migration mechanism, namely a directed movement of glioma cells (by advection) towards high densities of normal brain cells.…”

“…Mathematical models and computational approaches have become increasingly abundant in cancer research to study tumour dynamics and responses to treatment modalities such as chemo-and radiotherapy [17][18][19][20]. Mathematical modelling provides a useful theoretical framework to perform in silico experiments, as well as to evaluate assumptions and make predictions that can be experimentally tested [21][22][23][24][25][26][27][28][29][30][31][32]. In the last two decades, several mathematical models have been developed to investigate key mechanisms governing glioma growth and invasion [23,[33][34][35].…”

Temporally feathered intensity‐modulated radiation therapy: A planning technique to reduce normal tissue toxicity

“…Furthermore, we assume that both the delivery of each treatment fraction and response to radiation are instantaneous. We notice that similar dynamical models have been previously proposed to simulate the effect of radiation on brain and lung tumors, as well as to define an organ‐specific NTCP model …”

“…The dynamical NTCP model considered in this work parallels prior similar models which have been proposed to simulate radiation effects on different tumor types, as well as in healthy tissues . The current BED formulation is limited by the lack of a temporal recovery term of radiation‐induced damage, and therefore are not suitable models to compare radiation schema with various fractionations over time.…”