On the Simulation of Organ-on-Chip Cell Processes: Application to an In Vitro Model of Glioblastoma Evolution

Abstract Microfluidic systems have emerged as a technique with the potential to recreate biomimetic microenvironments that permit in vitro modeling of several important organ functions (organ-on-chip) as well as to analyze cellular processes. This allows designing experiments for validating scientific hypotheses and better understand complex biological processes, and determine biological parameters in an unprecedented way. The crosstalk between this new experimental capacity and mathematical models within a general framework is extensively discussed in this chapter, reviewing the formulation of cell processes, together with their interaction with the surrounding environment. Also, its particularization to a particular problem of interest such as the analysis of tumor evolution, which can be modeled in organ-on-chip devices. One of the important cases of the solid tumors is glioblastoma (GBM), the most lethal primary brain tumor. One of the characteristics in such types of tumors is the appearance of hypercellularized regions, named as pseudopalisades. These structures have been hypothesized to be produced by oxygen and nutrient depletion caused by tumor-induced blood vessel occlusion. However, despite the important instrumental role of these pseudopalisades in GBM's spread and invasion, the recreation of these in vitro has remained challenging. To analyze this problem, we designed a microdevice that comprises a central microchamber flanked by two lateral microchannels, separated by a series of projections. GBM cells were then embedded within a collagen hydrogel in the central microchamber thereby mimicking the three-dimensional structure and distribution. The lateral microchannels were used to perfuse different media or drugs, so normoxic, hypoxic, and necrotic regions may be naturally generated. In this chapter, we detail the model itself and the fitting of the model parameters. We compare the experimental and numerical results and we discuss the experimental trends and the underlying hypotheses.