Page 316 - Advances in Biomechanics and Tissue Regeneration

314 16. ON THE SIMULATION OF ORGAN-ON-CHIP CELL PROCESSES

TME could help to better understand the evolution of the disease and would provide a tool for testing new drugs and
reducing animal experiments. However, there is still an important lack of predictive power of currently available
in vitro models, with this being one of the main reasons for the continuous drop of new drugs appearing per billion
dollars invested [12, 13].
For example, many authors report strong changes in cell functions when cells are cultured in three dimensions (3D)
compared with those in two dimensions (2D) (drug resistance, number, and specificity of focal adhesions) [14]. Despite
this, cells are usually cultured on the traditional Petri dishes, where tumor complexity is mostly lost, which explains the
efforts made to reproduce three-dimensionality in in vitro experiments [15]. Recently, microfluidics has arisen as a
powerful tool to recreate the complex microenvironment that governs tumor dynamics [16, 17]. This technique allows
reproducing important features of tumor evolution that were not seen before in 2D cultures as well as testing drugs in a
much more reliable and efficient way. In particular, one of the most important fields of application of microfluidics in
cell culture has been the study of chemotactic processes such as tumor-induced angiogenesis [18], tumor invasion [19],
tumor intravasation [20], tumor extravasation [21], and metastasis [22], among others.
One particular case of cancer is the type that affects the central nervous system (CNS). According to the American
Brain Tumor Association, the primary tumors of the CNS make up about 2% of all cancers in adults and 20% in chil-
dren. Of these, different types of astrocytomas account for 76% of gliomas. Astrocytomas are classified in four different
degrees to describe their level of abnormality and their degree of malignancy, with grade one having the best prognosis
and grade 4, which is known as a glioblastoma (GBM), being the most aggressive. Survival of patients with this type of
tumor who undergo the first-line standard treatments (local radiotherapy and chemotherapy with concomitant temo-
zolomide) has a median of 14 months since diagnosis and has a 5-year survival rate of less than 10% [23, 24]. It is char-
acterized by rapid growth and a high level of malignancy, being, unfortunately, the most frequent type of brain tumor
with an incidence of 17% of all primary tumors.
GBM is a highly infiltrating and fast-progressing tumor, characterized by two main histopathological conditions:
necrotic foci typically surrounded by areas of high cellularity known as pseudopalisades, and microvascular hyper-
plasia [25, 26]. In an early stage, GBM proliferation and secretion of procoagulant signals would cause thrombotic
events, leading to hypoxia and nutrient depletion. As a consequence, GBM cells start to migrate toward enriched
regions guided by this nutrient and oxygen gradient; this leads to the generation of the characteristic GBM pseudo-
palisades. These migrating cells would reach other healthy blood vessels, allowing GBM cell proliferation. Eventually,
GBM cells will cause again the collapse of this blood vessel, restarting the process and creating an expanding wave of
migrating tumor cells across the brain. Thereby, it has been proposed that one of the driving forces of glioma aggres-
siveness is the nutrient and oxygen starvation due to thrombotic events [27]. Recent histological studies have shown
that proliferation in pseudopalisading areas is significantly lower while apoptosis is substantially larger than in neigh-
boring regions. This evidence suggests that pseudopalisades are due to causes other than simply higher proliferation
or survival rates [26]. In recent studies, it has been described that at least 50% of the pseudopalisades have a central
occluded blood vessel and that GBM cells express several procoagulant factors [28] and hypoxia-induced factor-1
(HIF-1) [29], responsible for the vascular hyperplasia characteristic of GBM.
However, and despite these new experimental possibilities, the complexity and heterogeneity of the TME as well as
of its dynamic interactions with tumor cells make it difficult to separate effects, check new hypotheses, and quantify the
effect of every parameter for predicting the outcome in what if situations, even in these more realistic and controlled
conditions. To get this, the only way is to combine the new possibilities of in vitro assays with the quantitative power
and versatility of mathematical modeling and computational techniques [30, 31]. There have been many attempts to
build mathematical models to describe how these tumors grow and respond to therapies [32–36]. In particular, a recent
review [37], besides reviewing the mathematical models available to incorporate the main components of the TME,
analyzes aspects such as the importance of the hypoxic environment for GBM progression and in the formation of
cellular pseudopalisades [38]; tumor vasculature formation (including angiogenesis, and vessel cooption, remodeling
and regression), the role of biophysical and biomechanical properties of the ECM in tumor cell invasion, the intravas-
cular fluid microenvironment, tumor cell migration and dissemination through the lymphatic network, or the role of
microenvironmental niches and sanctuaries in the emergence of acquired drug resistance in tumors. Also, in previous
works in our group, we demonstrated the possibility of developing GBM pseudopalisades in vitro [39].
One of the main problems in these models is the lack of reliable values for the many parameters involved, which
many times forces us to rely on approximations derived from very different situations, leading sometimes to unreliable
conclusions.
In this chapter, we present a new mathematical framework to model the behavior of cell processes in vitro using
microfluidic devices, especially for modeling the process of pseudopalisade formation in such devices. The first section
describes the particular problem analyzed and the experiments performed in the microfluidic device as well as the

II. MECHANOBIOLOGY AND TISSUE REGENERATION