Although in vitro models can never capture a complete representation of the tumor microenvironment, they can be useful for examining the effect of its most salient features on cellular metabolism, including physical properties of the matrix and the impact of fluid transport. One of the greatest challenges in studying metabolism is navigating between levels of space, time, and complexity, from molecular details to whole-body physiology. This is one area in which new tissue-engineered model systems are proving especially useful.
Conventional in vitro assays are largely based on monotypic populations of cells cultured on plastic or glass substrates. Monolayer cultures of homogeneous cells, or mouse xenografts derived from commercial cell lines, diverge from the original tumor, most notably through the dramatic loss of heterogeneity and tissue structure. Microarray-based comparisons of cancer cells in two-dimensional (2D) versus 3D culture revealed broad changes in hypoxia response and proinflammatory pathways (>34). These observations reflect a growing consensus that the culture environment is a critical determinant of cell behavior and that 3D models may be able to recapitulate changes in cellular metabolism that cannot be studied using conventional in vitro approaches.
Varying degrees of complexity can be accomplished with 3D culture techniques. Simply embedding cells within 3D substrates can restore a mélange of important functions, including 3D morphogenesis, assembly of multiprotein adhesions, secretory functions, and tissue homeostasis. However, “3D culture” has become an umbrella term that obscures a more nuanced reality. There are many differences between 2D, 3D, and physiological settings; dimensionality is complicated by the numerous parameters that define each model system. For example, “matrix mechanics” encompasses fiber architecture and conformation, matrix composition and porosity, covalent and ionic cross-linking, cell density, polarity, and contractility. Similarly, “mass transport” not only is a question of vascular proximity but also involves osmotic and hydrostatic pressure gradients, fluid viscosity and shear stress, cell density and metabolic activity, concentrations of ions and dissolved gases, and matrix binding kinetics. Functional consequences emerge from the integrative effects of these manifold variables, rather than from a perfunctory switch from 2D to 3D. 3D assays provide demonstrable evidence that context is important, but we must carefully consider how various features of the experimental system provide instructive cues that alter cell behavior, especially with regard to metabolic programming. Because many physical factors can affect tumor metabolism by altering nutrient availability, it is also critical to consider that media composition alone can have profound effects on metabolic wiring and regulation. This was highlighted by a recent study showing that culturing cells with human plasma-like medium affected their metabolism, including the metabolome, redox state, and glucose utilization (>35).
Emerging tissue-engineering technologies now provide attractive tools to control the physical microenvironment for studies of cancer cell metabolism. Hydrogel-based biomaterials are frequently the basis for 3D culture, and a catalog of natural and synthetic materials is available to support cell adhesion, viability, and remodeling; nutrient and waste exchange; and appropriate mechanical properties. Natural materials have inherent biological functions, such as adhesive ligands and cleavage sites, but it can be difficult to precisely define and manipulate the composition and/or structural properties. On the other hand, synthetic gels afford greater control over materials properties, and can be readily manipulated with biological moieties, but lack the biological complexity of native tumor-associated ECM. Nevertheless, it should be kept in mind that cells remodel their ECM environment over time. Hence, the ECM that exists at any given time will differ from its initial state, which, in turn, will influence the type of ECM that will be deposited.
Both natural and synthetic materials are readily integrated with microfluidic technologies to recapitulate matrix mechanics and fluid transport processes that affect tumor metabolism. For example, microfluidic biomaterials can be generated using a confined gel, whereby microchannels are patterned within a transparent silicone mold (>36). Alternatively, dense hydrogels allow imprinting of microfluidic conduits directly within the scaffold to control the spatial and temporal gradients of exogenous factors or drugs, reminiscent of microvascular function (>37, >38). In addition to forming predefined vascular structures, endothelial cells can also be mixed into natural or synthetic ECMs to allow them to assemble into microvascular networks that model those of primary tumors (>39). These strategies have been used to construct biomimetic vascularized tissue constructs to recapitulate the individual and combinatorial effects of matrix structure, solute transport, and cellular composition that define the metabolic environment.
Microfluidic biomaterials can also be integrated with live cell imaging techniques to acquire spatial and temporal information about the complex interdependencies between the microenvironment and cell metabolism. These tools can be used to readily manipulate and measure real-time, single-cell dynamics by using endogenous or genetically encoded fluorescent sensors. For example, a vascularized microtumor (VMT) model was used to map metabolic activity within different regions of hybrid microfluidic organoids via fluorescence lifetime imaging of NAD+ (nicotinamide adenine dinucleotide) and NADH (reduced form of NAD+) (>40). The VMT platform mimicked stromal composition, matrix structure, and vascular function, and it simulated metabolic responses to pharmacologic agents (>40).
Advances in biomaterials and microfabrication technologies (like the VMT model described above) afford new methods to integrate vascular, stromal, and epithelial compartments with precise arrangements of parenchymal and interstitial elements (>41). In addition, emerging tissue culture techniques have produced a new generation of microphysiological devices (“tissue chips”) that capture increasingly accurate representations of whole organs, including liver, kidney, heart, lungs, brain, gastrointestinal (GI) system, blood vessels, skin, adipose, cervix, uterus, and ovaries (>41). Originally designed for preclinical drug screening, organ-on-a-chip models have been used to simulate first-pass metabolism; activation of anticancer prodrugs; synergistic actions of drug combinations; modulation of tissue bioavailability; membrane barrier function; off-target toxicity; and mechanisms of drug adsorption, distribution, metabolism, and excretion (>42). Tumor metabolism is a multiscale phenomenon, and these platforms make it possible to simulate higher-order metabolic regulation in vitro.
The next milestone for microphysiological platforms involves the serial integration of multiple organs within a single device. A complete “body-on-a-chip” would simulate interactions between organs, such as drug adsorption through the GI tract, metabolism in the liver, clearance in the kidneys, and cytotoxic effects in the heart or other tissues (>42). Already, pioneering systems have been strategically validated as physical analogs for pharmacokinetic/pharmacodynamic modeling (>43). By carefully controlling tissue volume and fluid residence time, integrated microphysiological systems can mimic drug distribution, uptake, and activity in surrogate organs (>44). One such platform predicted nontarget drug retention in adipose tissue and nephrotoxicity. Similarly, a commercial model called Hurel was instrumental for identifying drug metabolites that were not present in traditional, monotypic cell culture (>45).
Collectively, microphysiological devices present a promising opportunity to navigate across cell, tissue, and organ systems when investigating cancer metabolism and drug response. Microtissue devices are not delicate “artisan” products but increasingly robust platforms for broad application in the laboratory and the clinic. Several platforms are commercially available, with high simplicity, reliability, and throughput, making these technologies suitable for implementation in non-engineering laboratories.
Source : http://stm.sciencemag.org/content/10/442/eaaq1011.full