Biomaterials for 3D Tumor Modeling (Materials Today)

Biomaterials for 3D Tumor Modeling
Copyright
Contents
List of Contributors
Preface
1 Trends in biomaterials for three-dimensional cancer modeling
	Abbreviations
	1.1 A historical introduction
		1.1.1 In vitro and in vivo models: an overview
		1.1.2 A paradigm shift
		1.1.3 Three-dimensional biomaterials for cancer modeling
		1.1.4 From the lab to the clinic
	1.2 The three-dimensional tumor microenvironment
		1.2.1 The tumor and its three-dimensional environment: a synergistic interaction
		1.2.2 Biomaterials as a model of the tumor niche
			1.2.2.1 Scaffold-based biomaterials
			1.2.2.2 Matrix-based
			1.2.2.3 Microcarrier-based
			1.2.2.4 Scaffold-free: tumor spheroids
			1.2.2.5 Microstructured surfaces
	1.3 Engineering the native tumor microenvironment using custom-designed three-dimensional biomaterials
		1.3.1 Tissue engineering approaches
			1.3.1.1 Freeze-drying
			1.3.1.2 Photopolymerization
			1.3.1.3 Three-dimensional bioprinting
		1.3.2 Nanotechnology approaches
			1.3.2.1 Molding
			1.3.2.2 Printing
				1.3.2.2.1 (Two-dimensional) microcontact printing
				1.3.2.2.2 Three-dimensional printing
				1.3.2.2.3 Four-dimensional printing
	1.4 Advanced models of the three-dimensional tumor microenvironment
		1.4.1 Microfluidics-based models
			1.4.1.1 Microfluidic-based models of tumors: tumor-on-a-chip
			1.4.1.2 Drug discovery and screening on-chip
			1.4.1.3 Reproducing dynamic events on-chip
			1.4.1.4 Personalized tumor-on-a-chip models
			1.4.1.5 Manufacturing methods of a tumor-on-a-chip
		1.4.2 Three-dimensional bioprinted models
	1.5 Applications of three-dimensional tumor models in cancer therapeutics
		1.5.1 Drug discovery, development, and screening
		1.5.2 Transport and delivery of drugs
	1.6 Limitations of biomaterials-based three-dimensional tumor models
	1.7 Future of three-dimensional biomaterials for cancer research
	1.8 Final remarks and conclusions
	References
2 Bioinspired biomaterials to develop cell-rich spherical microtissues for 3D in vitro tumor modeling
	2.1 Introduction
	2.2 Human Tumor microenvironment—key hallmarks to mimic in vitro
	2.3 3D In vitro tumor models—bridging the gap from 2D flat cultures to in vivo
	2.4 Classes of 3D multicellular tumor models
		2.4.1 Scaffold-free cell-rich 3D multicellular tumor spheroids
		2.4.2 Scaffold-based 3D multicellular tumor models
			2.4.2.1 Biomaterials for establishing physiomimetic 3D tumor microenvironments
				2.4.2.1.1 Natural and nature-derived biomaterials for 3D tumor modeling
					Protein-based biomaterials
					Polysaccharide-based biomaterials
				2.4.2.1.2 Synthetic biomaterials for 3D tumor modeling
				2.4.2.1.3 Hybrid biomaterials for 3D tumor modeling
		2.4.3 Generation of spherically structured cell-rich 3D tumor models
			2.4.3.1 Microparticles for spherically structured 3D tumor models assembly
			2.4.3.2 Microgels for spherically structured 3D tumor models assembly
			2.4.3.3 Microcapsules for spherically structured 3D tumor models assembly
	2.5 Conclusions
	References
4 Biomatrices that mimic the cancer extracellular environment
	4.1 Introduction
	4.2 The three-dimensional in vitro models
		4.2.1 Natural-based models
			4.2.1.1 Protein-based systems
			4.2.1.2 Polysaccharide-based systems
			4.2.1.3 Other natural occurring materials
		4.2.2 Synthetic and other biobased models
		4.2.3 Mimicking the tumor microenvironment mechanical features
	4.3 Conclusions and future remarks
	References
5 3D neuroblastoma in vitro models using engineered cell-derived matrices
	5.1 Introduction
	5.2 Neuroblastoma
		5.2.1 Evidence of cell–extracellular matrix interaction in neuroblastoma
	5.3 Cell-derived matrices in tumor modeling
	5.4 Engineering cell-derived matrix deposition
		5.4.1 Cell source
		5.4.2 Culture medium composition
		5.4.3 Culture substrates and conditions
		5.4.4 Decellularization agents
		5.4.5 Chemical and physical modifications
	5.5 Cell-derived matrices and cell morphodynamic characterization
	5.6 Cell-derived matrix capture relevant processes involved in neuroblastoma malignancy
	5.7 Conclusions
	References
6 3D culture systems as models for solid tumors and cancer metabolism
	Abbreviations
	6.1 Introduction
	6.2 Solid tumors: tumor microenvironment and tumorigenesis
	6.3 Cancer metabolism: influence in tumor microenvironment
	6.4 Solid tumors in vitro models
		6.4.1 2D cell culture systems in cancer research
		6.4.2 3D cell culture systems
	6.5 3D cell culture systems in cancer research
	6.6 3D cell culture systems for study cancer metabolism
	6.7 Conclusions
	Conflict of interest
	References
7 Biomaterials as ECM-like matrices for 3D in vitro tumor models
	Abbreviations
	7.1 Introduction
	7.2 Biomaterials as ECM-like matrices for cancer 3D in vitro models
		7.2.1 Synthetic
		7.2.2 Natural-based
			7.2.2.1 Proteins
			7.2.2.2 Polysaccharides
		7.2.3 Decellularized matrices
	7.3 Conclusion and future trends
	References
8 Three-dimensional in vitro models of angiogenesis
	8.1 Vessels formation and tumor angiogenesis
	8.2 Vascular extracellular matrix
		8.2.1 Vascular basement membrane composition
		8.2.2 Interstitial matrix
	8.3 Endothelial cells-based 3D angiogenesis models
		8.3.1 Vascular differentiation in embryoid body
		8.3.2 Tube formation on basement membrane matrix gel
		8.3.3 Sprouting from endothelial cell spheroids in collagen gel
	8.4 Vascular explant-based 3D angiogenesis models
		8.4.1 Rat aortic ring sprouting assay
		8.4.2 Mouse aortic ring sprouting assay
		8.4.3 Human arterial ring angiogenesis assay
	8.5 Microvessels on a chip
		8.5.1 Microfluidics-based devices
		8.5.2 3D bioprinting and sacrificial templating
		8.5.3 Organ-on-a-chip
	8.6 Future perspectives
	References
9 Metastasis in three-dimensional biomaterials
	9.1 Why biomaterial is needed in cancer modeling?
	9.2 Biomaterials employed in tumor ECM modeling
		9.2.1 Naturally derived biomaterials
			9.2.1.1 Collagen
			9.2.1.2 Gelatin
			9.2.1.3 Laminin-rich extracellular matrix
			9.2.1.4 Alginate
			9.2.1.5 Chitosan
			9.2.1.6 Hyaluronic acid
			9.2.1.7 Silk
		9.2.2 Synthetic biomaterials
			9.2.2.1 Polyethylene glycol and its derivatives
			9.2.2.2 Poly(lactic-co-glycolic) acid
			9.2.2.3 Polycaprolactone
			9.2.2.4 Polyacrylamide
			9.2.2.5 Polydimethylsiloxane
			9.2.2.6 Thermoresponsive polymers
	9.3 Properties of cell surrounding matrix/niche contribute to tumor cell migration
		9.3.1 Pore size
		9.3.2 Topography or contact guidance
		9.3.3 Stiffness
		9.3.4 Matrix rheology
		9.3.5 Ligand accessibility
	9.4 Biomaterial-based stepwise modeling of cancer metastasis in vitro
		9.4.1 Tumor initiation and progression
		9.4.2 Tumor angiogenesis
		9.4.3 Modeling of tumor invasion or migration
			9.4.3.1 Spheroids
			9.4.3.2 Transwell-based models
			9.4.3.3 Microfluidic models
		9.4.4 Intravasation models
			9.4.4.1 Prevascularized spheroids
			9.4.4.2 Microfluidic devices
			9.4.4.3 Magnetic force-based cell patterning
		9.4.5 Extravasation and colonization
	9.5 Biomaterial-based in vitro models of cancer dormancy and reactivation
	9.6 Concluding remarks
	References
10 3D cancer spheroids and microtissues
	Abbreviations
	10.1 Introduction
	10.2 Biomaterials advances tumor cell culture to the third dimension
		10.2.1 Biodegradable microcarriers to develop in vitro 3D heterotypic tumor models
		10.2.2 Exogenous extracellular matrix as support for the growth of tumor spheroids
	10.3 Recapitulating the tumor–stroma crosstalk in spheroid and microtissue models
		10.3.1 The role of cancer-associated fibroblasts in promoting cancer progression
		10.3.2 Co-cultured spheroid models
	10.4 Vascularized microtumor models
		10.4.1 Endothelial cells promote invasion and migration of cancer cells
		10.4.2 Multicellular spheroids to recapitulate the tumor angiogenesis
		10.4.3 Tumor microtissues as 3D bioengineered architecture to study cancer vascularization
	10.5 The contribution of immune system cells in microtumors
		10.5.1 Macrophage: the double side of the same player
		10.5.2 Spheroids incorporating the immune system cells
		10.5.3 3D complex architecture to copycat the immune-competence in tumors
	10.6 Spheroids as screening platform for drug testing
		10.6.1 The importance of moving 3D culture to high-throughput screening approaches
		10.6.2 The development of novel methodology for solving high-content imaging problem in preclinical study models
	10.7 Conclusion and future trends
	References
11 Biomaterial-based in vitro models for pancreatic cancer
	11.1 Introduction
	11.2 In vitro 3D models for pancreatic cancer
		11.2.1 Spheroids and organoids
		11.2.2 Hydrogels
		11.2.3 Polymer scaffolds
	11.3 Using 3D models for disease understanding
		11.3.1 Biomimetic role of scaffold features
		11.3.2 Tumor progression and metastasis
	11.4 Using 3D models for therapeutic screening
	11.5 Conclusions and future trends
	References
12 In vitro three-dimensional modeling for prostate cancer
	12.1 Introduction
		12.1.1 Preclinical models for addressing prostate cancer
			12.1.1.1 In vivo models
			12.1.1.2 In vitro models
		12.1.2 Three-dimensional in vitro models of prostate cancer
			12.1.2.1 Spherical cancer models
			12.1.2.2 Bioengineered models
			12.1.2.3 Microfluidic models
			12.1.2.4 Bioreactors
			12.1.2.5 Organ explants
	12.2 Modeling primary tumors
		12.2.1 Modeling localized prostate cancer
			12.2.1.1 Monocellular models of primary tumors
			12.2.1.2 Multicellular models of primary tumors incorporating stromal elements
		12.2.2 Three-dimensional models to address androgen-mediated biology
		12.2.3 Three-dimensional models for prostate cancer stem cells
		12.2.4 Three-dimensional models to address therapeutic response
	12.3 Modeling early stages of prostate cancer progression
		12.3.1 Modeling tumor invasion
		12.3.2 Modeling angiogenesis and the contribution of vessels to tumor progression
		12.3.3 Isolation of circulating tumor cells
		12.3.4 Extravasation
	12.4 Modeling advanced stages of prostate cancer progression
		12.4.1 Disseminated tumor cells
		12.4.2 Three-dimensional models to address the biology of prostate cancer bone metastasis
		12.4.3 Three-dimensional models to address the therapeutic response of metastatic prostate cancer to bone
		12.4.4 Three-dimensional models of metastatic prostate cancer to the liver
	12.5 Conclusion
	References
13 3D in vitro cutaneous melanoma models
	Abbreviations
	13.1 Introduction
	13.2 Types of melanoma
	13.3 Risk factors for melanoma
		13.3.1 Ultraviolet radiation
		13.3.2 Heritable factors
	13.4 Cutaneous melanoma development
	13.5 Cutaneous melanoma treatment
		13.5.1 Classic approach
		13.5.2 Immunotherapy
		13.5.3 Targeted therapy
	13.6 In vitro models
		13.6.1 3D in vitro melanoma models
			13.6.1.1 Spheroids
			13.6.1.2 Organotypic cutaneous melanoma models
	References
14 3D scaffold materials for skin cancer modeling
	14.1 Introduction
	14.2 Effective factors in cell culture; 2D and 3D models
		14.2.1 Ethical and economical parameters
		14.2.2 Biological parameters
			14.2.2.1 Angiogenesis capabilities
			14.2.2.2 Attachment capabilities to the extracellular matrix
		14.2.3 Physical parameters
			14.2.3.1 Cell density, proteins, and adhesion molecules
			14.2.3.2 Surface properties
		14.2.4 Tumor microenvironmental properties
		14.2.5 Hydrophobicity/hydrophilicity effects
	14.3 Skin cancers
	14.4 Modeling of skin cancer
		14.4.1 In vitro skin cancer modeling
			14.4.1.1 Spheroid formation
			14.4.1.2 Natural-based 3D scaffolds
			14.4.1.3 Peptide-derived hydrogels
			14.4.1.4 3D fiber scaffolding in vitro models
			14.4.1.5 Chemical additives in 3D culture
			14.4.1.6 Biomaterials based 3D models
			14.4.1.7 3D cell cultures using microfluidic devices
		14.4.2 In vivo models
		14.4.3 New insights in 3D models of skin cancer
			14.4.3.1 Microfluidic approach
			14.4.3.2 Personalized medicine
	14.5 Conclusion and future prospective
	Conflict of interest
	References
15 Microfluidic systems in cancer research
	15.1 Introduction
		15.1.1 Background
		15.1.2 Traditional systems for tumor diagnosis and modeling
		15.1.3 Microfluidics and cancer: main tools and applications
	15.2 Fundamentals of microfluidics: fluid mechanics in miniaturized devices
		15.2.1 Laminar flow
		15.2.2 Diffusion
		15.2.3 Surface tension
		15.2.4 Capillary forces
		15.2.5 Flow rate and resistance
	15.3 Fabrication principles of microfluidic devices
		15.3.1 Molding
			15.3.1.1 Replica molding
			15.3.1.2 Hot embossing
			15.3.1.3 Microthermoforming
			15.3.1.4 Microinjection molding
		15.3.2 Sacrificial templating
		15.3.3 3D (bio)printing
	15.4 Mimicking the tumor microenvironment using microfluidics
		15.4.1 The tumor microenvironment: an overview
		15.4.2 Microfluidics for reproducing biochemical cues during tumor invasion
			15.4.2.1 Biochemical gradients
			15.4.2.2 Oxygen gradients and hypoxia
			15.4.2.3 Microdroplet generation
		15.4.3 Microfluidics for reproducing mechanical cues in tumor invasion
			15.4.3.1 Physical constrictions
			15.4.3.2 Anisotropic features
			15.4.3.3 Mechanical deformation
			15.4.3.4 Modulating matrix stiffness
			15.4.3.5 Interstitial fluid pressure and flow
	15.5 Microfluidic models of cancer
		15.5.1 Organ-on-a-chip technology
		15.5.2 Organ-on-a-chip models of cancer metastasis: cancer- or tumor-on-a-chip
			15.5.2.1 Tumor growth and invasion models
			15.5.2.2 Angiogenesis models
			15.5.2.3 Lymphatic system and lymphangiogenesis models
			15.5.2.4 Intravasation models
			15.5.2.5 Extravasation models
			15.5.2.6 Multiorgan and organ specificity models
		15.5.3 Liquid biopsy-on-a-chip: isolation of CTCs
		15.5.4 Microfluidics for cancer biomarkers detection
	15.6 Future perspectives
		15.6.1 Microfluidic cancer models for clinical applications
		15.6.2 Microfluidic cancer models for industrial applications
	15.7 Conclusions
	Conflicts of interest
	References
16 Perfusion-based 3D tumor-on-chip devices for anticancer drug testing
	Abbreviations
	16.1 Introduction
	16.2 Disadvantages of 2D in vitro, 3D in vitro, and animal models
	16.3 Microfluidic devices for tumor modeling
	16.4 Tumor components and their inclusion in tumor-on-chip
		16.4.1 Cells: monoculture/co-culture
		16.4.2 ECM: chemical and mechanical cues
		16.4.3 Growth factors
		16.4.4 Shear stress
	16.5 Types of perfusion methods
	16.6 Benefits of perfusion and specific applications
		16.6.1 Vasculature
		16.6.2 Multiorgan systems
		16.6.3 Interstitial flow within 3D hydrogel systems
		16.6.4 Drug pharmacokinetics and pharmacodynamics
	16.7 Specific designs for enhancing perfusion
	16.8 Conclusion
	References
17 Engineering breast cancer models in vitro with 3D bioprinting
	17.1 Breast cancer microenvironment in vivo
		17.1.1 Types and stages of breast cancer
		17.1.2 Cancer cell behavior in vivo, microenvironment structure and mechanics
	17.2 Biomaterial-based breast cancer in vitro models
		17.2.1 Mammary morphogenesis in 3D
		17.2.2 Studies on cancer cell migration in 3D (metastasis models)
		17.2.3 3D spheroid and organoid invasion models
		17.2.4 3D models of heterotypic tumor–stromal interactions
	17.3 Biomaterials design for in vitro breast cancer models
		17.3.1 Natural, synthetic, and hybrid biomaterials
		17.3.2 Matrix stiffness, cross-linking, and network architecture
		17.3.3 Time-dependent and nonlinear mechanics
		17.3.4 Stimuli-responsive dynamic materials
		17.3.5 Biomaterial inks for 3D bioprinting
	17.4 3D bioprinting methods and their suitability for breast cancer in vitro engineering
		17.4.1 Microextrusion- and laser-induced forward transfer used in breast cancer research
		17.4.2 Volumetric and sacrificial bioprinting as future technologies in cancer research
		17.4.3 Bioprinting heterotypic cancer models for functional treatment modeling
	17.5 Discussion and outlook
		17.5.1 Evolution of breast cancer in vitro 3D models: from 2D culture to 3D bioprinting
		17.5.2 Advantages and challenges of 3D bioprinting in breast cancer research
		17.5.3 3D bioprinting in personalized breast cancer research and clinical treatment prognosis
	References
18 A predictive oncology framework—modeling tumor proliferation using a FEM platform
	Chapter points
	18.1 Introduction
		18.1.1 A vision of feasible virtualized oncological prognoses
		18.1.2 An engineering approach toward predictive oncology
		18.1.3 The cancer liver: a valuable case study
	18.2 A perspective framework of predictive oncology
		18.2.1 Step 1: Acquisition of diagnostic images
		18.2.2 Step 2: Real 2 virtual image
			18.2.2.1 By using some open-source software
			18.2.2.2 By using some proprietary software
		18.2.3 Step 3: Mathematical formulation
			18.2.3.1 Level 0
			18.2.3.2 Level 1
			18.2.3.3 Level 2
		18.2.4 Step 4: Solution and postprocessing
		18.2.5 Step 5: Replication of the model
	18.3 Detailed model formulation using level 1 modeling
		18.3.1 The biological conversion logistics-based mechanisms
		18.3.2 Governing equations
		18.3.3 Initial conditions, proliferation, and therapy onset
		18.3.4 Boundary conditions
	18.4 A sensitivity analysis of hallmark parameters: results
		18.4.1 Numerical treatment
		18.4.2 Model validation: application to a hepatocellular carcinoma—Case 0
		18.4.3 Model application to different tumor growth rates—Cases 1 and 2
		18.4.4 Model application to different therapies—Cases 3 to 7
		18.4.5 Model application to different values of tumor and drug diffusivities—Cases 8 to 11
	18.5 POEM as a tool to empower the clinical decisions
	18.6 Conclusions
	Glossary
	References
19 Tissue-engineered 3D cancer microenvironment for screening therapeutics
	19.1 Introduction
	19.2 Tumor microenvironment
		19.2.1 Cellular components
		19.2.2 Non-cellular components
	19.3 Current strategies for creating cell and matrix organization to mimic microenvironment
		19.3.1 Organoid derivation options (patient-derived organoid vs patient-derived xenograft)
		19.3.2 Transwell-based assays
		19.3.3 Organotypic model
		19.3.4 Microfluidic devices
		19.3.5 Micromolded 3D gels
		19.3.6 Multicellular spheroid
		19.3.7 Stacked paper models
		19.3.8 Cell sources used in tissue-engineered models
	19.4 Modeling important aspects of the tumor microenvironment
		19.4.1 In vitro models of tumor–fibroblast interactions
		19.4.2 In vitro models of tumor–immune interactions
		19.4.3 In vitro models of hypoxia and small molecular gradients
			19.4.3.1 Oxygen gradients
			19.4.3.2 Gradients of cytokines and other signaling factors
		19.4.4 In vitro models of tumor vasculature
	19.5 Future outlook
	References
20 Three-dimensional tumor model and their implication in drug screening for tackling chemoresistance
	Abbreviations
	20.1 Chemoresistance in cancer
	20.2 3D tumor culture: an advanced model preferred over 2D culture
	20.3 3D culture and chemoresistance
		20.3.1 3D culture acts as a good model to study chemoresistance
		20.3.2 Importance of tumor microenvironment interaction in the development of chemoresistance
		20.3.3 Tumor heterogeneity and chemoresistance
	20.4 Methods of generating 3D culture system
		20.4.1 Methods of generating 3D organoids
		20.4.2 Methods of generating 3D spheroids
			20.4.2.1 Hanging drop model
			20.4.2.2 Nonadherent surface model
			20.4.2.3 Suspension culture model
			20.4.2.4 Scaffold-based model
			20.4.2.5 Magnetic levitation model
	20.5 3D culture and biomaterials
		20.5.1 Cell-derived or natural biomaterials
			20.5.1.1 Collagen
			20.5.1.2 Laminin-rich extracellular matrix
			20.5.1.3 Alginate matrix
			20.5.1.4 Chitosan matrix
			20.5.1.5 Silk
			20.5.1.6 Matrigel
			20.5.1.7 Hyaluronan-based hydrogel
		20.5.2 Synthetic biomaterials
			20.5.2.1 Polyethylene glycol-based hydrogel
			20.5.2.2 Polyethylene glycol-dextran aqueous two-phase system
			20.5.2.3 Polycaprolactone
			20.5.2.4 Poly(lactic-co-glycolic) acid
			20.5.2.5 Thermoresponsive hydrogels
	20.6 Drug screening in 3D culture
		20.6.1 Importance of organoids for developing personalized medicines
		20.6.2 Organoids in cancer medicine
		20.6.3 Patient-derived organoids used for cancer drug screening
	20.7 Future aspects of the 3D tumor organoid model: biobanks for tumor tissues
	20.8 Limitations of 3D culture technology
	20.9 Conclusion
	References
21 Co-culture and 3D tumor models for drug/gene therapy testing
	21.1 Introduction
	21.2 Lung cancer
		21.2.1 Scaffold chemo/drug treatment
		21.2.2 Scaffold gene therapy
		21.2.3 Scaffold co-culture chemo/drug treatment
		21.2.4 Hydrogel chemo/drug treatment
		21.2.5 Hydrogel co-culture
	21.3 Breast cancer
		21.3.1 Scaffolds chemo/drug therapy
		21.3.2 Scaffolds gene therapy
		21.3.3 Scaffolds co-culture chemotherapy
		21.3.4 Hydrogels and chemo/drug therapy
		21.3.5 Hydrogels and gene therapy
	21.4 Prostate cancer
		21.4.1 Scaffold chemo/drug treatment
		21.4.2 Scaffold gene therapy
		21.4.3 Scaffold co-culture gene therapy
		21.4.4 Hydrogel chemo/drug treatment
		21.4.5 Hydrogel gene therapy
		21.4.6 Hydrogel co-culture chemo
	21.5 Future outlook
	References
22 Newly emerged engineering of in vitro 3D tumor models using biomaterials for chemotherapy
	22.1 Introduction
	22.2 Constitution of artificially engineered tumor models
		22.2.1 Cells
		22.2.2 Materials
	22.3 Newly emerged engineering of in vitro 3D tumors for chemotherapy
		22.3.1 Microfluidic tumor models
			22.3.1.1 Fluid network for mimicking vasculature
			22.3.1.2 Easy and efficient set-up for massive drug screening
			22.3.1.3 “Organ-on-a-chip” for investigating organ-specific drug response
			22.3.1.4 Integration of multimicrochips for systemic drug toxicity evaluation
		22.3.2 Bioprinted 3D tumor models
	22.4 Summary
	References
23 Marine-derived biomaterials for cancer treatment
	23.1 Introduction
	23.2 Marine biopolymers as bioactive agents
		23.2.1 Fucoidan
		23.2.2 Chitosan
	23.3 Drug-delivery systems
		23.3.1 Fucoidan-based systems
		23.3.2 Chitosan-based systems
		23.3.3 Carrageenan-based systems
		23.3.4 Alginate-based systems
	23.4 Three-dimensional in vitro models of cancer
		23.4.1 Chitosan-based cancer models
		23.4.2 Alginate-based cancer models
		23.4.3 Chitosan-alginate-based cancer models
	23.5 Conclusions
	References
24 Mesoporous silica nanoparticles for cancer theranostic applications
	24.1 Introduction
	24.2 MSNs chemistry
	24.3 Biological effects of MSNs
	24.4 3D modeling of MSN for cancer therapy
		24.4.1 Hydrogels
		24.4.2 Electrospun nanofiber scaffolds
		24.4.3 3D-printed scaffolds
	24.5 Medical applications of MSNs
		24.5.1 Stimuli-responsive drug release
			24.5.1.1 pH-responsive
			24.5.1.2 Redox-responsive
			24.5.1.3 Light-responsive
			24.5.1.4 Magnetic field-responsive
		24.5.2 Targeted drug delivery
			24.5.2.1 Cell-membrane targeting
			24.5.2.2 Cell-cytoplasm targeting
		24.5.3 Other therapeutic strategies
			24.5.3.1 Phototherapy
			24.5.3.2 Ultrasound therapy
			24.5.3.3 Chemodynamic therapy
	24.6 Diagnostic application of MSNs
		24.6.1 Magnetic resonance imaging
		24.6.2 Fluorescent/luminescent imaging
		24.6.3 Positron emission tomography imaging
	24.7 Theranostics application of MSNs
	24.8 Conclusions and outlook
	References
25 Causes of cancer: physical, chemical, biological carcinogens, and viruses
	Abbreviations
	25.1 Introduction
		25.1.1 How normal cells become cancerous?
		25.1.2 Stages of carcinogenesis
			25.1.2.1 Initiation
			25.1.2.2 Promotion
			25.1.2.3 Progression
		25.1.3 Carcinogens
	25.2 Physical carcinogens
		25.2.1 Mechanism of action of physical carcinogens
		25.2.2 Electromagnetic radiation
		25.2.3 Ionizing radiation
		25.2.4 Hard and soft materials
			25.2.4.1 Asbestos
			25.2.4.2 Erionite
			25.2.4.3 Nonfibrous particulate materials
			25.2.4.4 Air pollutants
			25.2.4.5 Gel materials
		25.2.5 Trauma
	25.3 Chemical carcinogens
		25.3.1 Mechanisms of chemical carcinogenesis
		25.3.2 Types of chemical carcinogens
			25.3.2.1 Aromatic amines
			25.3.2.2 N-Nitroso compounds
			25.3.2.3 Dyes
			25.3.2.4 Alkylating agents
			25.3.2.5 Natural carcinogens
			25.3.2.6 Inorganic carcinogenic agents
			25.3.2.7 Solvents and other compounds
	25.4 Biological carcinogens and viruses
		25.4.1 Mechanisms of biological carcinogenesis
		25.4.2 Viral carcinogens
			25.4.2.1 Epstein–Barr virus
			25.4.2.2 Hepatitis B virus
			25.4.2.3 Hepatitis C virus
			25.4.2.4 Kaposi sarcoma herpesvirus
			25.4.2.5 Human immunodeficiency virus-1
			25.4.2.6 Human papillomavirus
			25.4.2.7 Human T-cell lymphotropic virus type-1
		25.4.3 Bacterial carcinogens
			25.4.3.1 Helicobacter pylori
		25.4.4 Protozoal carcinogens
			25.4.4.1 Opisthorchis viverrini and Clonorchis sinensis
			25.4.4.2 Schistosoma haematobium
		25.4.5 Other biological carcinogens
	25.5 Conclusion
	References
26 Biodetection and sensing for cancer diagnostics
	26.1 Introduction
	26.2 Biomarkers for cancer detection
		26.2.1 Protein biomarkers
		26.2.2 Circulating tumor cells
		26.2.3 MicroRNAs
		26.2.4 Circulating tumor DNA
		26.2.5 Biomarker panels
	26.3 Cancer biosensors
		26.3.1 Electrochemical biosensors
		26.3.2 Optical biosensors
		26.3.3 Piezoelectric biosensors
	26.4 Commercialization and clinical trials of cancer biosensors
	26.5 Conclusions
	References
27 Understanding the impact of controlled oxygen delivery to 3D cancer cell culture
	27.1 Introduction
	27.2 What is known about physiological oxygen levels?
		27.2.1 Normoxia versus physoxia
		27.2.2 Hypoxia (physiological vs pathological)
		27.2.3 Tumor hypoxia
	27.3 Importance of oxygen levels in various stages of cancer progression
		27.3.1 Hypoxia
		27.3.2 Angiogenesis
		27.3.3 Metastasis
	27.4 Techniques for measuring oxygenation
		27.4.1 Oxygen-sensing electrodes
		27.4.2 Biologic and synthetic absorptiometric probes
		27.4.3 Fluorescent and phosphorescent luminescent probes
		27.4.4 Spectroscopic imaging: magnetic, paramagnetic, and electron spin resonance
	27.5 Traditional/current strategies for controlling oxygen concentration in vitro
		27.5.1 Hypoxia chambers and two-dimensional models
		27.5.2 Three-dimensional models: spheroids
		27.5.3 Other strategies for controlling oxygen delivery in 3D: lab-on-chip systems, bioreactors
	27.6 Characterizing the effects of oxygenation on cells and tissues
		27.6.1 RNA-Seq
		27.6.2 qPCR of downstream targets
		27.6.3 Pimonidazole staining
		27.6.4 Real-time imaging of growth
		27.6.5 Metabolic characterization and imaging
		27.6.6 In vivo metabolic imaging
		27.6.7 In vitro metabolic imaging
	27.7 Conclusions and future prospects
	References
28 Tissue engineering strategies for the treatment of skeletal maxillofacial defects resulting from neoplasms resections
	28.1 Background
		28.1.1 Oral and maxillofacial neoplasms
			28.1.1.1 Myxoma
			28.1.1.2 Ameloblastoma
			28.1.1.3 Odontoma
			28.1.1.4 Odontogenic keratocyst
			28.1.1.5 Central giant cells granuloma
		28.1.2 Currently used therapies
	28.2 Tissue engineering for reconstruction of ablated skeletal maxillofacial tissues
		28.2.1 Scaffolds
			28.2.1.1 Inorganic materials
			28.2.1.2 Synthetic polymeric materials
			28.2.1.3 Natural polymers
		28.2.2 Cells
			28.2.2.1 Mesenchymal stem cells
				28.2.2.1.1 Bone marrow derived stem cells
				28.2.2.1.2 Periosteal-derived progenitor cells
				28.2.2.1.3 Adipose tissue-derived stem cells
				28.2.2.1.4 Dental pulp stem cells
				28.2.2.1.5 Co-cultures
		28.2.3 Biochemical cues
		28.2.4 Bioreactors
		28.2.5 Prophylactic tissue engineering constructs
	28.3 Future perspectives and unmet challenges
	References
Index
Front Cover
Biomaterials for 3D Tumor Modeling
Copyright Page
Contents
List of Contributors
Preface
I. Engineering biomaterials for 3D cancer modelling
	1 Trends in biomaterials for three-dimensional cancer modeling
		Abbreviations
		1.1 A historical introduction
			1.1.1 In vitro and in vivo models: an overview
			1.1.2 A paradigm shift
			1.1.3 Three-dimensional biomaterials for cancer modeling
			1.1.4 From the lab to the clinic
		1.2 The three-dimensional tumor microenvironment
			1.2.1 The tumor and its three-dimensional environment: a synergistic interaction
			1.2.2 Biomaterials as a model of the tumor niche
				1.2.2.1 Scaffold-based biomaterials
				1.2.2.2 Matrix-based
				1.2.2.3 Microcarrier-based
				1.2.2.4 Scaffold-free: tumor spheroids
				1.2.2.5 Microstructured surfaces
		1.3 Engineering the native tumor microenvironment using custom-designed three-dimensional biomaterials
			1.3.1 Tissue engineering approaches
				1.3.1.1 Freeze-drying
				1.3.1.2 Photopolymerization
				1.3.1.3 Three-dimensional bioprinting
			1.3.2 Nanotechnology approaches
				1.3.2.1 Molding
				1.3.2.2 Printing
					1.3.2.2.1 (Two-dimensional) microcontact printing
					1.3.2.2.2 Three-dimensional printing
					1.3.2.2.3 Four-dimensional printing
		1.4 Advanced models of the three-dimensional tumor microenvironment
			1.4.1 Microfluidics-based models
				1.4.1.1 Microfluidic-based models of tumors: tumor-on-a-chip
				1.4.1.2 Drug discovery and screening on-chip
				1.4.1.3 Reproducing dynamic events on-chip
				1.4.1.4 Personalized tumor-on-a-chip models
				1.4.1.5 Manufacturing methods of a tumor-on-a-chip
			1.4.2 Three-dimensional bioprinted models
		1.5 Applications of three-dimensional tumor models in cancer therapeutics
			1.5.1 Drug discovery, development, and screening
			1.5.2 Transport and delivery of drugs
		1.6 Limitations of biomaterials-based three-dimensional tumor models
		1.7 Future of three-dimensional biomaterials for cancer research
		1.8 Final remarks and conclusions
		References
	2 Bioinspired biomaterials to develop cell-rich spherical microtissues for 3D in vitro tumor modeling
		2.1 Introduction
		2.2 Human Tumor microenvironment—key hallmarks to mimic in vitro
		2.3 3D In vitro tumor models—bridging the gap from 2D flat cultures to in vivo
		2.4 Classes of 3D multicellular tumor models
			2.4.1 Scaffold-free cell-rich 3D multicellular tumor spheroids
			2.4.2 Scaffold-based 3D multicellular tumor models
				2.4.2.1 Biomaterials for establishing physiomimetic 3D tumor microenvironments
					2.4.2.1.1 Natural and nature-derived biomaterials for 3D tumor modeling
						Protein-based biomaterials
						Polysaccharide-based biomaterials
					2.4.2.1.2 Synthetic biomaterials for 3D tumor modeling
					2.4.2.1.3 Hybrid biomaterials for 3D tumor modeling
			2.4.3 Generation of spherically structured cell-rich 3D tumor models
				2.4.3.1 Microparticles for spherically structured 3D tumor models assembly
				2.4.3.2 Microgels for spherically structured 3D tumor models assembly
				2.4.3.3 Microcapsules for spherically structured 3D tumor models assembly
		2.5 Conclusions
		References
	3 Biofabrication of 3D tumor models in cancer research
		3.1 Current challenges in oncology
		3.2 The tumor microenvironment
		3.3 Development of the cancer therapeutics field
		3.4 3D tumor models in cancer research
			3.4.1 Nonscaffold-based 3D cell culture methods
			3.4.2 Scaffold-based 3D cell culture methods
		3.5 Evaluation of anticancer therapeutics in 3D tumor models
			3.5.1 Drug screening/drug resistance
			3.5.2 Anticancer nanomedicines
		3.6 Implementation of 3D tumor models in a clinical setting
		3.7 Final remarks
		References
	4 Biomatrices that mimic the cancer extracellular environment
		4.1 Introduction
		4.2 The three-dimensional in vitro models
			4.2.1 Natural-based models
				4.2.1.1 Protein-based systems
				4.2.1.2 Polysaccharide-based systems
				4.2.1.3 Other natural occurring materials
			4.2.2 Synthetic and other biobased models
			4.2.3 Mimicking the tumor microenvironment mechanical features
		4.3 Conclusions and future remarks
		References
	5 3D neuroblastoma in vitro models using engineered cell-derived matrices
		5.1 Introduction
		5.2 Neuroblastoma
			5.2.1 Evidence of cell–extracellular matrix interaction in neuroblastoma
		5.3 Cell-derived matrices in tumor modeling
		5.4 Engineering cell-derived matrix deposition
			5.4.1 Cell source
			5.4.2 Culture medium composition
			5.4.3 Culture substrates and conditions
			5.4.4 Decellularization agents
			5.4.5 Chemical and physical modifications
		5.5 Cell-derived matrices and cell morphodynamic characterization
		5.6 Cell-derived matrix capture relevant processes involved in neuroblastoma malignancy
		5.7 Conclusions
		References
	6 3D culture systems as models for solid tumors and cancer metabolism
		Abbreviations
		6.1 Introduction
		6.2 Solid tumors: tumor microenvironment and tumorigenesis
		6.3 Cancer metabolism: influence in tumor microenvironment
		6.4 Solid tumors in vitro models
			6.4.1 2D cell culture systems in cancer research
			6.4.2 3D cell culture systems
		6.5 3D cell culture systems in cancer research
		6.6 3D cell culture systems for study cancer metabolism
		6.7 Conclusions
		Conflict of interest
		References
	7 Biomaterials as ECM-like matrices for 3D in vitro tumor models
		Abbreviations
		7.1 Introduction
		7.2 Biomaterials as ECM-like matrices for cancer 3D in vitro models
			7.2.1 Synthetic
			7.2.2 Natural-based
				7.2.2.1 Proteins
				7.2.2.2 Polysaccharides
			7.2.3 Decellularized matrices
		7.3 Conclusion and future trends
		References
	8 Three-dimensional in vitro models of angiogenesis
		8.1 Vessels formation and tumor angiogenesis
		8.2 Vascular extracellular matrix
			8.2.1 Vascular basement membrane composition
			8.2.2 Interstitial matrix
		8.3 Endothelial cells-based 3D angiogenesis models
			8.3.1 Vascular differentiation in embryoid body
			8.3.2 Tube formation on basement membrane matrix gel
			8.3.3 Sprouting from endothelial cell spheroids in collagen gel
		8.4 Vascular explant-based 3D angiogenesis models
			8.4.1 Rat aortic ring sprouting assay
			8.4.2 Mouse aortic ring sprouting assay
			8.4.3 Human arterial ring angiogenesis assay
		8.5 Microvessels on a chip
			8.5.1 Microfluidics-based devices
			8.5.2 3D bioprinting and sacrificial templating
			8.5.3 Organ-on-a-chip
		8.6 Future perspectives
		References
	9 Metastasis in three-dimensional biomaterials
		9.1 Why biomaterial is needed in cancer modeling?
		9.2 Biomaterials employed in tumor ECM modeling
			9.2.1 Naturally derived biomaterials
				9.2.1.1 Collagen
				9.2.1.2 Gelatin
				9.2.1.3 Laminin-rich extracellular matrix
				9.2.1.4 Alginate
				9.2.1.5 Chitosan
				9.2.1.6 Hyaluronic acid
				9.2.1.7 Silk
			9.2.2 Synthetic biomaterials
				9.2.2.1 Polyethylene glycol and its derivatives
				9.2.2.2 Poly(lactic-co-glycolic) acid
				9.2.2.3 Polycaprolactone
				9.2.2.4 Polyacrylamide
				9.2.2.5 Polydimethylsiloxane
				9.2.2.6 Thermoresponsive polymers
		9.3 Properties of cell surrounding matrix/niche contribute to tumor cell migration
			9.3.1 Pore size
			9.3.2 Topography or contact guidance
			9.3.3 Stiffness
			9.3.4 Matrix rheology
			9.3.5 Ligand accessibility
		9.4 Biomaterial-based stepwise modeling of cancer metastasis in vitro
			9.4.1 Tumor initiation and progression
			9.4.2 Tumor angiogenesis
			9.4.3 Modeling of tumor invasion or migration
				9.4.3.1 Spheroids
				9.4.3.2 Transwell-based models
				9.4.3.3 Microfluidic models
			9.4.4 Intravasation models
				9.4.4.1 Prevascularized spheroids
				9.4.4.2 Microfluidic devices
				9.4.4.3 Magnetic force-based cell patterning
			9.4.5 Extravasation and colonization
		9.5 Biomaterial-based in vitro models of cancer dormancy and reactivation
		9.6 Concluding remarks
		References
	10 3D cancer spheroids and microtissues
		Abbreviations
		10.1 Introduction
		10.2 Biomaterials advances tumor cell culture to the third dimension
			10.2.1 Biodegradable microcarriers to develop in vitro 3D heterotypic tumor models
			10.2.2 Exogenous extracellular matrix as support for the growth of tumor spheroids
		10.3 Recapitulating the tumor–stroma crosstalk in spheroid and microtissue models
			10.3.1 The role of cancer-associated fibroblasts in promoting cancer progression
			10.3.2 Co-cultured spheroid models
		10.4 Vascularized microtumor models
			10.4.1 Endothelial cells promote invasion and migration of cancer cells
			10.4.2 Multicellular spheroids to recapitulate the tumor angiogenesis
			10.4.3 Tumor microtissues as 3D bioengineered architecture to study cancer vascularization
		10.5 The contribution of immune system cells in microtumors
			10.5.1 Macrophage: the double side of the same player
			10.5.2 Spheroids incorporating the immune system cells
			10.5.3 3D complex architecture to copycat the immune-competence in tumors
		10.6 Spheroids as screening platform for drug testing
			10.6.1 The importance of moving 3D culture to high-throughput screening approaches
			10.6.2 The development of novel methodology for solving high-content imaging problem in preclinical study models
		10.7 Conclusion and future trends
		References
	11 Biomaterial-based in vitro models for pancreatic cancer
		11.1 Introduction
		11.2 In vitro 3D models for pancreatic cancer
			11.2.1 Spheroids and organoids
			11.2.2 Hydrogels
			11.2.3 Polymer scaffolds
		11.3 Using 3D models for disease understanding
			11.3.1 Biomimetic role of scaffold features
			11.3.2 Tumor progression and metastasis
		11.4 Using 3D models for therapeutic screening
		11.5 Conclusions and future trends
		References
	12 In vitro three-dimensional modeling for prostate cancer
		12.1 Introduction
			12.1.1 Preclinical models for addressing prostate cancer
				12.1.1.1 In vivo models
				12.1.1.2 In vitro models
			12.1.2 Three-dimensional in vitro models of prostate cancer
				12.1.2.1 Spherical cancer models
				12.1.2.2 Bioengineered models
				12.1.2.3 Microfluidic models
				12.1.2.4 Bioreactors
				12.1.2.5 Organ explants
		12.2 Modeling primary tumors
			12.2.1 Modeling localized prostate cancer
				12.2.1.1 Monocellular models of primary tumors
				12.2.1.2 Multicellular models of primary tumors incorporating stromal elements
			12.2.2 Three-dimensional models to address androgen-mediated biology
			12.2.3 Three-dimensional models for prostate cancer stem cells
			12.2.4 Three-dimensional models to address therapeutic response
		12.3 Modeling early stages of prostate cancer progression
			12.3.1 Modeling tumor invasion
			12.3.2 Modeling angiogenesis and the contribution of vessels to tumor progression
			12.3.3 Isolation of circulating tumor cells
			12.3.4 Extravasation
		12.4 Modeling advanced stages of prostate cancer progression
			12.4.1 Disseminated tumor cells
			12.4.2 Three-dimensional models to address the biology of prostate cancer bone metastasis
			12.4.3 Three-dimensional models to address the therapeutic response of metastatic prostate cancer to bone
			12.4.4 Three-dimensional models of metastatic prostate cancer to the liver
		12.5 Conclusion
		References
	13 3D in vitro cutaneous melanoma models
		Abbreviations
		13.1 Introduction
		13.2 Types of melanoma
		13.3 Risk factors for melanoma
			13.3.1 Ultraviolet radiation
			13.3.2 Heritable factors
		13.4 Cutaneous melanoma development
		13.5 Cutaneous melanoma treatment
			13.5.1 Classic approach
			13.5.2 Immunotherapy
			13.5.3 Targeted therapy
		13.6 In vitro models
			13.6.1 3D in vitro melanoma models
				13.6.1.1 Spheroids
				13.6.1.2 Organotypic cutaneous melanoma models
		References
	14 3D scaffold materials for skin cancer modeling
		14.1 Introduction
		14.2 Effective factors in cell culture; 2D and 3D models
			14.2.1 Ethical and economical parameters
			14.2.2 Biological parameters
				14.2.2.1 Angiogenesis capabilities
				14.2.2.2 Attachment capabilities to the extracellular matrix
			14.2.3 Physical parameters
				14.2.3.1 Cell density, proteins, and adhesion molecules
				14.2.3.2 Surface properties
			14.2.4 Tumor microenvironmental properties
			14.2.5 Hydrophobicity/hydrophilicity effects
		14.3 Skin cancers
		14.4 Modeling of skin cancer
			14.4.1 In vitro skin cancer modeling
				14.4.1.1 Spheroid formation
				14.4.1.2 Natural-based 3D scaffolds
				14.4.1.3 Peptide-derived hydrogels
				14.4.1.4 3D fiber scaffolding in vitro models
				14.4.1.5 Chemical additives in 3D culture
				14.4.1.6 Biomaterials based 3D models
				14.4.1.7 3D cell cultures using microfluidic devices
			14.4.2 In vivo models
			14.4.3 New insights in 3D models of skin cancer
				14.4.3.1 Microfluidic approach
				14.4.3.2 Personalized medicine
		14.5 Conclusion and future prospective
		Conflict of interest
		References
II. Advanced models for cancer research
	15 Microfluidic systems in cancer research
		15.1 Introduction
			15.1.1 Background
			15.1.2 Traditional systems for tumor diagnosis and modeling
			15.1.3 Microfluidics and cancer: main tools and applications
		15.2 Fundamentals of microfluidics: fluid mechanics in miniaturized devices
			15.2.1 Laminar flow
			15.2.2 Diffusion
			15.2.3 Surface tension
			15.2.4 Capillary forces
			15.2.5 Flow rate and resistance
		15.3 Fabrication principles of microfluidic devices
			15.3.1 Molding
				15.3.1.1 Replica molding
				15.3.1.2 Hot embossing
				15.3.1.3 Microthermoforming
				15.3.1.4 Microinjection molding
			15.3.2 Sacrificial templating
			15.3.3 3D (bio)printing
		15.4 Mimicking the tumor microenvironment using microfluidics
			15.4.1 The tumor microenvironment: an overview
			15.4.2 Microfluidics for reproducing biochemical cues during tumor invasion
				15.4.2.1 Biochemical gradients
				15.4.2.2 Oxygen gradients and hypoxia
				15.4.2.3 Microdroplet generation
			15.4.3 Microfluidics for reproducing mechanical cues in tumor invasion
				15.4.3.1 Physical constrictions
				15.4.3.2 Anisotropic features
				15.4.3.3 Mechanical deformation
				15.4.3.4 Modulating matrix stiffness
				15.4.3.5 Interstitial fluid pressure and flow
		15.5 Microfluidic models of cancer
			15.5.1 Organ-on-a-chip technology
			15.5.2 Organ-on-a-chip models of cancer metastasis: cancer- or tumor-on-a-chip
				15.5.2.1 Tumor growth and invasion models
				15.5.2.2 Angiogenesis models
				15.5.2.3 Lymphatic system and lymphangiogenesis models
				15.5.2.4 Intravasation models
				15.5.2.5 Extravasation models
				15.5.2.6 Multiorgan and organ specificity models
			15.5.3 Liquid biopsy-on-a-chip: isolation of CTCs
			15.5.4 Microfluidics for cancer biomarkers detection
		15.6 Future perspectives
			15.6.1 Microfluidic cancer models for clinical applications
			15.6.2 Microfluidic cancer models for industrial applications
		15.7 Conclusions
		Conflicts of interest
		References
	16 Perfusion-based 3D tumor-on-chip devices for anticancer drug testing
		Abbreviations
		16.1 Introduction
		16.2 Disadvantages of 2D in vitro, 3D in vitro, and animal models
		16.3 Microfluidic devices for tumor modeling
		16.4 Tumor components and their inclusion in tumor-on-chip
			16.4.1 Cells: monoculture/co-culture
			16.4.2 ECM: chemical and mechanical cues
			16.4.3 Growth factors
			16.4.4 Shear stress
		16.5 Types of perfusion methods
		16.6 Benefits of perfusion and specific applications
			16.6.1 Vasculature
			16.6.2 Multiorgan systems
			16.6.3 Interstitial flow within 3D hydrogel systems
			16.6.4 Drug pharmacokinetics and pharmacodynamics
		16.7 Specific designs for enhancing perfusion
		16.8 Conclusion
		References
	17 Engineering breast cancer models in vitro with 3D bioprinting
		17.1 Breast cancer microenvironment in vivo
			17.1.1 Types and stages of breast cancer
			17.1.2 Cancer cell behavior in vivo, microenvironment structure and mechanics
		17.2 Biomaterial-based breast cancer in vitro models
			17.2.1 Mammary morphogenesis in 3D
			17.2.2 Studies on cancer cell migration in 3D (metastasis models)
			17.2.3 3D spheroid and organoid invasion models
			17.2.4 3D models of heterotypic tumor–stromal interactions
		17.3 Biomaterials design for in vitro breast cancer models
			17.3.1 Natural, synthetic, and hybrid biomaterials
			17.3.2 Matrix stiffness, cross-linking, and network architecture
			17.3.3 Time-dependent and nonlinear mechanics
			17.3.4 Stimuli-responsive dynamic materials
			17.3.5 Biomaterial inks for 3D bioprinting
		17.4 3D bioprinting methods and their suitability for breast cancer in vitro engineering
			17.4.1 Microextrusion- and laser-induced forward transfer used in breast cancer research
			17.4.2 Volumetric and sacrificial bioprinting as future technologies in cancer research
			17.4.3 Bioprinting heterotypic cancer models for functional treatment modeling
		17.5 Discussion and outlook
			17.5.1 Evolution of breast cancer in vitro 3D models: from 2D culture to 3D bioprinting
			17.5.2 Advantages and challenges of 3D bioprinting in breast cancer research
			17.5.3 3D bioprinting in personalized breast cancer research and clinical treatment prognosis
		References
	18 A predictive oncology framework—modeling tumor proliferation using a FEM platform
		Chapter points
		18.1 Introduction
			18.1.1 A vision of feasible virtualized oncological prognoses
			18.1.2 An engineering approach toward predictive oncology
			18.1.3 The cancer liver: a valuable case study
		18.2 A perspective framework of predictive oncology
			18.2.1 Step 1: Acquisition of diagnostic images
			18.2.2 Step 2: Real 2 virtual image
				18.2.2.1 By using some open-source software
				18.2.2.2 By using some proprietary software
			18.2.3 Step 3: Mathematical formulation
				18.2.3.1 Level 0
				18.2.3.2 Level 1
				18.2.3.3 Level 2
			18.2.4 Step 4: Solution and postprocessing
			18.2.5 Step 5: Replication of the model
		18.3 Detailed model formulation using level 1 modeling
			18.3.1 The biological conversion logistics-based mechanisms
			18.3.2 Governing equations
			18.3.3 Initial conditions, proliferation, and therapy onset
			18.3.4 Boundary conditions
		18.4 A sensitivity analysis of hallmark parameters: results
			18.4.1 Numerical treatment
			18.4.2 Model validation: application to a hepatocellular carcinoma—Case 0
			18.4.3 Model application to different tumor growth rates—Cases 1 and 2
			18.4.4 Model application to different therapies—Cases 3 to 7
			18.4.5 Model application to different values of tumor and drug diffusivities—Cases 8 to 11
		18.5 POEM as a tool to empower the clinical decisions
		18.6 Conclusions
		Glossary
		References
III. Tumor models for drug discovery and therapeutics
	19 Tissue-engineered 3D cancer microenvironment for screening therapeutics
		19.1 Introduction
		19.2 Tumor microenvironment
			19.2.1 Cellular components
			19.2.2 Non-cellular components
		19.3 Current strategies for creating cell and matrix organization to mimic microenvironment
			19.3.1 Organoid derivation options (patient-derived organoid vs patient-derived xenograft)
			19.3.2 Transwell-based assays
			19.3.3 Organotypic model
			19.3.4 Microfluidic devices
			19.3.5 Micromolded 3D gels
			19.3.6 Multicellular spheroid
			19.3.7 Stacked paper models
			19.3.8 Cell sources used in tissue-engineered models
		19.4 Modeling important aspects of the tumor microenvironment
			19.4.1 In vitro models of tumor–fibroblast interactions
			19.4.2 In vitro models of tumor–immune interactions
			19.4.3 In vitro models of hypoxia and small molecular gradients
				19.4.3.1 Oxygen gradients
				19.4.3.2 Gradients of cytokines and other signaling factors
			19.4.4 In vitro models of tumor vasculature
		19.5 Future outlook
		References
	20 Three-dimensional tumor model and their implication in drug screening for tackling chemoresistance
		Abbreviations
		20.1 Chemoresistance in cancer
		20.2 3D tumor culture: an advanced model preferred over 2D culture
		20.3 3D culture and chemoresistance
			20.3.1 3D culture acts as a good model to study chemoresistance
			20.3.2 Importance of tumor microenvironment interaction in the development of chemoresistance
			20.3.3 Tumor heterogeneity and chemoresistance
		20.4 Methods of generating 3D culture system
			20.4.1 Methods of generating 3D organoids
			20.4.2 Methods of generating 3D spheroids
				20.4.2.1 Hanging drop model
				20.4.2.2 Nonadherent surface model
				20.4.2.3 Suspension culture model
				20.4.2.4 Scaffold-based model
				20.4.2.5 Magnetic levitation model
		20.5 3D culture and biomaterials
			20.5.1 Cell-derived or natural biomaterials
				20.5.1.1 Collagen
				20.5.1.2 Laminin-rich extracellular matrix
				20.5.1.3 Alginate matrix
				20.5.1.4 Chitosan matrix
				20.5.1.5 Silk
				20.5.1.6 Matrigel
				20.5.1.7 Hyaluronan-based hydrogel
			20.5.2 Synthetic biomaterials
				20.5.2.1 Polyethylene glycol-based hydrogel
				20.5.2.2 Polyethylene glycol-dextran aqueous two-phase system
				20.5.2.3 Polycaprolactone
				20.5.2.4 Poly(lactic-co-glycolic) acid
				20.5.2.5 Thermoresponsive hydrogels
		20.6 Drug screening in 3D culture
			20.6.1 Importance of organoids for developing personalized medicines
			20.6.2 Organoids in cancer medicine
			20.6.3 Patient-derived organoids used for cancer drug screening
		20.7 Future aspects of the 3D tumor organoid model: biobanks for tumor tissues
		20.8 Limitations of 3D culture technology
		20.9 Conclusion
		References
	21 Co-culture and 3D tumor models for drug/gene therapy testing
		21.1 Introduction
		21.2 Lung cancer
			21.2.1 Scaffold chemo/drug treatment
			21.2.2 Scaffold gene therapy
			21.2.3 Scaffold co-culture chemo/drug treatment
			21.2.4 Hydrogel chemo/drug treatment
			21.2.5 Hydrogel co-culture
		21.3 Breast cancer
			21.3.1 Scaffolds chemo/drug therapy
			21.3.2 Scaffolds gene therapy
			21.3.3 Scaffolds co-culture chemotherapy
			21.3.4 Hydrogels and chemo/drug therapy
			21.3.5 Hydrogels and gene therapy
		21.4 Prostate cancer
			21.4.1 Scaffold chemo/drug treatment
			21.4.2 Scaffold gene therapy
			21.4.3 Scaffold co-culture gene therapy
			21.4.4 Hydrogel chemo/drug treatment
			21.4.5 Hydrogel gene therapy
			21.4.6 Hydrogel co-culture chemo
		21.5 Future outlook
		References
	22 Newly emerged engineering of in vitro 3D tumor models using biomaterials for chemotherapy
		22.1 Introduction
		22.2 Constitution of artificially engineered tumor models
			22.2.1 Cells
			22.2.2 Materials
		22.3 Newly emerged engineering of in vitro 3D tumors for chemotherapy
			22.3.1 Microfluidic tumor models
				22.3.1.1 Fluid network for mimicking vasculature
				22.3.1.2 Easy and efficient set-up for massive drug screening
				22.3.1.3 “Organ-on-a-chip” for investigating organ-specific drug response
				22.3.1.4 Integration of multimicrochips for systemic drug toxicity evaluation
			22.3.2 Bioprinted 3D tumor models
		22.4 Summary
		References
	23 Marine-derived biomaterials for cancer treatment
		23.1 Introduction
		23.2 Marine biopolymers as bioactive agents
			23.2.1 Fucoidan
			23.2.2 Chitosan
		23.3 Drug-delivery systems
			23.3.1 Fucoidan-based systems
			23.3.2 Chitosan-based systems
			23.3.3 Carrageenan-based systems
			23.3.4 Alginate-based systems
		23.4 Three-dimensional in vitro models of cancer
			23.4.1 Chitosan-based cancer models
			23.4.2 Alginate-based cancer models
			23.4.3 Chitosan-alginate-based cancer models
		23.5 Conclusions
		References
	24 Mesoporous silica nanoparticles for cancer theranostic applications
		24.1 Introduction
		24.2 MSNs chemistry
		24.3 Biological effects of MSNs
		24.4 3D modeling of MSN for cancer therapy
			24.4.1 Hydrogels
			24.4.2 Electrospun nanofiber scaffolds
			24.4.3 3D-printed scaffolds
		24.5 Medical applications of MSNs
			24.5.1 Stimuli-responsive drug release
				24.5.1.1 pH-responsive
				24.5.1.2 Redox-responsive
				24.5.1.3 Light-responsive
				24.5.1.4 Magnetic field-responsive
			24.5.2 Targeted drug delivery
				24.5.2.1 Cell-membrane targeting
				24.5.2.2 Cell-cytoplasm targeting
			24.5.3 Other therapeutic strategies
				24.5.3.1 Phototherapy
				24.5.3.2 Ultrasound therapy
				24.5.3.3 Chemodynamic therapy
		24.6 Diagnostic application of MSNs
			24.6.1 Magnetic resonance imaging
			24.6.2 Fluorescent/luminescent imaging
			24.6.3 Positron emission tomography imaging
		24.7 Theranostics application of MSNs
		24.8 Conclusions and outlook
		References
IV. Point-of-care applications
	25 Causes of cancer: physical, chemical, biological carcinogens, and viruses
		Abbreviations
		25.1 Introduction
			25.1.1 How normal cells become cancerous?
			25.1.2 Stages of carcinogenesis
				25.1.2.1 Initiation
				25.1.2.2 Promotion
				25.1.2.3 Progression
			25.1.3 Carcinogens
		25.2 Physical carcinogens
			25.2.1 Mechanism of action of physical carcinogens
			25.2.2 Electromagnetic radiation
			25.2.3 Ionizing radiation
			25.2.4 Hard and soft materials
				25.2.4.1 Asbestos
				25.2.4.2 Erionite
				25.2.4.3 Nonfibrous particulate materials
				25.2.4.4 Air pollutants
				25.2.4.5 Gel materials
			25.2.5 Trauma
		25.3 Chemical carcinogens
			25.3.1 Mechanisms of chemical carcinogenesis
			25.3.2 Types of chemical carcinogens
				25.3.2.1 Aromatic amines
				25.3.2.2 N-Nitroso compounds
				25.3.2.3 Dyes
				25.3.2.4 Alkylating agents
				25.3.2.5 Natural carcinogens
				25.3.2.6 Inorganic carcinogenic agents
				25.3.2.7 Solvents and other compounds
		25.4 Biological carcinogens and viruses
			25.4.1 Mechanisms of biological carcinogenesis
			25.4.2 Viral carcinogens
				25.4.2.1 Epstein–Barr virus
				25.4.2.2 Hepatitis B virus
				25.4.2.3 Hepatitis C virus
				25.4.2.4 Kaposi sarcoma herpesvirus
				25.4.2.5 Human immunodeficiency virus-1
				25.4.2.6 Human papillomavirus
				25.4.2.7 Human T-cell lymphotropic virus type-1
			25.4.3 Bacterial carcinogens
				25.4.3.1 Helicobacter pylori
			25.4.4 Protozoal carcinogens
				25.4.4.1 Opisthorchis viverrini and Clonorchis sinensis
				25.4.4.2 Schistosoma haematobium
			25.4.5 Other biological carcinogens
		25.5 Conclusion
		References
	26 Biodetection and sensing for cancer diagnostics
		26.1 Introduction
		26.2 Biomarkers for cancer detection
			26.2.1 Protein biomarkers
			26.2.2 Circulating tumor cells
			26.2.3 MicroRNAs
			26.2.4 Circulating tumor DNA
			26.2.5 Biomarker panels
		26.3 Cancer biosensors
			26.3.1 Electrochemical biosensors
			26.3.2 Optical biosensors
			26.3.3 Piezoelectric biosensors
		26.4 Commercialization and clinical trials of cancer biosensors
		26.5 Conclusions
		References
	27 Understanding the impact of controlled oxygen delivery to 3D cancer cell culture
		27.1 Introduction
		27.2 What is known about physiological oxygen levels?
			27.2.1 Normoxia versus physoxia
			27.2.2 Hypoxia (physiological vs pathological)
			27.2.3 Tumor hypoxia
		27.3 Importance of oxygen levels in various stages of cancer progression
			27.3.1 Hypoxia
			27.3.2 Angiogenesis
			27.3.3 Metastasis
		27.4 Techniques for measuring oxygenation
			27.4.1 Oxygen-sensing electrodes
			27.4.2 Biologic and synthetic absorptiometric probes
			27.4.3 Fluorescent and phosphorescent luminescent probes
			27.4.4 Spectroscopic imaging: magnetic, paramagnetic, and electron spin resonance
		27.5 Traditional/current strategies for controlling oxygen concentration in vitro
			27.5.1 Hypoxia chambers and two-dimensional models
			27.5.2 Three-dimensional models: spheroids
			27.5.3 Other strategies for controlling oxygen delivery in 3D: lab-on-chip systems, bioreactors
		27.6 Characterizing the effects of oxygenation on cells and tissues
			27.6.1 RNA-Seq
			27.6.2 qPCR of downstream targets
			27.6.3 Pimonidazole staining
			27.6.4 Real-time imaging of growth
			27.6.5 Metabolic characterization and imaging
			27.6.6 In vivo metabolic imaging
			27.6.7 In vitro metabolic imaging
		27.7 Conclusions and future prospects
		References
	28 Tissue engineering strategies for the treatment of skeletal maxillofacial defects resulting from neoplasms resections
		28.1 Background
			28.1.1 Oral and maxillofacial neoplasms
				28.1.1.1 Myxoma
				28.1.1.2 Ameloblastoma
				28.1.1.3 Odontoma
				28.1.1.4 Odontogenic keratocyst
				28.1.1.5 Central giant cells granuloma
			28.1.2 Currently used therapies
		28.2 Tissue engineering for reconstruction of ablated skeletal maxillofacial tissues
			28.2.1 Scaffolds
				28.2.1.1 Inorganic materials
				28.2.1.2 Synthetic polymeric materials
				28.2.1.3 Natural polymers
			28.2.2 Cells
				28.2.2.1 Mesenchymal stem cells
					28.2.2.1.1 Bone marrow derived stem cells
					28.2.2.1.2 Periosteal-derived progenitor cells
					28.2.2.1.3 Adipose tissue-derived stem cells
					28.2.2.1.4 Dental pulp stem cells
					28.2.2.1.5 Co-cultures
			28.2.3 Biochemical cues
			28.2.4 Bioreactors
			28.2.5 Prophylactic tissue engineering constructs
		28.3 Future perspectives and unmet challenges
		References
Index
Back Cover
Front Cover
Biomaterials for 3D Tumor Modeling
Copyright Page
Contents
List of Contributors
Preface
I. Engineering biomaterials for 3D cancer modelling
	1 Trends in biomaterials for three-dimensional cancer modeling
		Abbreviations
		1.1 A historical introduction
			1.1.1 In vitro and in vivo models: an overview
			1.1.2 A paradigm shift
			1.1.3 Three-dimensional biomaterials for cancer modeling
			1.1.4 From the lab to the clinic
		1.2 The three-dimensional tumor microenvironment
			1.2.1 The tumor and its three-dimensional environment: a synergistic interaction
			1.2.2 Biomaterials as a model of the tumor niche
				1.2.2.1 Scaffold-based biomaterials
				1.2.2.2 Matrix-based
				1.2.2.3 Microcarrier-based
				1.2.2.4 Scaffold-free: tumor spheroids
				1.2.2.5 Microstructured surfaces
		1.3 Engineering the native tumor microenvironment using custom-designed three-dimensional biomaterials
			1.3.1 Tissue engineering approaches
				1.3.1.1 Freeze-drying
				1.3.1.2 Photopolymerization
				1.3.1.3 Three-dimensional bioprinting
			1.3.2 Nanotechnology approaches
				1.3.2.1 Molding
				1.3.2.2 Printing
					1.3.2.2.1 (Two-dimensional) microcontact printing
					1.3.2.2.2 Three-dimensional printing
					1.3.2.2.3 Four-dimensional printing
		1.4 Advanced models of the three-dimensional tumor microenvironment
			1.4.1 Microfluidics-based models
				1.4.1.1 Microfluidic-based models of tumors: tumor-on-a-chip
				1.4.1.2 Drug discovery and screening on-chip
				1.4.1.3 Reproducing dynamic events on-chip
				1.4.1.4 Personalized tumor-on-a-chip models
				1.4.1.5 Manufacturing methods of a tumor-on-a-chip
			1.4.2 Three-dimensional bioprinted models
		1.5 Applications of three-dimensional tumor models in cancer therapeutics
			1.5.1 Drug discovery, development, and screening
			1.5.2 Transport and delivery of drugs
		1.6 Limitations of biomaterials-based three-dimensional tumor models
		1.7 Future of three-dimensional biomaterials for cancer research
		1.8 Final remarks and conclusions
		References
	2 Bioinspired biomaterials to develop cell-rich spherical microtissues for 3D in vitro tumor modeling
		2.1 Introduction
		2.2 Human Tumor microenvironment—key hallmarks to mimic in vitro
		2.3 3D In vitro tumor models—bridging the gap from 2D flat cultures to in vivo
		2.4 Classes of 3D multicellular tumor models
			2.4.1 Scaffold-free cell-rich 3D multicellular tumor spheroids
			2.4.2 Scaffold-based 3D multicellular tumor models
				2.4.2.1 Biomaterials for establishing physiomimetic 3D tumor microenvironments
					2.4.2.1.1 Natural and nature-derived biomaterials for 3D tumor modeling
						Protein-based biomaterials
						Polysaccharide-based biomaterials
					2.4.2.1.2 Synthetic biomaterials for 3D tumor modeling
					2.4.2.1.3 Hybrid biomaterials for 3D tumor modeling
			2.4.3 Generation of spherically structured cell-rich 3D tumor models
				2.4.3.1 Microparticles for spherically structured 3D tumor models assembly
				2.4.3.2 Microgels for spherically structured 3D tumor models assembly
				2.4.3.3 Microcapsules for spherically structured 3D tumor models assembly
		2.5 Conclusions
		References
	3 Biofabrication of 3D tumor models in cancer research
		3.1 Current challenges in oncology
		3.2 The tumor microenvironment
		3.3 Development of the cancer therapeutics field
		3.4 3D tumor models in cancer research
			3.4.1 Nonscaffold-based 3D cell culture methods
			3.4.2 Scaffold-based 3D cell culture methods
		3.5 Evaluation of anticancer therapeutics in 3D tumor models
			3.5.1 Drug screening/drug resistance
			3.5.2 Anticancer nanomedicines
		3.6 Implementation of 3D tumor models in a clinical setting
		3.7 Final remarks
		References
	4 Biomatrices that mimic the cancer extracellular environment
		4.1 Introduction
		4.2 The three-dimensional in vitro models
			4.2.1 Natural-based models
				4.2.1.1 Protein-based systems
				4.2.1.2 Polysaccharide-based systems
				4.2.1.3 Other natural occurring materials
			4.2.2 Synthetic and other biobased models
			4.2.3 Mimicking the tumor microenvironment mechanical features
		4.3 Conclusions and future remarks
		References
	5 3D neuroblastoma in vitro models using engineered cell-derived matrices
		5.1 Introduction
		5.2 Neuroblastoma
			5.2.1 Evidence of cell–extracellular matrix interaction in neuroblastoma
		5.3 Cell-derived matrices in tumor modeling
		5.4 Engineering cell-derived matrix deposition
			5.4.1 Cell source
			5.4.2 Culture medium composition
			5.4.3 Culture substrates and conditions
			5.4.4 Decellularization agents
			5.4.5 Chemical and physical modifications
		5.5 Cell-derived matrices and cell morphodynamic characterization
		5.6 Cell-derived matrix capture relevant processes involved in neuroblastoma malignancy
		5.7 Conclusions
		References
	6 3D culture systems as models for solid tumors and cancer metabolism
		Abbreviations
		6.1 Introduction
		6.2 Solid tumors: tumor microenvironment and tumorigenesis
		6.3 Cancer metabolism: influence in tumor microenvironment
		6.4 Solid tumors in vitro models
			6.4.1 2D cell culture systems in cancer research
			6.4.2 3D cell culture systems
		6.5 3D cell culture systems in cancer research
		6.6 3D cell culture systems for study cancer metabolism
		6.7 Conclusions
		Conflict of interest
		References
	7 Biomaterials as ECM-like matrices for 3D in vitro tumor models
		Abbreviations
		7.1 Introduction
		7.2 Biomaterials as ECM-like matrices for cancer 3D in vitro models
			7.2.1 Synthetic
			7.2.2 Natural-based
				7.2.2.1 Proteins
				7.2.2.2 Polysaccharides
			7.2.3 Decellularized matrices
		7.3 Conclusion and future trends
		References
	8 Three-dimensional in vitro models of angiogenesis
		8.1 Vessels formation and tumor angiogenesis
		8.2 Vascular extracellular matrix
			8.2.1 Vascular basement membrane composition
			8.2.2 Interstitial matrix
		8.3 Endothelial cells-based 3D angiogenesis models
			8.3.1 Vascular differentiation in embryoid body
			8.3.2 Tube formation on basement membrane matrix gel
			8.3.3 Sprouting from endothelial cell spheroids in collagen gel
		8.4 Vascular explant-based 3D angiogenesis models
			8.4.1 Rat aortic ring sprouting assay
			8.4.2 Mouse aortic ring sprouting assay
			8.4.3 Human arterial ring angiogenesis assay
		8.5 Microvessels on a chip
			8.5.1 Microfluidics-based devices
			8.5.2 3D bioprinting and sacrificial templating
			8.5.3 Organ-on-a-chip
		8.6 Future perspectives
		References
	9 Metastasis in three-dimensional biomaterials
		9.1 Why biomaterial is needed in cancer modeling?
		9.2 Biomaterials employed in tumor ECM modeling
			9.2.1 Naturally derived biomaterials
				9.2.1.1 Collagen
				9.2.1.2 Gelatin
				9.2.1.3 Laminin-rich extracellular matrix
				9.2.1.4 Alginate
				9.2.1.5 Chitosan
				9.2.1.6 Hyaluronic acid
				9.2.1.7 Silk
			9.2.2 Synthetic biomaterials
				9.2.2.1 Polyethylene glycol and its derivatives
				9.2.2.2 Poly(lactic-co-glycolic) acid
				9.2.2.3 Polycaprolactone
				9.2.2.4 Polyacrylamide
				9.2.2.5 Polydimethylsiloxane
				9.2.2.6 Thermoresponsive polymers
		9.3 Properties of cell surrounding matrix/niche contribute to tumor cell migration
			9.3.1 Pore size
			9.3.2 Topography or contact guidance
			9.3.3 Stiffness
			9.3.4 Matrix rheology
			9.3.5 Ligand accessibility
		9.4 Biomaterial-based stepwise modeling of cancer metastasis in vitro
			9.4.1 Tumor initiation and progression
			9.4.2 Tumor angiogenesis
			9.4.3 Modeling of tumor invasion or migration
				9.4.3.1 Spheroids
				9.4.3.2 Transwell-based models
				9.4.3.3 Microfluidic models
			9.4.4 Intravasation models
				9.4.4.1 Prevascularized spheroids
				9.4.4.2 Microfluidic devices
				9.4.4.3 Magnetic force-based cell patterning
			9.4.5 Extravasation and colonization
		9.5 Biomaterial-based in vitro models of cancer dormancy and reactivation
		9.6 Concluding remarks
		References
	10 3D cancer spheroids and microtissues
		Abbreviations
		10.1 Introduction
		10.2 Biomaterials advances tumor cell culture to the third dimension
			10.2.1 Biodegradable microcarriers to develop in vitro 3D heterotypic tumor models
			10.2.2 Exogenous extracellular matrix as support for the growth of tumor spheroids
		10.3 Recapitulating the tumor–stroma crosstalk in spheroid and microtissue models
			10.3.1 The role of cancer-associated fibroblasts in promoting cancer progression
			10.3.2 Co-cultured spheroid models
		10.4 Vascularized microtumor models
			10.4.1 Endothelial cells promote invasion and migration of cancer cells
			10.4.2 Multicellular spheroids to recapitulate the tumor angiogenesis
			10.4.3 Tumor microtissues as 3D bioengineered architecture to study cancer vascularization
		10.5 The contribution of immune system cells in microtumors
			10.5.1 Macrophage: the double side of the same player
			10.5.2 Spheroids incorporating the immune system cells
			10.5.3 3D complex architecture to copycat the immune-competence in tumors
		10.6 Spheroids as screening platform for drug testing
			10.6.1 The importance of moving 3D culture to high-throughput screening approaches
			10.6.2 The development of novel methodology for solving high-content imaging problem in preclinical study models
		10.7 Conclusion and future trends
		References
	11 Biomaterial-based in vitro models for pancreatic cancer
		11.1 Introduction
		11.2 In vitro 3D models for pancreatic cancer
			11.2.1 Spheroids and organoids
			11.2.2 Hydrogels
			11.2.3 Polymer scaffolds
		11.3 Using 3D models for disease understanding
			11.3.1 Biomimetic role of scaffold features
			11.3.2 Tumor progression and metastasis
		11.4 Using 3D models for therapeutic screening
		11.5 Conclusions and future trends
		References
	12 In vitro three-dimensional modeling for prostate cancer
		12.1 Introduction
			12.1.1 Preclinical models for addressing prostate cancer
				12.1.1.1 In vivo models
				12.1.1.2 In vitro models
			12.1.2 Three-dimensional in vitro models of prostate cancer
				12.1.2.1 Spherical cancer models
				12.1.2.2 Bioengineered models
				12.1.2.3 Microfluidic models
				12.1.2.4 Bioreactors
				12.1.2.5 Organ explants
		12.2 Modeling primary tumors
			12.2.1 Modeling localized prostate cancer
				12.2.1.1 Monocellular models of primary tumors
				12.2.1.2 Multicellular models of primary tumors incorporating stromal elements
			12.2.2 Three-dimensional models to address androgen-mediated biology
			12.2.3 Three-dimensional models for prostate cancer stem cells
			12.2.4 Three-dimensional models to address therapeutic response
		12.3 Modeling early stages of prostate cancer progression
			12.3.1 Modeling tumor invasion
			12.3.2 Modeling angiogenesis and the contribution of vessels to tumor progression
			12.3.3 Isolation of circulating tumor cells
			12.3.4 Extravasation
		12.4 Modeling advanced stages of prostate cancer progression
			12.4.1 Disseminated tumor cells
			12.4.2 Three-dimensional models to address the biology of prostate cancer bone metastasis
			12.4.3 Three-dimensional models to address the therapeutic response of metastatic prostate cancer to bone
			12.4.4 Three-dimensional models of metastatic prostate cancer to the liver
		12.5 Conclusion
		References
	13 3D in vitro cutaneous melanoma models
		Abbreviations
		13.1 Introduction
		13.2 Types of melanoma
		13.3 Risk factors for melanoma
			13.3.1 Ultraviolet radiation
			13.3.2 Heritable factors
		13.4 Cutaneous melanoma development
		13.5 Cutaneous melanoma treatment
			13.5.1 Classic approach
			13.5.2 Immunotherapy
			13.5.3 Targeted therapy
		13.6 In vitro models
			13.6.1 3D in vitro melanoma models
				13.6.1.1 Spheroids
				13.6.1.2 Organotypic cutaneous melanoma models
		References
	14 3D scaffold materials for skin cancer modeling
		14.1 Introduction
		14.2 Effective factors in cell culture; 2D and 3D models
			14.2.1 Ethical and economical parameters
			14.2.2 Biological parameters
				14.2.2.1 Angiogenesis capabilities
				14.2.2.2 Attachment capabilities to the extracellular matrix
			14.2.3 Physical parameters
				14.2.3.1 Cell density, proteins, and adhesion molecules
				14.2.3.2 Surface properties
			14.2.4 Tumor microenvironmental properties
			14.2.5 Hydrophobicity/hydrophilicity effects
		14.3 Skin cancers
		14.4 Modeling of skin cancer
			14.4.1 In vitro skin cancer modeling
				14.4.1.1 Spheroid formation
				14.4.1.2 Natural-based 3D scaffolds
				14.4.1.3 Peptide-derived hydrogels
				14.4.1.4 3D fiber scaffolding in vitro models
				14.4.1.5 Chemical additives in 3D culture
				14.4.1.6 Biomaterials based 3D models
				14.4.1.7 3D cell cultures using microfluidic devices
			14.4.2 In vivo models
			14.4.3 New insights in 3D models of skin cancer
				14.4.3.1 Microfluidic approach
				14.4.3.2 Personalized medicine
		14.5 Conclusion and future prospective
		Conflict of interest
		References
II. Advanced models for cancer research
	15 Microfluidic systems in cancer research
		15.1 Introduction
			15.1.1 Background
			15.1.2 Traditional systems for tumor diagnosis and modeling
			15.1.3 Microfluidics and cancer: main tools and applications
		15.2 Fundamentals of microfluidics: fluid mechanics in miniaturized devices
			15.2.1 Laminar flow
			15.2.2 Diffusion
			15.2.3 Surface tension
			15.2.4 Capillary forces
			15.2.5 Flow rate and resistance
		15.3 Fabrication principles of microfluidic devices
			15.3.1 Molding
				15.3.1.1 Replica molding
				15.3.1.2 Hot embossing
				15.3.1.3 Microthermoforming
				15.3.1.4 Microinjection molding
			15.3.2 Sacrificial templating
			15.3.3 3D (bio)printing
		15.4 Mimicking the tumor microenvironment using microfluidics
			15.4.1 The tumor microenvironment: an overview
			15.4.2 Microfluidics for reproducing biochemical cues during tumor invasion
				15.4.2.1 Biochemical gradients
				15.4.2.2 Oxygen gradients and hypoxia
				15.4.2.3 Microdroplet generation
			15.4.3 Microfluidics for reproducing mechanical cues in tumor invasion
				15.4.3.1 Physical constrictions
				15.4.3.2 Anisotropic features
				15.4.3.3 Mechanical deformation
				15.4.3.4 Modulating matrix stiffness
				15.4.3.5 Interstitial fluid pressure and flow
		15.5 Microfluidic models of cancer
			15.5.1 Organ-on-a-chip technology
			15.5.2 Organ-on-a-chip models of cancer metastasis: cancer- or tumor-on-a-chip
				15.5.2.1 Tumor growth and invasion models
				15.5.2.2 Angiogenesis models
				15.5.2.3 Lymphatic system and lymphangiogenesis models
				15.5.2.4 Intravasation models
				15.5.2.5 Extravasation models
				15.5.2.6 Multiorgan and organ specificity models
			15.5.3 Liquid biopsy-on-a-chip: isolation of CTCs
			15.5.4 Microfluidics for cancer biomarkers detection
		15.6 Future perspectives
			15.6.1 Microfluidic cancer models for clinical applications
			15.6.2 Microfluidic cancer models for industrial applications
		15.7 Conclusions
		Conflicts of interest
		References
	16 Perfusion-based 3D tumor-on-chip devices for anticancer drug testing
		Abbreviations
		16.1 Introduction
		16.2 Disadvantages of 2D in vitro, 3D in vitro, and animal models
		16.3 Microfluidic devices for tumor modeling
		16.4 Tumor components and their inclusion in tumor-on-chip
			16.4.1 Cells: monoculture/co-culture
			16.4.2 ECM: chemical and mechanical cues
			16.4.3 Growth factors
			16.4.4 Shear stress
		16.5 Types of perfusion methods
		16.6 Benefits of perfusion and specific applications
			16.6.1 Vasculature
			16.6.2 Multiorgan systems
			16.6.3 Interstitial flow within 3D hydrogel systems
			16.6.4 Drug pharmacokinetics and pharmacodynamics
		16.7 Specific designs for enhancing perfusion
		16.8 Conclusion
		References
	17 Engineering breast cancer models in vitro with 3D bioprinting
		17.1 Breast cancer microenvironment in vivo
			17.1.1 Types and stages of breast cancer
			17.1.2 Cancer cell behavior in vivo, microenvironment structure and mechanics
		17.2 Biomaterial-based breast cancer in vitro models
			17.2.1 Mammary morphogenesis in 3D
			17.2.2 Studies on cancer cell migration in 3D (metastasis models)
			17.2.3 3D spheroid and organoid invasion models
			17.2.4 3D models of heterotypic tumor–stromal interactions
		17.3 Biomaterials design for in vitro breast cancer models
			17.3.1 Natural, synthetic, and hybrid biomaterials
			17.3.2 Matrix stiffness, cross-linking, and network architecture
			17.3.3 Time-dependent and nonlinear mechanics
			17.3.4 Stimuli-responsive dynamic materials
			17.3.5 Biomaterial inks for 3D bioprinting
		17.4 3D bioprinting methods and their suitability for breast cancer in vitro engineering
			17.4.1 Microextrusion- and laser-induced forward transfer used in breast cancer research
			17.4.2 Volumetric and sacrificial bioprinting as future technologies in cancer research
			17.4.3 Bioprinting heterotypic cancer models for functional treatment modeling
		17.5 Discussion and outlook
			17.5.1 Evolution of breast cancer in vitro 3D models: from 2D culture to 3D bioprinting
			17.5.2 Advantages and challenges of 3D bioprinting in breast cancer research
			17.5.3 3D bioprinting in personalized breast cancer research and clinical treatment prognosis
		References
	18 A predictive oncology framework—modeling tumor proliferation using a FEM platform
		Chapter points
		18.1 Introduction
			18.1.1 A vision of feasible virtualized oncological prognoses
			18.1.2 An engineering approach toward predictive oncology
			18.1.3 The cancer liver: a valuable case study
		18.2 A perspective framework of predictive oncology
			18.2.1 Step 1: Acquisition of diagnostic images
			18.2.2 Step 2: Real 2 virtual image
				18.2.2.1 By using some open-source software
				18.2.2.2 By using some proprietary software
			18.2.3 Step 3: Mathematical formulation
				18.2.3.1 Level 0
				18.2.3.2 Level 1
				18.2.3.3 Level 2
			18.2.4 Step 4: Solution and postprocessing
			18.2.5 Step 5: Replication of the model
		18.3 Detailed model formulation using level 1 modeling
			18.3.1 The biological conversion logistics-based mechanisms
			18.3.2 Governing equations
			18.3.3 Initial conditions, proliferation, and therapy onset
			18.3.4 Boundary conditions
		18.4 A sensitivity analysis of hallmark parameters: results
			18.4.1 Numerical treatment
			18.4.2 Model validation: application to a hepatocellular carcinoma—Case 0
			18.4.3 Model application to different tumor growth rates—Cases 1 and 2
			18.4.4 Model application to different therapies—Cases 3 to 7
			18.4.5 Model application to different values of tumor and drug diffusivities—Cases 8 to 11
		18.5 POEM as a tool to empower the clinical decisions
		18.6 Conclusions
		Glossary
		References
III. Tumor models for drug discovery and therapeutics
	19 Tissue-engineered 3D cancer microenvironment for screening therapeutics
		19.1 Introduction
		19.2 Tumor microenvironment
			19.2.1 Cellular components
			19.2.2 Non-cellular components
		19.3 Current strategies for creating cell and matrix organization to mimic microenvironment
			19.3.1 Organoid derivation options (patient-derived organoid vs patient-derived xenograft)
			19.3.2 Transwell-based assays
			19.3.3 Organotypic model
			19.3.4 Microfluidic devices
			19.3.5 Micromolded 3D gels
			19.3.6 Multicellular spheroid
			19.3.7 Stacked paper models
			19.3.8 Cell sources used in tissue-engineered models
		19.4 Modeling important aspects of the tumor microenvironment
			19.4.1 In vitro models of tumor–fibroblast interactions
			19.4.2 In vitro models of tumor–immune interactions
			19.4.3 In vitro models of hypoxia and small molecular gradients
				19.4.3.1 Oxygen gradients
				19.4.3.2 Gradients of cytokines and other signaling factors
			19.4.4 In vitro models of tumor vasculature
		19.5 Future outlook
		References
	20 Three-dimensional tumor model and their implication in drug screening for tackling chemoresistance
		Abbreviations
		20.1 Chemoresistance in cancer
		20.2 3D tumor culture: an advanced model preferred over 2D culture
		20.3 3D culture and chemoresistance
			20.3.1 3D culture acts as a good model to study chemoresistance
			20.3.2 Importance of tumor microenvironment interaction in the development of chemoresistance
			20.3.3 Tumor heterogeneity and chemoresistance
		20.4 Methods of generating 3D culture system
			20.4.1 Methods of generating 3D organoids
			20.4.2 Methods of generating 3D spheroids
				20.4.2.1 Hanging drop model
				20.4.2.2 Nonadherent surface model
				20.4.2.3 Suspension culture model
				20.4.2.4 Scaffold-based model
				20.4.2.5 Magnetic levitation model
		20.5 3D culture and biomaterials
			20.5.1 Cell-derived or natural biomaterials
				20.5.1.1 Collagen
				20.5.1.2 Laminin-rich extracellular matrix
				20.5.1.3 Alginate matrix
				20.5.1.4 Chitosan matrix
				20.5.1.5 Silk
				20.5.1.6 Matrigel
				20.5.1.7 Hyaluronan-based hydrogel
			20.5.2 Synthetic biomaterials
				20.5.2.1 Polyethylene glycol-based hydrogel
				20.5.2.2 Polyethylene glycol-dextran aqueous two-phase system
				20.5.2.3 Polycaprolactone
				20.5.2.4 Poly(lactic-co-glycolic) acid
				20.5.2.5 Thermoresponsive hydrogels
		20.6 Drug screening in 3D culture
			20.6.1 Importance of organoids for developing personalized medicines
			20.6.2 Organoids in cancer medicine
			20.6.3 Patient-derived organoids used for cancer drug screening
		20.7 Future aspects of the 3D tumor organoid model: biobanks for tumor tissues
		20.8 Limitations of 3D culture technology
		20.9 Conclusion
		References
	21 Co-culture and 3D tumor models for drug/gene therapy testing
		21.1 Introduction
		21.2 Lung cancer
			21.2.1 Scaffold chemo/drug treatment
			21.2.2 Scaffold gene therapy
			21.2.3 Scaffold co-culture chemo/drug treatment
			21.2.4 Hydrogel chemo/drug treatment
			21.2.5 Hydrogel co-culture
		21.3 Breast cancer
			21.3.1 Scaffolds chemo/drug therapy
			21.3.2 Scaffolds gene therapy
			21.3.3 Scaffolds co-culture chemotherapy
			21.3.4 Hydrogels and chemo/drug therapy
			21.3.5 Hydrogels and gene therapy
		21.4 Prostate cancer
			21.4.1 Scaffold chemo/drug treatment
			21.4.2 Scaffold gene therapy
			21.4.3 Scaffold co-culture gene therapy
			21.4.4 Hydrogel chemo/drug treatment
			21.4.5 Hydrogel gene therapy
			21.4.6 Hydrogel co-culture chemo
		21.5 Future outlook
		References
	22 Newly emerged engineering of in vitro 3D tumor models using biomaterials for chemotherapy
		22.1 Introduction
		22.2 Constitution of artificially engineered tumor models
			22.2.1 Cells
			22.2.2 Materials
		22.3 Newly emerged engineering of in vitro 3D tumors for chemotherapy
			22.3.1 Microfluidic tumor models
				22.3.1.1 Fluid network for mimicking vasculature
				22.3.1.2 Easy and efficient set-up for massive drug screening
				22.3.1.3 “Organ-on-a-chip” for investigating organ-specific drug response
				22.3.1.4 Integration of multimicrochips for systemic drug toxicity evaluation
			22.3.2 Bioprinted 3D tumor models
		22.4 Summary
		References
	23 Marine-derived biomaterials for cancer treatment
		23.1 Introduction
		23.2 Marine biopolymers as bioactive agents
			23.2.1 Fucoidan
			23.2.2 Chitosan
		23.3 Drug-delivery systems
			23.3.1 Fucoidan-based systems
			23.3.2 Chitosan-based systems
			23.3.3 Carrageenan-based systems
			23.3.4 Alginate-based systems
		23.4 Three-dimensional in vitro models of cancer
			23.4.1 Chitosan-based cancer models
			23.4.2 Alginate-based cancer models
			23.4.3 Chitosan-alginate-based cancer models
		23.5 Conclusions
		References
	24 Mesoporous silica nanoparticles for cancer theranostic applications
		24.1 Introduction
		24.2 MSNs chemistry
		24.3 Biological effects of MSNs
		24.4 3D modeling of MSN for cancer therapy
			24.4.1 Hydrogels
			24.4.2 Electrospun nanofiber scaffolds
			24.4.3 3D-printed scaffolds
		24.5 Medical applications of MSNs
			24.5.1 Stimuli-responsive drug release
				24.5.1.1 pH-responsive
				24.5.1.2 Redox-responsive
				24.5.1.3 Light-responsive
				24.5.1.4 Magnetic field-responsive
			24.5.2 Targeted drug delivery
				24.5.2.1 Cell-membrane targeting
				24.5.2.2 Cell-cytoplasm targeting
			24.5.3 Other therapeutic strategies
				24.5.3.1 Phototherapy
				24.5.3.2 Ultrasound therapy
				24.5.3.3 Chemodynamic therapy
		24.6 Diagnostic application of MSNs
			24.6.1 Magnetic resonance imaging
			24.6.2 Fluorescent/luminescent imaging
			24.6.3 Positron emission tomography imaging
		24.7 Theranostics application of MSNs
		24.8 Conclusions and outlook
		References
IV. Point-of-care applications
	25 Causes of cancer: physical, chemical, biological carcinogens, and viruses
		Abbreviations
		25.1 Introduction
			25.1.1 How normal cells become cancerous?
			25.1.2 Stages of carcinogenesis
				25.1.2.1 Initiation
				25.1.2.2 Promotion
				25.1.2.3 Progression
			25.1.3 Carcinogens
		25.2 Physical carcinogens
			25.2.1 Mechanism of action of physical carcinogens
			25.2.2 Electromagnetic radiation
			25.2.3 Ionizing radiation
			25.2.4 Hard and soft materials
				25.2.4.1 Asbestos
				25.2.4.2 Erionite
				25.2.4.3 Nonfibrous particulate materials
				25.2.4.4 Air pollutants
				25.2.4.5 Gel materials
			25.2.5 Trauma
		25.3 Chemical carcinogens
			25.3.1 Mechanisms of chemical carcinogenesis
			25.3.2 Types of chemical carcinogens
				25.3.2.1 Aromatic amines
				25.3.2.2 N-Nitroso compounds
				25.3.2.3 Dyes
				25.3.2.4 Alkylating agents
				25.3.2.5 Natural carcinogens
				25.3.2.6 Inorganic carcinogenic agents
				25.3.2.7 Solvents and other compounds
		25.4 Biological carcinogens and viruses
			25.4.1 Mechanisms of biological carcinogenesis
			25.4.2 Viral carcinogens
				25.4.2.1 Epstein–Barr virus
				25.4.2.2 Hepatitis B virus
				25.4.2.3 Hepatitis C virus
				25.4.2.4 Kaposi sarcoma herpesvirus
				25.4.2.5 Human immunodeficiency virus-1
				25.4.2.6 Human papillomavirus
				25.4.2.7 Human T-cell lymphotropic virus type-1
			25.4.3 Bacterial carcinogens
				25.4.3.1 Helicobacter pylori
			25.4.4 Protozoal carcinogens
				25.4.4.1 Opisthorchis viverrini and Clonorchis sinensis
				25.4.4.2 Schistosoma haematobium
			25.4.5 Other biological carcinogens
		25.5 Conclusion
		References
	26 Biodetection and sensing for cancer diagnostics
		26.1 Introduction
		26.2 Biomarkers for cancer detection
			26.2.1 Protein biomarkers
			26.2.2 Circulating tumor cells
			26.2.3 MicroRNAs
			26.2.4 Circulating tumor DNA
			26.2.5 Biomarker panels
		26.3 Cancer biosensors
			26.3.1 Electrochemical biosensors
			26.3.2 Optical biosensors
			26.3.3 Piezoelectric biosensors
		26.4 Commercialization and clinical trials of cancer biosensors
		26.5 Conclusions
		References
	27 Understanding the impact of controlled oxygen delivery to 3D cancer cell culture
		27.1 Introduction
		27.2 What is known about physiological oxygen levels?
			27.2.1 Normoxia versus physoxia
			27.2.2 Hypoxia (physiological vs pathological)
			27.2.3 Tumor hypoxia
		27.3 Importance of oxygen levels in various stages of cancer progression
			27.3.1 Hypoxia
			27.3.2 Angiogenesis
			27.3.3 Metastasis
		27.4 Techniques for measuring oxygenation
			27.4.1 Oxygen-sensing electrodes
			27.4.2 Biologic and synthetic absorptiometric probes
			27.4.3 Fluorescent and phosphorescent luminescent probes
			27.4.4 Spectroscopic imaging: magnetic, paramagnetic, and electron spin resonance
		27.5 Traditional/current strategies for controlling oxygen concentration in vitro
			27.5.1 Hypoxia chambers and two-dimensional models
			27.5.2 Three-dimensional models: spheroids
			27.5.3 Other strategies for controlling oxygen delivery in 3D: lab-on-chip systems, bioreactors
		27.6 Characterizing the effects of oxygenation on cells and tissues
			27.6.1 RNA-Seq
			27.6.2 qPCR of downstream targets
			27.6.3 Pimonidazole staining
			27.6.4 Real-time imaging of growth
			27.6.5 Metabolic characterization and imaging
			27.6.6 In vivo metabolic imaging
			27.6.7 In vitro metabolic imaging
		27.7 Conclusions and future prospects
		References
	28 Tissue engineering strategies for the treatment of skeletal maxillofacial defects resulting from neoplasms resections
		28.1 Background
			28.1.1 Oral and maxillofacial neoplasms
				28.1.1.1 Myxoma
				28.1.1.2 Ameloblastoma
				28.1.1.3 Odontoma
				28.1.1.4 Odontogenic keratocyst
				28.1.1.5 Central giant cells granuloma
			28.1.2 Currently used therapies
		28.2 Tissue engineering for reconstruction of ablated skeletal maxillofacial tissues
			28.2.1 Scaffolds
				28.2.1.1 Inorganic materials
				28.2.1.2 Synthetic polymeric materials
				28.2.1.3 Natural polymers
			28.2.2 Cells
				28.2.2.1 Mesenchymal stem cells
					28.2.2.1.1 Bone marrow derived stem cells
					28.2.2.1.2 Periosteal-derived progenitor cells
					28.2.2.1.3 Adipose tissue-derived stem cells
					28.2.2.1.4 Dental pulp stem cells
					28.2.2.1.5 Co-cultures
			28.2.3 Biochemical cues
			28.2.4 Bioreactors
			28.2.5 Prophylactic tissue engineering constructs
		28.3 Future perspectives and unmet challenges
		References
Index
Back Cover
Front Cover
Biomaterials for 3D Tumor Modeling
Copyright Page
Contents
List of Contributors
Preface
I. Engineering biomaterials for 3D cancer modelling
	1 Trends in biomaterials for three-dimensional cancer modeling
		Abbreviations
		1.1 A historical introduction
			1.1.1 In vitro and in vivo models: an overview
			1.1.2 A paradigm shift
			1.1.3 Three-dimensional biomaterials for cancer modeling
			1.1.4 From the lab to the clinic
		1.2 The three-dimensional tumor microenvironment
			1.2.1 The tumor and its three-dimensional environment: a synergistic interaction
			1.2.2 Biomaterials as a model of the tumor niche
				1.2.2.1 Scaffold-based biomaterials
				1.2.2.2 Matrix-based
				1.2.2.3 Microcarrier-based
				1.2.2.4 Scaffold-free: tumor spheroids
				1.2.2.5 Microstructured surfaces
		1.3 Engineering the native tumor microenvironment using custom-designed three-dimensional biomaterials
			1.3.1 Tissue engineering approaches
				1.3.1.1 Freeze-drying
				1.3.1.2 Photopolymerization
				1.3.1.3 Three-dimensional bioprinting
			1.3.2 Nanotechnology approaches
				1.3.2.1 Molding
				1.3.2.2 Printing
					1.3.2.2.1 (Two-dimensional) microcontact printing
					1.3.2.2.2 Three-dimensional printing
					1.3.2.2.3 Four-dimensional printing
		1.4 Advanced models of the three-dimensional tumor microenvironment
			1.4.1 Microfluidics-based models
				1.4.1.1 Microfluidic-based models of tumors: tumor-on-a-chip
				1.4.1.2 Drug discovery and screening on-chip
				1.4.1.3 Reproducing dynamic events on-chip
				1.4.1.4 Personalized tumor-on-a-chip models
				1.4.1.5 Manufacturing methods of a tumor-on-a-chip
			1.4.2 Three-dimensional bioprinted models
		1.5 Applications of three-dimensional tumor models in cancer therapeutics
			1.5.1 Drug discovery, development, and screening
			1.5.2 Transport and delivery of drugs
		1.6 Limitations of biomaterials-based three-dimensional tumor models
		1.7 Future of three-dimensional biomaterials for cancer research
		1.8 Final remarks and conclusions
		References
	2 Bioinspired biomaterials to develop cell-rich spherical microtissues for 3D in vitro tumor modeling
		2.1 Introduction
		2.2 Human Tumor microenvironment—key hallmarks to mimic in vitro
		2.3 3D In vitro tumor models—bridging the gap from 2D flat cultures to in vivo
		2.4 Classes of 3D multicellular tumor models
			2.4.1 Scaffold-free cell-rich 3D multicellular tumor spheroids
			2.4.2 Scaffold-based 3D multicellular tumor models
				2.4.2.1 Biomaterials for establishing physiomimetic 3D tumor microenvironments
					2.4.2.1.1 Natural and nature-derived biomaterials for 3D tumor modeling
						Protein-based biomaterials
						Polysaccharide-based biomaterials
					2.4.2.1.2 Synthetic biomaterials for 3D tumor modeling
					2.4.2.1.3 Hybrid biomaterials for 3D tumor modeling
			2.4.3 Generation of spherically structured cell-rich 3D tumor models
				2.4.3.1 Microparticles for spherically structured 3D tumor models assembly
				2.4.3.2 Microgels for spherically structured 3D tumor models assembly
				2.4.3.3 Microcapsules for spherically structured 3D tumor models assembly
		2.5 Conclusions
		References
	3 Biofabrication of 3D tumor models in cancer research
		3.1 Current challenges in oncology
		3.2 The tumor microenvironment
		3.3 Development of the cancer therapeutics field
		3.4 3D tumor models in cancer research
			3.4.1 Nonscaffold-based 3D cell culture methods
			3.4.2 Scaffold-based 3D cell culture methods
		3.5 Evaluation of anticancer therapeutics in 3D tumor models
			3.5.1 Drug screening/drug resistance
			3.5.2 Anticancer nanomedicines
		3.6 Implementation of 3D tumor models in a clinical setting
		3.7 Final remarks
		References
	4 Biomatrices that mimic the cancer extracellular environment
		4.1 Introduction
		4.2 The three-dimensional in vitro models
			4.2.1 Natural-based models
				4.2.1.1 Protein-based systems
				4.2.1.2 Polysaccharide-based systems
				4.2.1.3 Other natural occurring materials
			4.2.2 Synthetic and other biobased models
			4.2.3 Mimicking the tumor microenvironment mechanical features
		4.3 Conclusions and future remarks
		References
	5 3D neuroblastoma in vitro models using engineered cell-derived matrices
		5.1 Introduction
		5.2 Neuroblastoma
			5.2.1 Evidence of cell–extracellular matrix interaction in neuroblastoma
		5.3 Cell-derived matrices in tumor modeling
		5.4 Engineering cell-derived matrix deposition
			5.4.1 Cell source
			5.4.2 Culture medium composition
			5.4.3 Culture substrates and conditions
			5.4.4 Decellularization agents
			5.4.5 Chemical and physical modifications
		5.5 Cell-derived matrices and cell morphodynamic characterization
		5.6 Cell-derived matrix capture relevant processes involved in neuroblastoma malignancy
		5.7 Conclusions
		References
	6 3D culture systems as models for solid tumors and cancer metabolism
		Abbreviations
		6.1 Introduction
		6.2 Solid tumors: tumor microenvironment and tumorigenesis
		6.3 Cancer metabolism: influence in tumor microenvironment
		6.4 Solid tumors in vitro models
			6.4.1 2D cell culture systems in cancer research
			6.4.2 3D cell culture systems
		6.5 3D cell culture systems in cancer research
		6.6 3D cell culture systems for study cancer metabolism
		6.7 Conclusions
		Conflict of interest
		References
	7 Biomaterials as ECM-like matrices for 3D in vitro tumor models
		Abbreviations
		7.1 Introduction
		7.2 Biomaterials as ECM-like matrices for cancer 3D in vitro models
			7.2.1 Synthetic
			7.2.2 Natural-based
				7.2.2.1 Proteins
				7.2.2.2 Polysaccharides
			7.2.3 Decellularized matrices
		7.3 Conclusion and future trends
		References
	8 Three-dimensional in vitro models of angiogenesis
		8.1 Vessels formation and tumor angiogenesis
		8.2 Vascular extracellular matrix
			8.2.1 Vascular basement membrane composition
			8.2.2 Interstitial matrix
		8.3 Endothelial cells-based 3D angiogenesis models
			8.3.1 Vascular differentiation in embryoid body
			8.3.2 Tube formation on basement membrane matrix gel
			8.3.3 Sprouting from endothelial cell spheroids in collagen gel
		8.4 Vascular explant-based 3D angiogenesis models
			8.4.1 Rat aortic ring sprouting assay
			8.4.2 Mouse aortic ring sprouting assay
			8.4.3 Human arterial ring angiogenesis assay
		8.5 Microvessels on a chip
			8.5.1 Microfluidics-based devices
			8.5.2 3D bioprinting and sacrificial templating
			8.5.3 Organ-on-a-chip
		8.6 Future perspectives
		References
	9 Metastasis in three-dimensional biomaterials
		9.1 Why biomaterial is needed in cancer modeling?
		9.2 Biomaterials employed in tumor ECM modeling
			9.2.1 Naturally derived biomaterials
				9.2.1.1 Collagen
				9.2.1.2 Gelatin
				9.2.1.3 Laminin-rich extracellular matrix
				9.2.1.4 Alginate
				9.2.1.5 Chitosan
				9.2.1.6 Hyaluronic acid
				9.2.1.7 Silk
			9.2.2 Synthetic biomaterials
				9.2.2.1 Polyethylene glycol and its derivatives
				9.2.2.2 Poly(lactic-co-glycolic) acid
				9.2.2.3 Polycaprolactone
				9.2.2.4 Polyacrylamide
				9.2.2.5 Polydimethylsiloxane
				9.2.2.6 Thermoresponsive polymers
		9.3 Properties of cell surrounding matrix/niche contribute to tumor cell migration
			9.3.1 Pore size
			9.3.2 Topography or contact guidance
			9.3.3 Stiffness
			9.3.4 Matrix rheology
			9.3.5 Ligand accessibility
		9.4 Biomaterial-based stepwise modeling of cancer metastasis in vitro
			9.4.1 Tumor initiation and progression
			9.4.2 Tumor angiogenesis
			9.4.3 Modeling of tumor invasion or migration
				9.4.3.1 Spheroids
				9.4.3.2 Transwell-based models
				9.4.3.3 Microfluidic models
			9.4.4 Intravasation models
				9.4.4.1 Prevascularized spheroids
				9.4.4.2 Microfluidic devices
				9.4.4.3 Magnetic force-based cell patterning
			9.4.5 Extravasation and colonization
		9.5 Biomaterial-based in vitro models of cancer dormancy and reactivation
		9.6 Concluding remarks
		References
	10 3D cancer spheroids and microtissues
		Abbreviations
		10.1 Introduction
		10.2 Biomaterials advances tumor cell culture to the third dimension
			10.2.1 Biodegradable microcarriers to develop in vitro 3D heterotypic tumor models
			10.2.2 Exogenous extracellular matrix as support for the growth of tumor spheroids
		10.3 Recapitulating the tumor–stroma crosstalk in spheroid and microtissue models
			10.3.1 The role of cancer-associated fibroblasts in promoting cancer progression
			10.3.2 Co-cultured spheroid models
		10.4 Vascularized microtumor models
			10.4.1 Endothelial cells promote invasion and migration of cancer cells
			10.4.2 Multicellular spheroids to recapitulate the tumor angiogenesis
			10.4.3 Tumor microtissues as 3D bioengineered architecture to study cancer vascularization
		10.5 The contribution of immune system cells in microtumors
			10.5.1 Macrophage: the double side of the same player
			10.5.2 Spheroids incorporating the immune system cells
			10.5.3 3D complex architecture to copycat the immune-competence in tumors
		10.6 Spheroids as screening platform for drug testing
			10.6.1 The importance of moving 3D culture to high-throughput screening approaches
			10.6.2 The development of novel methodology for solving high-content imaging problem in preclinical study models
		10.7 Conclusion and future trends
		References
	11 Biomaterial-based in vitro models for pancreatic cancer
		11.1 Introduction
		11.2 In vitro 3D models for pancreatic cancer
			11.2.1 Spheroids and organoids
			11.2.2 Hydrogels
			11.2.3 Polymer scaffolds
		11.3 Using 3D models for disease understanding
			11.3.1 Biomimetic role of scaffold features
			11.3.2 Tumor progression and metastasis
		11.4 Using 3D models for therapeutic screening
		11.5 Conclusions and future trends
		References
	12 In vitro three-dimensional modeling for prostate cancer
		12.1 Introduction
			12.1.1 Preclinical models for addressing prostate cancer
				12.1.1.1 In vivo models
				12.1.1.2 In vitro models
			12.1.2 Three-dimensional in vitro models of prostate cancer
				12.1.2.1 Spherical cancer models
				12.1.2.2 Bioengineered models
				12.1.2.3 Microfluidic models
				12.1.2.4 Bioreactors
				12.1.2.5 Organ explants
		12.2 Modeling primary tumors
			12.2.1 Modeling localized prostate cancer
				12.2.1.1 Monocellular models of primary tumors
				12.2.1.2 Multicellular models of primary tumors incorporating stromal elements
			12.2.2 Three-dimensional models to address androgen-mediated biology
			12.2.3 Three-dimensional models for prostate cancer stem cells
			12.2.4 Three-dimensional models to address therapeutic response
		12.3 Modeling early stages of prostate cancer progression
			12.3.1 Modeling tumor invasion
			12.3.2 Modeling angiogenesis and the contribution of vessels to tumor progression
			12.3.3 Isolation of circulating tumor cells
			12.3.4 Extravasation
		12.4 Modeling advanced stages of prostate cancer progression
			12.4.1 Disseminated tumor cells
			12.4.2 Three-dimensional models to address the biology of prostate cancer bone metastasis
			12.4.3 Three-dimensional models to address the therapeutic response of metastatic prostate cancer to bone
			12.4.4 Three-dimensional models of metastatic prostate cancer to the liver
		12.5 Conclusion
		References
	13 3D in vitro cutaneous melanoma models
		Abbreviations
		13.1 Introduction
		13.2 Types of melanoma
		13.3 Risk factors for melanoma
			13.3.1 Ultraviolet radiation
			13.3.2 Heritable factors
		13.4 Cutaneous melanoma development
		13.5 Cutaneous melanoma treatment
			13.5.1 Classic approach
			13.5.2 Immunotherapy
			13.5.3 Targeted therapy
		13.6 In vitro models
			13.6.1 3D in vitro melanoma models
				13.6.1.1 Spheroids
				13.6.1.2 Organotypic cutaneous melanoma models
		References
	14 3D scaffold materials for skin cancer modeling
		14.1 Introduction
		14.2 Effective factors in cell culture; 2D and 3D models
			14.2.1 Ethical and economical parameters
			14.2.2 Biological parameters
				14.2.2.1 Angiogenesis capabilities
				14.2.2.2 Attachment capabilities to the extracellular matrix
			14.2.3 Physical parameters
				14.2.3.1 Cell density, proteins, and adhesion molecules
				14.2.3.2 Surface properties
			14.2.4 Tumor microenvironmental properties
			14.2.5 Hydrophobicity/hydrophilicity effects
		14.3 Skin cancers
		14.4 Modeling of skin cancer
			14.4.1 In vitro skin cancer modeling
				14.4.1.1 Spheroid formation
				14.4.1.2 Natural-based 3D scaffolds
				14.4.1.3 Peptide-derived hydrogels
				14.4.1.4 3D fiber scaffolding in vitro models
				14.4.1.5 Chemical additives in 3D culture
				14.4.1.6 Biomaterials based 3D models
				14.4.1.7 3D cell cultures using microfluidic devices
			14.4.2 In vivo models
			14.4.3 New insights in 3D models of skin cancer
				14.4.3.1 Microfluidic approach
				14.4.3.2 Personalized medicine
		14.5 Conclusion and future prospective
		Conflict of interest
		References
II. Advanced models for cancer research
	15 Microfluidic systems in cancer research
		15.1 Introduction
			15.1.1 Background
			15.1.2 Traditional systems for tumor diagnosis and modeling
			15.1.3 Microfluidics and cancer: main tools and applications
		15.2 Fundamentals of microfluidics: fluid mechanics in miniaturized devices
			15.2.1 Laminar flow
			15.2.2 Diffusion
			15.2.3 Surface tension
			15.2.4 Capillary forces
			15.2.5 Flow rate and resistance
		15.3 Fabrication principles of microfluidic devices
			15.3.1 Molding
				15.3.1.1 Replica molding
				15.3.1.2 Hot embossing
				15.3.1.3 Microthermoforming
				15.3.1.4 Microinjection molding
			15.3.2 Sacrificial templating
			15.3.3 3D (bio)printing
		15.4 Mimicking the tumor microenvironment using microfluidics
			15.4.1 The tumor microenvironment: an overview
			15.4.2 Microfluidics for reproducing biochemical cues during tumor invasion
				15.4.2.1 Biochemical gradients
				15.4.2.2 Oxygen gradients and hypoxia
				15.4.2.3 Microdroplet generation
			15.4.3 Microfluidics for reproducing mechanical cues in tumor invasion
				15.4.3.1 Physical constrictions
				15.4.3.2 Anisotropic features
				15.4.3.3 Mechanical deformation
				15.4.3.4 Modulating matrix stiffness
				15.4.3.5 Interstitial fluid pressure and flow
		15.5 Microfluidic models of cancer
			15.5.1 Organ-on-a-chip technology
			15.5.2 Organ-on-a-chip models of cancer metastasis: cancer- or tumor-on-a-chip
				15.5.2.1 Tumor growth and invasion models
				15.5.2.2 Angiogenesis models
				15.5.2.3 Lymphatic system and lymphangiogenesis models
				15.5.2.4 Intravasation models
				15.5.2.5 Extravasation models
				15.5.2.6 Multiorgan and organ specificity models
			15.5.3 Liquid biopsy-on-a-chip: isolation of CTCs
			15.5.4 Microfluidics for cancer biomarkers detection
		15.6 Future perspectives
			15.6.1 Microfluidic cancer models for clinical applications
			15.6.2 Microfluidic cancer models for industrial applications
		15.7 Conclusions
		Conflicts of interest
		References
	16 Perfusion-based 3D tumor-on-chip devices for anticancer drug testing
		Abbreviations
		16.1 Introduction
		16.2 Disadvantages of 2D in vitro, 3D in vitro, and animal models
		16.3 Microfluidic devices for tumor modeling
		16.4 Tumor components and their inclusion in tumor-on-chip
			16.4.1 Cells: monoculture/co-culture
			16.4.2 ECM: chemical and mechanical cues
			16.4.3 Growth factors
			16.4.4 Shear stress
		16.5 Types of perfusion methods
		16.6 Benefits of perfusion and specific applications
			16.6.1 Vasculature
			16.6.2 Multiorgan systems
			16.6.3 Interstitial flow within 3D hydrogel systems
			16.6.4 Drug pharmacokinetics and pharmacodynamics
		16.7 Specific designs for enhancing perfusion
		16.8 Conclusion
		References
	17 Engineering breast cancer models in vitro with 3D bioprinting
		17.1 Breast cancer microenvironment in vivo
			17.1.1 Types and stages of breast cancer
			17.1.2 Cancer cell behavior in vivo, microenvironment structure and mechanics
		17.2 Biomaterial-based breast cancer in vitro models
			17.2.1 Mammary morphogenesis in 3D
			17.2.2 Studies on cancer cell migration in 3D (metastasis models)
			17.2.3 3D spheroid and organoid invasion models
			17.2.4 3D models of heterotypic tumor–stromal interactions
		17.3 Biomaterials design for in vitro breast cancer models
			17.3.1 Natural, synthetic, and hybrid biomaterials
			17.3.2 Matrix stiffness, cross-linking, and network architecture
			17.3.3 Time-dependent and nonlinear mechanics
			17.3.4 Stimuli-responsive dynamic materials
			17.3.5 Biomaterial inks for 3D bioprinting
		17.4 3D bioprinting methods and their suitability for breast cancer in vitro engineering
			17.4.1 Microextrusion- and laser-induced forward transfer used in breast cancer research
			17.4.2 Volumetric and sacrificial bioprinting as future technologies in cancer research
			17.4.3 Bioprinting heterotypic cancer models for functional treatment modeling
		17.5 Discussion and outlook
			17.5.1 Evolution of breast cancer in vitro 3D models: from 2D culture to 3D bioprinting
			17.5.2 Advantages and challenges of 3D bioprinting in breast cancer research
			17.5.3 3D bioprinting in personalized breast cancer research and clinical treatment prognosis
		References
	18 A predictive oncology framework—modeling tumor proliferation using a FEM platform
		Chapter points
		18.1 Introduction
			18.1.1 A vision of feasible virtualized oncological prognoses
			18.1.2 An engineering approach toward predictive oncology
			18.1.3 The cancer liver: a valuable case study
		18.2 A perspective framework of predictive oncology
			18.2.1 Step 1: Acquisition of diagnostic images
			18.2.2 Step 2: Real 2 virtual image
				18.2.2.1 By using some open-source software
				18.2.2.2 By using some proprietary software
			18.2.3 Step 3: Mathematical formulation
				18.2.3.1 Level 0
				18.2.3.2 Level 1
				18.2.3.3 Level 2
			18.2.4 Step 4: Solution and postprocessing
			18.2.5 Step 5: Replication of the model
		18.3 Detailed model formulation using level 1 modeling
			18.3.1 The biological conversion logistics-based mechanisms
			18.3.2 Governing equations
			18.3.3 Initial conditions, proliferation, and therapy onset
			18.3.4 Boundary conditions
		18.4 A sensitivity analysis of hallmark parameters: results
			18.4.1 Numerical treatment
			18.4.2 Model validation: application to a hepatocellular carcinoma—Case 0
			18.4.3 Model application to different tumor growth rates—Cases 1 and 2
			18.4.4 Model application to different therapies—Cases 3 to 7
			18.4.5 Model application to different values of tumor and drug diffusivities—Cases 8 to 11
		18.5 POEM as a tool to empower the clinical decisions
		18.6 Conclusions
		Glossary
		References
III. Tumor models for drug discovery and therapeutics
	19 Tissue-engineered 3D cancer microenvironment for screening therapeutics
		19.1 Introduction
		19.2 Tumor microenvironment
			19.2.1 Cellular components
			19.2.2 Non-cellular components
		19.3 Current strategies for creating cell and matrix organization to mimic microenvironment
			19.3.1 Organoid derivation options (patient-derived organoid vs patient-derived xenograft)
			19.3.2 Transwell-based assays
			19.3.3 Organotypic model
			19.3.4 Microfluidic devices
			19.3.5 Micromolded 3D gels
			19.3.6 Multicellular spheroid
			19.3.7 Stacked paper models
			19.3.8 Cell sources used in tissue-engineered models
		19.4 Modeling important aspects of the tumor microenvironment
			19.4.1 In vitro models of tumor–fibroblast interactions
			19.4.2 In vitro models of tumor–immune interactions
			19.4.3 In vitro models of hypoxia and small molecular gradients
				19.4.3.1 Oxygen gradients
				19.4.3.2 Gradients of cytokines and other signaling factors
			19.4.4 In vitro models of tumor vasculature
		19.5 Future outlook
		References
	20 Three-dimensional tumor model and their implication in drug screening for tackling chemoresistance
		Abbreviations
		20.1 Chemoresistance in cancer
		20.2 3D tumor culture: an advanced model preferred over 2D culture
		20.3 3D culture and chemoresistance
			20.3.1 3D culture acts as a good model to study chemoresistance
			20.3.2 Importance of tumor microenvironment interaction in the development of chemoresistance
			20.3.3 Tumor heterogeneity and chemoresistance
		20.4 Methods of generating 3D culture system
			20.4.1 Methods of generating 3D organoids
			20.4.2 Methods of generating 3D spheroids
				20.4.2.1 Hanging drop model
				20.4.2.2 Nonadherent surface model
				20.4.2.3 Suspension culture model
				20.4.2.4 Scaffold-based model
				20.4.2.5 Magnetic levitation model
		20.5 3D culture and biomaterials
			20.5.1 Cell-derived or natural biomaterials
				20.5.1.1 Collagen
				20.5.1.2 Laminin-rich extracellular matrix
				20.5.1.3 Alginate matrix
				20.5.1.4 Chitosan matrix
				20.5.1.5 Silk
				20.5.1.6 Matrigel
				20.5.1.7 Hyaluronan-based hydrogel
			20.5.2 Synthetic biomaterials
				20.5.2.1 Polyethylene glycol-based hydrogel
				20.5.2.2 Polyethylene glycol-dextran aqueous two-phase system
				20.5.2.3 Polycaprolactone
				20.5.2.4 Poly(lactic-co-glycolic) acid
				20.5.2.5 Thermoresponsive hydrogels
		20.6 Drug screening in 3D culture
			20.6.1 Importance of organoids for developing personalized medicines
			20.6.2 Organoids in cancer medicine
			20.6.3 Patient-derived organoids used for cancer drug screening
		20.7 Future aspects of the 3D tumor organoid model: biobanks for tumor tissues
		20.8 Limitations of 3D culture technology
		20.9 Conclusion
		References
	21 Co-culture and 3D tumor models for drug/gene therapy testing
		21.1 Introduction
		21.2 Lung cancer
			21.2.1 Scaffold chemo/drug treatment
			21.2.2 Scaffold gene therapy
			21.2.3 Scaffold co-culture chemo/drug treatment
			21.2.4 Hydrogel chemo/drug treatment
			21.2.5 Hydrogel co-culture
		21.3 Breast cancer
			21.3.1 Scaffolds chemo/drug therapy
			21.3.2 Scaffolds gene therapy
			21.3.3 Scaffolds co-culture chemotherapy
			21.3.4 Hydrogels and chemo/drug therapy
			21.3.5 Hydrogels and gene therapy
		21.4 Prostate cancer
			21.4.1 Scaffold chemo/drug treatment
			21.4.2 Scaffold gene therapy
			21.4.3 Scaffold co-culture gene therapy
			21.4.4 Hydrogel chemo/drug treatment
			21.4.5 Hydrogel gene therapy
			21.4.6 Hydrogel co-culture chemo
		21.5 Future outlook
		References
	22 Newly emerged engineering of in vitro 3D tumor models using biomaterials for chemotherapy
		22.1 Introduction
		22.2 Constitution of artificially engineered tumor models
			22.2.1 Cells
			22.2.2 Materials
		22.3 Newly emerged engineering of in vitro 3D tumors for chemotherapy
			22.3.1 Microfluidic tumor models
				22.3.1.1 Fluid network for mimicking vasculature
				22.3.1.2 Easy and efficient set-up for massive drug screening
				22.3.1.3 “Organ-on-a-chip” for investigating organ-specific drug response
				22.3.1.4 Integration of multimicrochips for systemic drug toxicity evaluation
			22.3.2 Bioprinted 3D tumor models
		22.4 Summary
		References
	23 Marine-derived biomaterials for cancer treatment
		23.1 Introduction
		23.2 Marine biopolymers as bioactive agents
			23.2.1 Fucoidan
			23.2.2 Chitosan
		23.3 Drug-delivery systems
			23.3.1 Fucoidan-based systems
			23.3.2 Chitosan-based systems
			23.3.3 Carrageenan-based systems
			23.3.4 Alginate-based systems
		23.4 Three-dimensional in vitro models of cancer
			23.4.1 Chitosan-based cancer models
			23.4.2 Alginate-based cancer models
			23.4.3 Chitosan-alginate-based cancer models
		23.5 Conclusions
		References
	24 Mesoporous silica nanoparticles for cancer theranostic applications
		24.1 Introduction
		24.2 MSNs chemistry
		24.3 Biological effects of MSNs
		24.4 3D modeling of MSN for cancer therapy
			24.4.1 Hydrogels
			24.4.2 Electrospun nanofiber scaffolds
			24.4.3 3D-printed scaffolds
		24.5 Medical applications of MSNs
			24.5.1 Stimuli-responsive drug release
				24.5.1.1 pH-responsive
				24.5.1.2 Redox-responsive
				24.5.1.3 Light-responsive
				24.5.1.4 Magnetic field-responsive
			24.5.2 Targeted drug delivery
				24.5.2.1 Cell-membrane targeting
				24.5.2.2 Cell-cytoplasm targeting
			24.5.3 Other therapeutic strategies
				24.5.3.1 Phototherapy
				24.5.3.2 Ultrasound therapy
				24.5.3.3 Chemodynamic therapy
		24.6 Diagnostic application of MSNs
			24.6.1 Magnetic resonance imaging
			24.6.2 Fluorescent/luminescent imaging
			24.6.3 Positron emission tomography imaging
		24.7 Theranostics application of MSNs
		24.8 Conclusions and outlook
		References
IV. Point-of-care applications
	25 Causes of cancer: physical, chemical, biological carcinogens, and viruses
		Abbreviations
		25.1 Introduction
			25.1.1 How normal cells become cancerous?
			25.1.2 Stages of carcinogenesis
				25.1.2.1 Initiation
				25.1.2.2 Promotion
				25.1.2.3 Progression
			25.1.3 Carcinogens
		25.2 Physical carcinogens
			25.2.1 Mechanism of action of physical carcinogens
			25.2.2 Electromagnetic radiation
			25.2.3 Ionizing radiation
			25.2.4 Hard and soft materials
				25.2.4.1 Asbestos
				25.2.4.2 Erionite
				25.2.4.3 Nonfibrous particulate materials
				25.2.4.4 Air pollutants
				25.2.4.5 Gel materials
			25.2.5 Trauma
		25.3 Chemical carcinogens
			25.3.1 Mechanisms of chemical carcinogenesis
			25.3.2 Types of chemical carcinogens
				25.3.2.1 Aromatic amines
				25.3.2.2 N-Nitroso compounds
				25.3.2.3 Dyes
				25.3.2.4 Alkylating agents
				25.3.2.5 Natural carcinogens
				25.3.2.6 Inorganic carcinogenic agents
				25.3.2.7 Solvents and other compounds
		25.4 Biological carcinogens and viruses
			25.4.1 Mechanisms of biological carcinogenesis
			25.4.2 Viral carcinogens
				25.4.2.1 Epstein–Barr virus
				25.4.2.2 Hepatitis B virus
				25.4.2.3 Hepatitis C virus
				25.4.2.4 Kaposi sarcoma herpesvirus
				25.4.2.5 Human immunodeficiency virus-1
				25.4.2.6 Human papillomavirus
				25.4.2.7 Human T-cell lymphotropic virus type-1
			25.4.3 Bacterial carcinogens
				25.4.3.1 Helicobacter pylori
			25.4.4 Protozoal carcinogens
				25.4.4.1 Opisthorchis viverrini and Clonorchis sinensis
				25.4.4.2 Schistosoma haematobium
			25.4.5 Other biological carcinogens
		25.5 Conclusion
		References
	26 Biodetection and sensing for cancer diagnostics
		26.1 Introduction
		26.2 Biomarkers for cancer detection
			26.2.1 Protein biomarkers
			26.2.2 Circulating tumor cells
			26.2.3 MicroRNAs
			26.2.4 Circulating tumor DNA
			26.2.5 Biomarker panels
		26.3 Cancer biosensors
			26.3.1 Electrochemical biosensors
			26.3.2 Optical biosensors
			26.3.3 Piezoelectric biosensors
		26.4 Commercialization and clinical trials of cancer biosensors
		26.5 Conclusions
		References
	27 Understanding the impact of controlled oxygen delivery to 3D cancer cell culture
		27.1 Introduction
		27.2 What is known about physiological oxygen levels?
			27.2.1 Normoxia versus physoxia
			27.2.2 Hypoxia (physiological vs pathological)
			27.2.3 Tumor hypoxia
		27.3 Importance of oxygen levels in various stages of cancer progression
			27.3.1 Hypoxia
			27.3.2 Angiogenesis
			27.3.3 Metastasis
		27.4 Techniques for measuring oxygenation
			27.4.1 Oxygen-sensing electrodes
			27.4.2 Biologic and synthetic absorptiometric probes
			27.4.3 Fluorescent and phosphorescent luminescent probes
			27.4.4 Spectroscopic imaging: magnetic, paramagnetic, and electron spin resonance
		27.5 Traditional/current strategies for controlling oxygen concentration in vitro
			27.5.1 Hypoxia chambers and two-dimensional models
			27.5.2 Three-dimensional models: spheroids
			27.5.3 Other strategies for controlling oxygen delivery in 3D: lab-on-chip systems, bioreactors
		27.6 Characterizing the effects of oxygenation on cells and tissues
			27.6.1 RNA-Seq
			27.6.2 qPCR of downstream targets
			27.6.3 Pimonidazole staining
			27.6.4 Real-time imaging of growth
			27.6.5 Metabolic characterization and imaging
			27.6.6 In vivo metabolic imaging
			27.6.7 In vitro metabolic imaging
		27.7 Conclusions and future prospects
		References
	28 Tissue engineering strategies for the treatment of skeletal maxillofacial defects resulting from neoplasms resections
		28.1 Background
			28.1.1 Oral and maxillofacial neoplasms
				28.1.1.1 Myxoma
				28.1.1.2 Ameloblastoma
				28.1.1.3 Odontoma
				28.1.1.4 Odontogenic keratocyst
				28.1.1.5 Central giant cells granuloma
			28.1.2 Currently used therapies
		28.2 Tissue engineering for reconstruction of ablated skeletal maxillofacial tissues
			28.2.1 Scaffolds
				28.2.1.1 Inorganic materials
				28.2.1.2 Synthetic polymeric materials
				28.2.1.3 Natural polymers
			28.2.2 Cells
				28.2.2.1 Mesenchymal stem cells
					28.2.2.1.1 Bone marrow derived stem cells
					28.2.2.1.2 Periosteal-derived progenitor cells
					28.2.2.1.3 Adipose tissue-derived stem cells
					28.2.2.1.4 Dental pulp stem cells
					28.2.2.1.5 Co-cultures
			28.2.3 Biochemical cues
			28.2.4 Bioreactors
			28.2.5 Prophylactic tissue engineering constructs
		28.3 Future perspectives and unmet challenges
		References
Index
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