The third dimension of tumor microenvironment—The importance of tumor stroma in 3D cancer models

Abstract

Recent advances in the three-dimensional (3D) cancer models give rise to a plethora of new possibilities in the development of anti-cancer drug therapies and bring us closer to personalized medicine. Three-dimensional models are undoubtedly more authentic than traditional two-dimensional (2D) cell cultures. Nowadays, they are becoming preferentially used in most cancer research fields due to their more accurate biomimetic characteristics. On the contrary, they still lack the cellular and matrix complexity of the native tumor microenvironment (TME). This review focuses on the description of existing 3D models, the incorporation of TME and fluidics into these models, and their perspective in the future research. It is clear that such an improvement would need not only biological but also technical progress. Therefore, the modern approach to anti-cancer drug discovery should involve various fields.

Keywords

3D models cancer research tumor microenvironment tumor stroma organoids 3D bioprinting

Impact Statement

This review provides insights into the field of three-dimensional (3D) in vitro models and their use in cancer research and therapies development. A special focus is put on the incorporation of the tumor microenvironment and non-cancerous cells in such models as a crucial part of tumorigenesis. Tumor microenvironment has been recognized as a hallmark of cancer. Therefore, ignoring its role in cancer development and progression in in vitro models means that they cannot provide a fully relevant platform for basic and translational cancer research, nor for anti-cancer drug development. The authors are discussing whether current 3D tissue models are capable of replicating all aspects of cancer biology and the directions which should be taken in developing them further into relevant in vitro platforms fully mimicking the tumor–stroma interactions as in native tumor tissue.

Introduction

Cancer is a major public health problem and one of the leading causes of death across the world with increasing incidence every year.¹ Despite decades of research on novel therapeutics, multiple tumors, such as glioblastoma, pancreatic cancer, and triple-negative breast cancer, still have limited clinical treatment options. Only about 10% of potential anti-cancer drugs succeed during their clinical testing.² Many of them are failing due to the disparities between results obtained in preclinical studies and outcomes in clinical settings. One of the main reasons behind this obstacle is the use of preclinical models that lack the ability to authentically represent all conditions and physiological processes in the human body.

There is a long journey before an anti-cancer drug progresses from laboratory to clinical testing stage. Usually, the initial in vitro studies are followed by the animal experiments—frequently on more than one animal species. However, there are many reasons that put a pressure on the need to use appropriate human in vitro models to their maximum potential. Those reasons include ethical problems of animal experimentation, legislative ones—such as 3Rs rules (Replacement, Reduction, and Refinement of the inclusion of animals in research) as well as cost. Yet another important set of factors that causes disconnection between preclinical and clinical stages are interspecies differences. Therefore, many of the promising therapies successfully tested on animals often fail when it comes to human treatment.

A very important step in improving and/or streamlining the preclinical stage is the newly published US Food and Drug Administration (FDA) decision from early 2023 that makes animal testing non-mandatory before human trials.³ This law doesn’t ban the testing of new drugs on animals outright because of the many limitations of in vitro systems. Companies simply cannot switch from animals to in vitro systems that might not be able to capture all of the types of toxicities, such as systemic effects. This decision simply creates possibilities to avoid animal testing in areas where suitable models and methods exist or will be created in the future. Therefore, this puts even more possibilities and pressure on the development of accurate in vitro models.

Unfortunately, much of the in vitro cancer research is still performed on two-dimensional (2D) cell cultures. While it is a straightforward approach with low-cost maintenance, these two factors may be also the only advantages of such approach nowadays.⁴ Limitations of using 2D in vitro models have been described many times proving their inadequacy as fully reliable preclinical cancer models that fail to address many pathological aspects.^2,5,6 For example, it has been reported that 2D cultures of healthy cells do not conserve the original shape and polarization of the cells,⁷ which could affect many properties through non-physiological cell signaling, even though the loss of cancer cells’ polarity is often observed.⁸ Cell cultures growing in monolayers on the plastic dishes also do not have proper spatial interactions with other cell types that are normally present in the native tissues. Lack of such intercellular communication, in turn, results in further skewing of not only signaling but also transport of nutrients and other molecules, including the therapeutic ones. There is no doubt about the contributions of 2D cultures in cancer biology, but to move forward more deeply into the problems that are not solved yet, they are simply not enough. On the contrary, the internal environment of animal models has a limited ability to mimic the complex process of pathophysiological conditions in humans. This may, according to Mak et al.,⁹ lead to a low rate of successful translation from animal models to clinical trials, which is at present not more than 8%. There is no doubt that animal models contributed greatly to many important discoveries, but still, most of the promising therapies successfully tested on animals fail when it comes to human treatment.

Since Mina Bissell with her colleagues pointed out the importance of the extracellular matrix (ECM) in the cell biology,^10–13 three-dimensional (3D) cell culture models are generally accepted as more accurate cancer research models than the 2D models that have been in use by then, since they allow studying not only the tumor cells but also to include various components of their microenvironment. The tumor microenvironment (TME) has an inseparable role in processes such as tumor proliferation, dissemination, immune evasion, angiogenesis, epigenetics, and many others associated with cancer progression. The composition of the TME varies between tumor types, but hallmark features include the presence of non-malignant epithelial cells, immune cells, stromal cells, blood and lymphatic vessels, microbiome, and ECM.^14,15 All of these types of cells interact with cancer cells, each other, and also with ECM by secreting different types of molecules, such as cytokines, chemokines, extracellular vesicles, and miRNA. All these direct cell-to-cell interactions together with indirect communication through secreted molecules can influence various signaling pathways that help cancer cells to proliferate, migrate, and spread throughout the organism.¹⁶ Therefore, an appropriate cancer model should be able to recapitulate all the aspects of the TME and its interactions with tumor, in order to properly study crucial cancer-related processes.

In the future, bioengineered humanized 3D models of tumors could eventually replace the requirement for testing on animals. In fact, it would be a desirable outcome for all the aforementioned ethical and even more importantly biological reasons. The development of such models would provide great ethical and economic benefits for the prediction of tumor response to treatment (e.g. chemotherapy, radiotherapy), and reduce the number of animals sacrificed in preclinical studies. Below, we discuss the currently available 3D in vitro models including the tumor cells with their TME and bring insight into the future of drug testing in oncology.

Spheroids

Multicellular tumor spheroids are considered to be the first and also simplest 3D in vitro model frequently used in cancer research.¹⁷ Spheroids are defined as cellular aggregates obtained in suspension or embedded within 3D matrix.¹⁸ In general, spheroids can be described as rounded clusters of cancer cells (usually cancer cell lines) grown on low-attachment or agarose-coated culture plates. Spheroid media are usually non-defined and serum-containing media. Another approach is a “hanging drop” technique, where the cells are cultured in a drop of culture medium hanging on the lid of Petri dishes and incubated under physiological conditions until they create 3D structures.¹⁹ The 3D formation allows cancer cells to be in close proximity to one another and form a “mass,” which provides great conditions for the accumulation of cell-generated collagen.²⁰ In majority of current models, spheroids are embedded in a gel²¹ or encapsulated into the alginate shells²² to more accurately recapitulate TME architecture in an ECM (different types of gels and scaffolds are discussed below). However, within spheroid formations, significant aspects of the tumor environment are not replicated because of the lack of stromal cells and their associated effects. On the contrary, there is a possibility to co-culture spheroids with immune cells,^23,24 stromal cells,²⁵ or even both as a triple co-culture²⁶ in order to increase the validity of the model. There is even an option to co-culture spheroids with the tumor-colonizing bacteria,²⁷ which are an important part of the environment, especially in colorectal tumors. This strategy would be a promising one to study such modalities as microbial cancer therapies, which are lately occurring, thanks to the ability to combine the discovery of tumor-colonizing bacteria with advances in synthetic biology.

Undisputable advantage of spheroid models is their ability to simulate oxygen gradient. In the tumor, the abnormal vasculature leads to the defects in mass transport, especially in the case of oxygen.²⁸ This usually causes a formation of a necrotic core consisting of dead cancer cells due to an inadequate oxygen supply. As a result, creation of hypoxic regions occurs and these are present in the majority of solid tumors. The cancer cells on the periphery of the spheroid have, on the contrary, higher access to the nutrients and oxygen. The availability of oxygen in the spheroids is critical for metabolism and to the responsiveness to drug treatments.²⁹ Hypoxic cells usually switch to a glycolytic metabolism, which increases glucose uptake, decreases oxygen consumption, and alters the pH of the microenvironment.³⁰ The formation of a microenvironment within spheroid is determined by the balance between oxygen diffusion from the growth medium and its consumption by cells within the spheroid. In 2016, a simple non-invasive technique was modified for the quantitative measurement and subsequent evaluation of oxygen gradients in spheroids using electron paramagnetic resonance (EPR) oximetry.²⁹ Therefore, tumor spheroids can be used to model some characteristics of avascular tumors or micro-metastases of large solid tumors. In addition, this method enables to better replicate the barrier for drug penetration and thus allows to study the drug/therapeutics delivery in the pathophysiological context of the native tumor tissue.

The main benefits of spheroids are their low cost, high throughput, reproducibility, and ease of use,³¹ but they are still not considered to be an ideal model for cancer therapies testing.

Tumor organoids

Tumor heterogeneity is known to be the major problem in the development of effective patient-specific therapies. Diverse tumor phenotypes usually change with the progression of disease and also as a reaction to different types of treatment. In addition to the intratumor heterogeneity, there is also a divergency across the patients that explains various patient-specific therapeutic responses³² (Figure 1). Therefore, spheroids that are usually formed from cancer cell lines cannot provide sufficient conditions to circumvent this problem. The development of successful personalized therapies relies on the ability of laboratory models to accurately recapitulate not only microenvironment but also the heterogeneity of a given tumor. In the last few years, 3D organoid cultures established from patient tumor tissues are considered to become relatively representative model preserving the heterogeneity of the tissue and allowing the interactions with the TME.³³ It began in 2009, when Sato et al. established 3D epithelial organoids from a single leucine-rich repeat-containing G protein-coupled receptor 5 (LGR5) + intestinal stem cell. These highly polarized epithelial structures with proliferative crypt and differentiated villus compartments grow embedded in the Matrigel^TM in a serum-free medium with several growth factors and inhibitors.³⁴ In the same year, Kuo’s laboratory introduced different organoid culture system using an air–liquid interface (ALI) with stromal support cells as a source of essential growth factors³⁵ that simplified used culture medium.

Figure 1.

Tumor organoids established from patients’ tumor tissue represent inter- and intra-tumor heterogeneity. The hypoxic gradient is created similarly as in native tumors, once they reach a certain size. There is an opportunity to incorporate a tumor microenvironment, use the samples for biobanking, and drug screening, or incorporate them in bioreactors. Created with BioRender.com.

Subsequently, organoids culture protocol for other epithelial tissues, of mouse as well as human origin, were published following a great number of protocols for organoids establishment from tumor tissue and created so-called “living biobanks” (reviewed in LeSavage et al.³⁶). Each tumor has unique composition on cellular and environmental level, which contributes to the heterogeneity within and across tumors. Many publications showed that organoid models could accurately recapitulate this biological heterogeneity and maintain phenotypic and genetic characteristics of original tumor epithelium. Moreover, tumor organoid cultures seem to be suitable for modeling the TME heterogeneity and cell interactions using co-culture with different type of cells, such as cancer-associated fibroblasts (CAFs)^37,38 or immune cells.^39,40 As mentioned above, hypoxia, which greatly contributes to malignant behavior and chemo- and radio-resistance, does develop in organoids once they reach a certain size.⁴¹ Therefore, tumor organoids established from primary tumors as well as from metastatic tissues have become a promising and eligible high-throughput platform for patient-specific testing.

Despite all the promising features mentioned above, organoids, as all other existing preclinical models, have their own limitations. The main disadvantage is the lack of standardized culture protocol. There is a great technical variability across the tumor organoid studies, including non-standardized tissue sources, variable protocols for their processing, different types of media formulation, and the use of heterogeneous animal-derived 3D matrices that are not able to properly mimic native tumor ECM.³⁶ It was shown that tumor organoids often grow slower than their matching normal organoid counterparts due to the higher rates of mitotic failures and subsequent cell death.⁴² Unfortunately, there is a great chance of the overgrowth of healthy epithelial tissue organoids derived from normal tissue in tumor biopsies.³³ This could be avoided by removing as much normal tissue as possible from tumor biopsies by skilled pathologist or by using selective culture medium. For example, tumors with mutations in the epidermal growth factor receptor (EGFR) signaling pathway can be selected by EGF withdrawal.⁴³ Another obstacle is linked to the efficacy of organoid derivation and subsequent in vitro expansion. There is a great deal of evidence that many tumor types have an efficacy of organoid derivation higher than 80%, but for some of them, for example non-small lung cancer⁴⁴, it is extremely low and unpredictable. Another major pitfall is the fact that the derivation time of most cancer organoids is currently weeks to months, which is unacceptable if they are supposed to be utilized as a tool of personalized medicine. Derivation time might be shortened if they were used as co-clinical models. This would have added value for the patient treatment setting.

Overall, given the great potential of cancer organoids to accurately recapitulate the intra- and inter-tumoral heterogeneity associated with patient-specific cancers, elimination of the technical variability in all steps of organoid derivation and in vitro expansion is necessary to establish reproducible robust platforms that can be translated into the patient care.

Assembloids

To look a little bit further into the future, organoids generated by spatially organizing multiple cell types, so-called assembloids, could allow more profound insight into the different processes and functions of the various types of tissues. One of such approaches, a simple mixing of different cell types into the organoid structures, was previously used, for example, to create brain organoids with vasculature-like structures.⁴⁵ These vascularized human cortical organoids acquired several blood–brain barrier characteristics, such as an increased expression of tight junctions, nutrient transporters, and trans-endothelial electrical resistance. Assembloids might help to look deeper into multiple biological processes and therefore be useful in research of several different complex diseases, including cancer. Even though aggregating different cell types into organoids is technically possible, it is hardly a model with defined spatial organization. This requires a much more advanced approach than just creating an organoid from a simple mixture of cell types. As an example, neuronal migration during development is a spatially organized process, which is not easy to recapitulate in vitro. Recently, a partial progress was made in this area when the researchers managed to create a model by fusing brain organoids of different regional identities. Moreover, they observed migration of interneurons from ventral to dorsal forebrain regions within the assembloids (shortly reviewed in Vogt⁴⁶).

Speaking of cancer research, only a few laboratories have succeeded to create a useful model of tumor assembloids yet. Multilayer bladder assembloids were developed by reconstituting tissue stem cells with stromal components to represent an organized architecture with an epithelium surrounding stroma and an outer muscle layer. Malignant tumor counterparts to these assembloids were developed to recapitulate the in vivo pathophysiological features of urothelial carcinoma. Here, they used connection of organoids with a connective tissue layer (patient-derived CAFs and endothelial HULECs), and the outer muscle layer (induced pluripotent stem cell (iPSC)-derived smooth muscle cells).⁴⁷ Pancreatic ductal adenocarcinoma (PDAC) assembloids were established from PDAC organoids, endothelial cells, and autologous immune cells to study cancer cell plasticity. In PDAC, the ability of tumor cells to dynamically switch between cancer-initiating and non-initiating cell states has been suggested as a reason for poor drug efficacy. Classic organoid model fails to recreate such cancer cells’ plasticity but assembloids containing plasticity-inducing endothelial and immune cells can. This model allowed to identify JAG1 as an essential player in this process and as a potential therapeutic target.⁴⁸

To reflect the complexity of processes in the human tissues, the complexity of organoids must be increased and assembloids are considered to be the nearest next step in this long journey. Different approaches in their assembly should be mixed and used to create highly complex, tissue-mimetic organoid models that could serve as very realistic laboratory models. These could be applied for studying the basic biology of human tissues and organs as well as for studying pathological processes.

Bioreactors

In the last few years, bioreactors and various types of flow systems have become indispensable tools in cell-based therapy research. They are used to maintain microenvironment and regulate cell growth, differentiation or tissue development, and therefore, are essential for providing standardized cell-based products for in vitro testing of various treatment agents. The bioreactors could be divided into three major groups: cell expansion bioreactors, tissue engineering bioreactors, and lab-on-a-chip systems.⁴⁹ There are a great number of companies with different modifications and improvements of bioreactors and microfluidic systems. Many of them are widely used in cancer research.

Microfluidics has greatly improved our ability to mimic the natural biophysical and chemical conditions of cell cultivation under in vitro conditions. There are different types of microfluidic platforms, so-called organ-on-chip or lab-on-chip, or in case of cancer tumor-on-chip devices, that can model several physiological functions of tissues and organs. These platforms combine the advantages of microfluidic technology and 3D cell culture models with improved recapitulation of the native microenvironment.⁵⁰ They allow performing high-throughput tests with decreased cost because of the usage of microscale volumes; they have the same ethical advantages as other in vitro systems with added bonus of enhanced reproducibility.⁵⁰ Their main advantage is the ability to modify and control various parameters independently—from the types and localization of cells or the orientation of tissue interface, to application of mechanical forces or chemical gradients.⁵¹ Last but not least, the microfluidic channels allow the combining of different types of tissues into logical units, thus simulating the relationships between different distant organs and/or tissues.

Microfluidic chips are usually fabricated by technique called “soft lithography”—method, where the desired patterning is printed on silicon wafers by photolithography, followed by replica molding of the silicon wafer with a liquid polymer, usually polydimethylsiloxane (PDMS).^50,51 PDMS is commonly used because of its numerous positive features such as, low price, gas-permeability, and transparency, allowing a high-resolution optical imaging.⁵² On the contrary, the main disadvantage of this material is the unspecific absorption of small molecules,^52,53 which is the main demand for the intensive search for a new material to replace PDMS in the manufacture of biochips. Other approaches for microchip fabrication include micromolding, microetching, laser etching, injection molding, photopolymerization, and 3D printing.⁵¹ Fabrication method depends on the specific microchip application.

Most microfluidics platforms designed for cancer research are coated with ECM or even involve scaffold-based materials to better mimic the native TME. Multiple cell types can be cultured in a microfluidic device to analyze specific interactions between cancer cells and their stroma.^54–56 For example, ECM remodeling is a typical consequence of tumor–stroma communication and subsequent activation, necessary for cancer progression. A model allowing to study this process was constructed by combining fibroblast-assembled ECM, mimicking a stromal compartment, and breast cancer cells (Figure 2, left). Authors observed that invasion of cancer cells led to the activation of CAFs and overexpression of both fibronectin and hyaluronic acid in the ECM.⁵⁷ Therefore, this is very unique in vitro platform allowing monitoring of the key factors in the switch between healthy and pathological stroma in cancer.

Figure 2.

Schematic presentation of different approaches of lab-on-chip devices in cancer research: ECM remodeling processes, microvasculature-related processes such as angiogenesis or metastasis, and TME incorporation for different fields of cancer research. Created with BioRender.com.

Even more innovative models than a standard co-culture of cell lines in fluidic devices have recently been developed. Microfluidic chip systems combined with organoid models, called organoids-on-chip, combine benefits of both innovative approaches in cancer research and allow us to study tumor heterogeneity and tumor–stroma interaction on a much different level. For instance, a state-of-the-art multicellular chip device was engineered to mimic the PDAC TME by using patient-derived organoids (PDOs), pancreatic stellate cells, and macrophages (Figure 2, right). This tissue-chip model improved long-term cell survival of primary PDOs and significantly increased the chemotherapy effect on cancer cells, thus validating the use of the device for drug testing.⁵⁸ In addition, their system allows extending its complexity by incorporating vasculature and multiple types of immune cells.

Furthermore, the microfluidic chip devices incorporating a microvascular compartment have been developed to recapitulate the crucial features of tumors, such as tumor angiogenesis and metastasis.⁵⁹ This self-assembly microvascular approach can be used to reconstruct tumor angiogenesis and vasculature for analysis of patient-derived tumor cellular behavior and drug testing, or metastatic cascade where extravasation of tumor cells plays a crucial role (reviewed in Lim et al.⁶⁰). Also, in this case, multiplex microfluidic systems combining microvasculature and organoids have been developed (Figure 2, middle). The microvascularized 3D tissues retain their functions representing the original in vivo tissues. For example, there is a platform, where a central feature is a quiescent perfused 3D microvascular network created prior to loading of breast patient-derived tumor organoids in an adjacent compartment, which provides the opportunity to simultaneously and dynamically observe hallmark features of tumor progression, including cell proliferation, angiogenesis, cell migration, and tumor cell intravasation. Moreover, organoids are viable for several weeks and induce robust sprouting of angiogenesis.⁶¹ Another research team combined PDAC organoids, human fibroblasts, and endothelial cells with the bio-scaffold that mimics perfusable vascularized vessels. Remodeling of tumor stiffness through myofibroblast contraction and collagen deposition was observed as well as decreased efficacy of a drug applied through the vasculature when compared with static organoid culture.⁶²

Modern approaches using combination of patient-derived tumor organoids and vasculature on microchip devices are the key to better understanding of cancer biology obstacles mentioned in this review. Representation of an “in vivo-like microenvironment” using platforms like these allows the development of new anti-cancer therapeutics and biological studies. As mentioned above the technology still has many imperfections and we are certainly not at the end of a journey. However, the number of options these technologies open for studying physiologically relevant interactions between different cell types (between tumor and TME), as well as the new ways to examine mechanisms of actions of candidate drugs in such constructs are certainly exciting. Further improvements of the limitations mentioned above should lead to increased efficiency of the preclinical stage of drug development and eventually to true customized patient-specific therapy.

Extracellular matrix, hydrogels, and scaffolds

As mentioned above, the 3D in vitro models were developed to recapitulate, at least partially, the complex architecture of real tissue/organ in a “Petri dish.” The principal environmental factors such as ECM composition affect greatly with the tumor development and metastasis. For instance, the ECM is directly involved in the regulation of tumor stemness properties, epithelial-to-mesenchymal transition (EMT), or drug response.^63–65 In fact, the ECM composition changes with tumor progression. Higher concentration of some proteins, including laminin, fibronectin, or fibrillar collagens, is responsible for alterations in the ECM architecture and mechanical and physicochemical properties underlining the key role of ECM in tumor biology.^66–69

The organoids establishment usually requires animal-derived ECM, which is commercially known under different names (e.g. Cultrex^® or Matrigel^TM). It has been considered a “gold standard” due to the spontaneous crosslinking at physiological temperature and biomolecular composition; it is derived from Engelbreth-Holm-Swarm mouse sarcoma tumors. This type of matrix is composed of a mixture of various basement membrane components, including laminin-1, collagen IV, entactin, heparan sulfate proteoglycans, and growth factors, and thus shows batch-to-batch variability in their composition. Apart from the remarkable tumor stroma mimicking characteristics and tissue-like physical features, usage of heterogeneous native ECM-obtained matrices generates discrepancies in organoid culture protocols and reduces the reproducibility and clinical compatibility by generating structures with variable cell-type composition, shape, and size. Therefore, enormous efforts have been put to develop bio-inspired products that might replace them and help to standardize the cultivation protocol and allow high-throughput screening.^70–72

Hydrogels have emerged as novel supporting materials for 3D cell culture. They are able to form 3D polymeric networks and absorb and retain over 20% of their mass in water or other biological fluids.⁷³ In parameters such as viscoelasticity, mechanical features, and bioactivity, the hydrogels are akin to the native tissue ECM. Noteworthy, their microarchitecture (pore shape and size, fiber length, specific distribution of mechanical signals and motifs involved in cell adhesion, and chemical structure) allows them to be modeled to mimic the adequate microenvironments for cancer cells expansion as well as 3D culture development.^74,75

Hydrogels are formed through physical and chemical crosslinking. In general, they are categorized according to their polymer composition. As an example, collagen, fibrin, gelatin, hyaluronic acid, and decellularized organ-derived ECM belong to natural hydrogels and are well known for their outstanding biocompatibility and bioactivity. These materials include native cell-binding epitopes (e.g. RGD motif) as well as degradation motifs for proteases that can cause uncontrolled hydrogel digestion. Moreover, the batch-to-batch variation of their natural sources may impair the hydrogels’ biochemical and biophysical tunability.^76–79 Type I collagen hydrogels are frequently used as supportive scaffolds for growing cancer stem cells (CSCs), spheroids, and organoids. Some of the greatest benefits of collagen hydrogels are their ability to sustain the broad spectrum of linear elastic moduli (10–200 kPa), allowing the 3D culture to be treated with several different mechanical stimuli.⁸⁰ It was reported that human osteosarcoma and breast tumor spheroids, embedded in controlled pore size collagen hydrogels, can grow more efficiently, when the stiffness of the supporting matrix mimics authentically the cancer cell niche. Osteosarcoma spheroids proliferate more efficiently in stiffer hydrogels, while breast spheroids grow bigger in softer hydrogels. In addition, the breast cancer spheroids, grown in a proper mechanical environment, show ability to predict the in vivo response to chemotherapy more accurately.²¹

Synthetic hydrogels based on polyacrylamide, polyethylene glycol (PEG), poly lactic acid (PLA), poly(lactic-co-glycolic acid) (PLGA), polycaprolactone (PCL), or polyurethane (PU) are commonly used as a scaffolds for tissue engineering. Their physicochemical characteristics are associated with lower batch-to-batch variance, higher stiffness, and tunability compared with hydrogels derived from natural sources. To fine-tune their features, the techniques for adjusting the polymer backbones and molecular weights of synthetic hydrogels are frequently used. Nonetheless, these hydrogels do not provide inherent principal biological stimuli and need to be conjugated with bioactive motifs and/or molecules (e.g. GFOGER, RGD, fibrinogen, and fibronectin) that mediate their biocompatibility.^81,82

Semi-synthetic hydrogels, such as methacrylated hyaluronic acid (HAMA) or gelatin methacryloyl (GelMA), are formed by incorporation of crosslinking sites into the backbone of a natural polymer.^83–85 These sites equip the semi-synthetic hydrogels with a stability and tunability that is lacking in natural hydrogels. Semi-synthetic hydrogels maintain biocompatibility and bioactive features to some extent since they are natural polymers derivates.^86,87 The efficiency of GelMA hydrogels were tested in studying the invasiveness of breast cancer cells. GelMA hydrogels with stiffness of 4.8 kPa enabled MDA-MB-231 cells to form spheroids having an upregulated expression of stemness-related genes. Upon 5-day cultivation, cancer cells migrated out of the 3D spheroid structure showing an increased expression of genes involved in the breast cancer invasiveness compared to spheroids established under the standard scaffold-free and low-attachment conditions. In addition, GelMA hydrogels-embedded cancer cells exhibited enhanced tumorigenic ability in vivo. Six weeks after their intravenous injection, the tumor nodules could be identified in lungs and in the thoracic cavity. Such an invasive behavior was not observed in tumors generated from cells grown in 2D monolayers.⁸⁸

Therefore, ongoing extensive development of advanced hydrogels that lead to the generation of multifactorial tissue-specific signals, and the validation of the reliability of specific composite hydrogels for 3D cultures will be crucial to make practical differences across numerous downstream applications in the near future.

Three-dimensional bioprinting

Thanks to the development of laser technology, computer-aided design techniques, and digital microelectronic devices, 3D printing has developed significantly in recent decades. The ultimate goal of this technology is to provide tools or approaches capable to create 3D constructs with a structure and composition similar to native tissue and involve sophisticated patterning of the ECM, biomolecules, and even cells to study biological processes or create living structures/tissues.⁸⁹

These technologies could further bridge the space between 2D cell cultures and animal models. Although, in vitro and in vivo models are gold standard and indispensable in preliminary tests for safety, efficacy, and cytotoxicity, as mentioned above, those traditional models have many limitations, with the high costs and ethical concerns being just the basic ones.⁹⁰

As stated before, the leaps made in the development of 3D cultivation greatly improved the ability of in vitro models to reproduce in vivo situation. However, achieving proper spatial organization within these structures is still a major pitfall; an internal architecture of many of them can still be considered unorganized.⁹¹

The 3D bioprinting techniques may be just a tool that is needed here. A 3D-printed construct can have a defined architecture and mechanics modulated by individual fibers’ orientation, density, and arrangement.^92,93 These can also be modified in different ways to create multiple layers with different porosity and nutrient supply to support the cell migration, proliferation, and differentiation in the construct. Because of the possibility of easy customization, which could be a part of personalized medicine, the product could be tailored to a specific patient.⁹⁴

The birth of 3D printing is dated back to 1984 when stereolithography (SLA) was invented, printing 3D objects from digital data.⁹⁵ The first bioprinting was carried out in 1988 using a standard inkjet printer.⁹⁶ Since that time, thanks to advances in both material science and technology, many bioprinting products have been introduced. In 2002, the first extrusion-based bioprinter, a predecessor of the later commercialized 3D-bioplotter, was presented.⁹⁷ Since that year, many printers have been developed and delivered, such as the first ink-jet bioprinter, commercial SLA printer,⁹⁸ or integrated tissue-organ printer.⁹⁹ Various procedures have created many different constructs such as the first 3D tissue with only cells (not scaffold),¹⁰⁰ scaffold-free vascular construct,¹⁰¹ 3D printed tubular structure,¹⁰² cartilage model, bioprinted cardioid structure, and collagen human heart,^103,104 skin,¹⁰⁵ nerve,¹⁰⁶ bone,^107,108 cartilage^109,110 and so on.

The biggest challenge in producing a 3D bioprinted cancer model is to imitate the TME as faithfully as possible. Such complexity of the TME in vivo cannot be simulated using 2D monolayer cultivation or 3D co-cultivation models. It was proven in a study by Herrores-Pomres et al.,¹¹¹ where they compared 2D culture and three different 3D printed platforms, rigid scaffold, hydrogel-based scaffold, and suspension spheroid culture enriched in CSCs from non-small-cell lung carcinoma. They observed different proliferation profiles of cancer cell lines and primary cancer cells on various scaffolds. Also, gene expression analysis confirmed that tumor spheres and cells seeded on hydrogel scaffolds significantly overexpress most of the stemness and invasive promoters tested compared to control cells grown in 2D culture. Their findings provide strong evidence of advantages of 3D-printed models, especially hydrogels as the primary scaffold material for studying CSCs, due to mimicking tumor complexity and regulating cancer cell behavior. Similarly, another scientific team compared cell proliferation, matrix metalloproteinase (MMP) protein expression, and chemoresistance in the printed 3D cervical tumor models and conventional 2D planar culture models,¹¹² where HeLa cells showed a higher proliferation rate in the bioprinted 3D environment and tended to form cellular spheroids, but in 2D culture they formed monolayer cell sheets. HeLa cells in 3D printed models also displayed higher MMP protein expression and chemoresistance than in the 2D culture.¹¹² Also, 3D bioprinted osteosarcoma model (3DBPO), containing osteosarcoma cells and photo-cross-linkable bioinks composed of gelatine methacrylamide and hyaluronic acid methacrylate, was compared with 2D models and tumor spheroids. The 3DBPO model showed significant changes in cell cycle, metabolism, adherens junctions, and other pathways associated with epigenetic regulation and was also more sensitive to therapies targeted to the autophagy pathway.¹¹³ Currently, the studies involving 3D bioprinted tumor models are trending massively, as evidenced by the great number of works reporting the preparation of 3D models of various malignancies such as malignant melanoma,¹¹⁴ multiple myeloma,¹¹⁵ ovarian cancer,¹¹⁶ brain tumor,¹¹⁷ breast cancer,¹¹⁸ and urological carcinomas.¹¹⁹

Three-dimensional bioprinting techniques can also be used to study the metastatic process. Holzapfel et al.¹²⁰ aimed to engineer a morphologically and functionally intact humanized organ bone that could serve as a homing site for human prostate cancer (PCa) cells. Human mesenchymal progenitor cells were seeded on the bone structure, and recombinant human bone morphogenetic protein-7 (rhBMP-7) growth factor was used to induce the metabolic activity and production of ECM components. Upon further culture, the PCa cells demonstrated a preference for the engineered bone constructs, proliferated, and developed macro-metastases. Similarly, a microtissue model of osteoblastic bone metastases was prepared using cultured primary human osteoprogenitor cells on a polymer scaffold and created a mineralized osteoblast-derived microtissue containing viable osteoblastic cells, osteocytic cells, and appropriate expression of osteoblast-/osteocyte-derived mRNA and proteins and mineral content.¹²¹ Co-cultured cancer cells showed increased affinity to the microtissue, upregulation of alkaline phosphatase and collagen-I, and sclerostin downregulation, consistent with the clinical marker profile of osteoblastic bone metastases.¹²¹

The knowledge/understanding gained from the systematic and methodological study of the complexity and dynamics of the TME using 3D bioprinted constructs can speed up the translation of research into clinical practice by accelerating the drug development process, reducing costs, saving resources, limiting animal testing, or providing a higher level of personalization. There are still some challenges discussed here that must be overcome before we are able to translate research into clinical practice, but these advances in material science and technology could mean major progress in cancer research. One such example is a recent development of new “smart” materials that enable a shift even into the so-called fourth dimension. So-called four-dimensional (4D) printing of dynamic 3D objects that can change their morphology and/or characteristics in time by external stimuli, leading to shape-shifting abilities, seems to be very promising in drug testing or disease modeling for a patient-centered approach.¹²²

Conclusions and future direction

There is a great deal of evidence highlighting the importance of tumor–stroma communication in various processes related to cancer progression, including drug resistance. Therefore, creating better laboratory models relevantly mimicking the interplay between the tumor and stroma would lead to the development of more effective anti-cancer therapies. In general, tumors need to be cultured in a physiologically relevant environment resembling the processes and niche as in the native tissue. To achieve such progress in this field, patient-derived 3D structures preserving the tumor heterogeneity together with variable cells and molecules from the TME should be cultured together in a specifically organized manner in xeno-free ECM. This can be accomplished by the integration of state-of-the-art technologies such as polymeric scaffolds, 3D bioprinting, and organ-on-chip platforms. Such a combination should allow to better mimic disease and develop personalized medicine programs. On the contrary, the increased complexity of the models could also complicate their analysis. However, nowadays this aspect can be, at least partially, solved by incorporating in silico analyses and/or artificial intelligence algorithms into the whole process, but that is the theme for another review.

To sum up, 3D culture models (available 3D cancer models with their advantages and limitations are summarized in Table 1) that combine primary tumor cells with their microenvironment together with various flow technologies have the potential not only to bridge the gap between 2D cell cultures and animal models, but become completely new testing platform for personalized medicine. In the future, the increasing complexity of these models and their integration with information technologies should allow us to achieve comparable outputs to those obtained in vivo without the involvement of experimental animals. Therefore, the future laboratory models in the oncology field, especially models used for personalized medicine, will rely on the interdisciplinary collaboration between various fields such as biology, medicine, physics, chemistry, mathematics, and bioinformatics. By using an increased number of 3D modeling as a preclinical tool, the number of animal studies may be reduced and lead to a more ethical approach in cancer research and better anti-cancer therapies.

Table 1.

Overview of currently used 3D cancer models and technologies with their advantages and limitations.

Model/technology	Characterization	Benefits	Drawbacks
2D cell lines	Traditional monolayer culture grown on flat culture dish	• Low cost • Straightforward approach	• Less reliable • Lack of spatial interactions
Spheroids	Cellular aggregates derived from established cell lines grown in suspension or in 3D matrix	• Simple 3D in vitro model • Simulate oxygen gradient • Mimic drug penetration • Low cost • Reproducible • High-throughput	• Less advanced model among 3D cultures • Less suitable model for drug testing (lacks patient heterogeneity)
Tumor organoids	Patient-derived 3D in vitro model	• Patient-specific • Tumor heterogeneity • Suitable for personalized approach • Suitable for modeling TME interactions • Maintain phenotypic and genetic characteristics • Hypoxia modeling • High-throughput	• Lack of standardized culture protocol • Technical variability • Variable efficacy of organoid derivation • Longer derivation time
Assembloids	Organoids generated from multiple cell types	• Use of multiple cell types • Can model biological processes • Cell plasticity • Increased complexity	• Difficult derivation • Non-defined spatial organization
Bioreactors	Manufactured systems including flow systems for cell culture	• Maintain microenvironment • Model physiological functions of tissue • High-throughput testing • Reproducible • Independent control of various parameters • Possible combination of multiple cell types	• Depends on the specific type of bioreactor (e.g. shear forces may impact cell viability or differentiation; limited scale-up potential . . .) • Higher cost
3D Bioprinting	Technology mixing bioinks with living cells and printing them in 3D to construct natural tissue-like structures	• Multiple cell types, defined 3D architecture • Easy customization • Possibility of studying metastatic process	• Depends on the specific type (e.g. time-consuming, higher cost, lengthy post-processing, need for low viscosity bioink . . .)

3D: three-dimensional; 2D: two-dimensional; TME: tumor microenvironment.

Footnotes

Authors’ Contributions

All authors contributed equally to the conceptualization and writing of the manuscript. All authors have read and agreed to the published version of the manuscript.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This publication was created with the support of the Operational Program Integrated Infrastructure for the project BIOFORD [ITMS2014+ 313011AFG5], co-financed from the European Regional Development Fund and the state budget of the Slovak Republic, and Scientific Grant Agency (VEGA) (grant numbers 2/0067/22 and 2/0138/20).

ORCID iDs

Jana Plava

Lubos Danisovic

References

Sung

Ferlay

Siegel

Laversanne

Soerjomataram

Jemal

Bray

. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2021;71:209–49

Martinez-Pacheco

O’Driscoll

. Pre-clinical in vitro models used in cancer research: results of a worldwide survey. Cancers (Basel) 2021;13:6033

Han

. FDA Modernization Act 2.0 allows for alternatives to animal testing. Artif Organs 2023;47:449–50

Kapałczyńska

Kolenda

Przybyła

Zajączkowska

Teresiak

Filas

Ibbs

Bliźniak

Łuczewski

Lamperska

. 2D and 3D cell cultures—a comparison of different types of cancer cell cultures. Arch Med Sci 2018;14:910–9

Jubelin

Muñoz-Garcia

Griscom

Cochonneau

Ollivier

Heymann

M-F

Vallette

Oliver

Heymann

. Three-dimensional in vitro culture models in oncology research. Cell Biosci 2022;12:155

Sangeeta

Ankita Jaywant

Shafina

Jyotirmoi

Soumya

. Two-dimensional and three-dimensional cell culture and their applications. In: Xianquan

(ed.) Cell culture. Rijeka: IntechOpen, 2021, p.Ch. 3

Mabry

Payne

Anseth

. Microarray analyses to quantify advantages of 2D and 3D hydrogel culture systems in maintaining the native valvular interstitial cell phenotype. Biomaterials 2016;74:31–41

Wodarz

Näthke

. Cell polarity in development and cancer. Nat Cell Biol 2007;9:1016–24

Mak

Evaniew

Ghert

. Lost in translation: animal models and clinical trials in cancer treatment. Am J Transl Res 2014;6:114–8

10.

Bissell

Kenny

Radisky

. Microenvironmental regulators of tissue structure and function also regulate tumor induction and progression: the role of extracellular matrix and its degrading enzymes. Cold Spring Harb Symp Quant Biol 2005;70:343–56

11.

Nelson

Bissell

. Of extracellular matrix, scaffolds, and signaling: tissue architecture regulates development, homeostasis, and cancer. Annu Rev Cell Dev Biol 2006;22:287–309

12.

Bissell

. Architecture is the message: the role of extracellular matrix and 3-D structure in tissue-specific gene expression and breast cancer. Pezcoller Found J 2007;16:2–17

13.

Spencer

Bissell

. Extracellular matrix, nuclear and chromatin structure, and gene expression in normal tissues and malignant tumors: a work in progress. Adv Cancer Res 2007;97:275–94

14.

Baghban

Roshangar

Jahanban-Esfahlan

Seidi

Ebrahimi-Kalan

Jaymand

Kolahian

Javaheri

Zare

. Tumor microenvironment complexity and therapeutic implications at a glance. Cell Commun Signal 2020;18:59

15.

Kovács

Mikó

Ujlaki

Sári

Bai

. The microbiome as a component of the tumor microenvironment. Adv Exp Med Biol 2020;1225:137–53

16.

Ramamonjisoa

Ackerstaff

. Characterization of the tumor microenvironment and tumor-stroma interaction by non-invasive preclinical imaging. Front Oncol 2017;7:3

17.

Mueller-Klieser

. Multicellular spheroids. A review on cellular aggregates in cancer research. J Cancer Res Clin Oncol 1987;113:101–22

18.

Rodrigues

Kundu

Silva-Correia

Kundu

Oliveira

Reis

Correlo

. Emerging tumor spheroids technologies for 3D in vitro cancer modeling. Pharmacol Ther 2018;184:201–11

19.

Foty

. A simple hanging drop cell culture protocol for generation of 3D spheroids. J Vis Exp 2011;51:2720

20.

De Angelis

Bruselles

Francescangeli

Pucilli

Vitale

Zeuner

Tartaglia

Baiocchi

. Colorectal cancer spheroid biobanks: multi-level approaches to drug sensitivity studies. Cell Biol Toxicol 2018;34:459–69

21.

Charoen

Fallica

Colson

Zaman

Grinstaff

. Embedded multicellular spheroids as a biomimetic 3D cancer model for evaluating drug and drug-device combinations. Biomaterials 2014;35:2264–71

22.

Alessandri

Sarangi

Gurchenkov

Sinha

Kießling

Fetler

Rico

Scheuring

Lamaze

Simon

Geraldo

Vignjevic

Doméjean

Rolland

Funfak

Bibette

Bremond

Nassoy

. Cellular capsules as a tool for multicellular spheroid production and for investigating the mechanics of tumor progression in vitro. Proc Natl Acad Sci U S A 2013;110:14843–8

23.

Saraiva

Matias

Braga

Jacinto

Cabral

. Establishment of a 3D co-culture with MDA-MB-231 breast cancer cell line and patient-derived immune cells for application in the development of immunotherapies. Front Oncol 2020;10:1543

24.

Courau

Bonnereau

Chicoteau

Bottois

Remark

Assante Miranda

Toubert

Blery

Aparicio

Allez

Le Bourhis

. Cocultures of human colorectal tumor spheroids with immune cells reveal the therapeutic potential of MICA/B and NKG2A targeting for cancer treatment. J Immunother Cancer 2019;7:74

25.

Yakavets

Jenard

Francois

Maklygina

Loschenov

Lassalle

Dolivet

Bezdetnaya

. Stroma-rich co-culture multicellular tumor spheroids as a tool for photoactive drugs screening. J Clin Med 2019;8:1686

26.

Bauleth-Ramos

Feijão

Gonçalves

Shahbazi

Liu

Barrias

Oliveira

Granja

Santos

Sarmento

. Colorectal cancer triple co-culture spheroid model to assess the biocompatibility and anticancer properties of polymeric nanoparticles. J Control Release 2020;323:398–411

27.

Harimoto

Deb

Danino

. A rapid screening platform to coculture bacteria within tumor spheroids. Nat Protoc 2022;17:2216–39

28.

Nobre

Entenberg

Wang

Condeelis

Aguirre-Ghiso

. The different routes to metastasis via hypoxia-regulated programs. Trends Cell Biol 2018;28:941–56

29.

Langan

Dodd

Owen

Purcell

Jackson

Jha

. Direct measurements of oxygen gradients in spheroid culture system using electron parametric resonance oximetry. PLoS ONE 2016;11:e0149492

30.

Hirschhaeuser

Menne

Dittfeld

West

Mueller-Klieser

Kunz-Schughart

. Multicellular tumor spheroids: an underestimated tool is catching up again. J Biotechnol 2010;148:3–15

31.

Lucendo-Villarin

Meseguer-Ripolles

Drew

Fischer

Flint

Simpson

Machesky

Mountford

Hay

. Development of a cost-effective automated platform to produce human liver spheroids for basic and applied research. Biofabrication 2020;13:015009

32.

Dagogo-Jack

Shaw

. Tumour heterogeneity and resistance to cancer therapies. Nat Rev Clin Oncol 2018;15:81–94

33.

Drost

Clevers

. Organoids in cancer research. Nat Rev Cancer 2018;18:407–18

34.

Sato

Vries

Snippert

van de Wetering

Barker

Stange

van Es

Abo

Kujala

Peters

Clevers

. Single Lgr5 stem cells build crypt-villus structures in vitro without a mesenchymal niche. Nature 2009;459:262–5

35.

Ootani

Sangiorgi

Ueno

Toda

Sugihara

Fujimoto

Weissman

Capecchi

Kuo

. Sustained in vitro intestinal epithelial culture within a Wnt-dependent stem cell niche. Nat Med 2009;15:701–6

36.

LeSavage

Suhar

Broguiere

Lutolf

Heilshorn

. Next-generation cancer organoids. Nat Mater 2022;21:143–59

37.

Liu

Wang

Noordam

Lieshout

Verstegen

MMA

Yang

Zhang

Zhou

Carrascosa

Sprengers

IJzermans

JNM

Smits

Kwekkeboom

van der Laan

LJW

Peppelenbosch

Pan

Cao

. Cancer-associated fibroblasts provide a stromal niche for liver cancer organoids that confers trophic effects and therapy resistance. Cell Mol Gastroenterol Hepatol 2021;11:407–31

38.

Schuth

Le Blanc

Krieger

Jabs

Schenk

Giese

Büchler

Eils

Conrad

Strobel

. Patient-specific modeling of stroma-mediated chemoresistance of pancreatic cancer using a three-dimensional organoid-fibroblast co-culture system. J Exp Clin Cancer Res 2022;41:312

39.

Schreurs

Baumdick

Drewniak

Bunders

. In vitro co-culture of human intestinal organoids and lamina propria-derived CD4(+) T cells. STAR Protoc 2021;2:100519

40.

Dijkstra

Cattaneo

Weeber

Chalabi

van de Haar

Fanchi

Slagter

van der Velden

Kaing

Kelderman

van Rooij

van Leerdam

Depla

Smit

Hartemink

de Groot

Wolkers

Sachs

Snaebjornsson

Monkhorst

Haanen

Clevers

Schumacher

Voest

. Generation of tumor-reactive T cells by co-culture of peripheral blood lymphocytes and tumor organoids. Cell 2018;174:1586–98.e12

41.

Hubert

Rivera

Spangler

Mack

Prager

Couce

McLendon

Sloan

Rich

. A three-dimensional organoid culture system derived from human glioblastomas recapitulates the hypoxic gradients and cancer stem cell heterogeneity of tumors found in vivo. Cancer Res 2016;76:2465–77

42.

Drost

van Jaarsveld

Ponsioen

Zimberlin

van Boxtel

Buijs

Sachs

Overmeer

Offerhaus

Begthel

Korving

van de Wetering

Schwank

Logtenberg

Cuppen

Snippert

Medema

Kops

Clevers

. Sequential cancer mutations in cultured human intestinal stem cells. Nature 2015;521:43–7

43.

Fujii

Shimokawa

Date

Takano

Matano

Nanki

Ohta

Toshimitsu

Nakazato

Kawasaki

Uraoka

Watanabe

Kanai

Sato

. A colorectal tumor organoid library demonstrates progressive loss of niche factor requirements during tumorigenesis. Cell Stem Cell 2016;18:827–38

44.

Dijkstra

Monkhorst

Schipper

Hartemink

Smit

Kaing

de Groot

Wolkers

Clevers

Cuppen

Voest

. Challenges in establishing pure lung cancer organoids limit their utility for personalized medicine. Cell Rep 2020;31:107588

45.

Cakir

Xiang

Tanaka

Kural

Parent

Kang

Chapeton

Patterson

Yuan

Raredon

MSB

Dengelegi

Kim

Sun

Zhong

Lee

Patra

Hyder

Niklason

Lee

Yoon

Park

. Engineering of human brain organoids with a functional vascular-like system. Nat Methods 2019;16:1169–75

46.

Vogt

. Assembloids. Nat Methods 2021;18:27

47.

Kim

Choi

Kang

Kong

Kim

Yoon

Lee

Kim

Lee

Yang

Lee

Kang

Roh

Jung

Kim

Shin

. Creation of bladder assembloids mimicking tissue regeneration and cancer. Nature 2020;588:664–9

48.

Choi

Rim

Jang

Park

Cho

Lim

. The role of Jagged1 as a dynamic switch of cancer cell plasticity in PDAC assembloids. Theranostics 2022;12:4431–45

49.

Stephenson

Grayson

. Recent advances in bioreactors for cell-based therapies [version 1; peer review: 2 approved]. F1000Res 2018;7:517

50.

Liu

Fang

Huang

Xie

Wang

Liu

Zhang

Peng

. Tumor-on-a-chip: from bioinspired design to biomedical application. Microsyst Nanoeng 2021;7:50

51.

Bhatia

Ingber

. Microfluidic organs-on-chips. Nat Biotechnol 2014;32:760–72

52.

Halldorsson

Lucumi

Gómez-Sjöberg

Fleming

RMT

. Advantages and challenges of microfluidic cell culture in polydimethylsiloxane devices. Biosens Bioelectron 2015;63:218–31

53.

Sontheimer-Phelps

Hassell

Ingber

. Modelling cancer in microfluidic human organs-on-chips. Nat Rev Cancer 2019;19:65–81

54.

Menon

Chuah

Cao

Lim

Kang

. A microfluidic co-culture system to monitor tumor-stromal interactions on a chip. Biomicrofluidics 2014;8:064118

55.

Aung

Kumar

Theprungsirikul

Davey

Varghese

. An engineered tumor-on-a-chip device with breast cancer-immune cell interactions for assessing T-cell recruitment. Cancer Res 2020;80:263–75

56.

Sun

Tan

Chen

Ran

Hui

Chen

Zhao

C-X

. Microfluidic formation of coculture tumor spheroids with stromal cells as a novel 3D tumor model for drug testing. ACS Biomater Sci Eng 2018;4:4425–33

57.

Gioiella

Urciuolo

Imparato

Brancato

Netti

. An engineered breast cancer model on a chip to replicate ECM-activation in vitro during tumor progression. Adv Healthc Mater 2016;5:3074–84

58.

Haque

Wessel

Leary

Wang

Bhushan

Bishehsari

. Patient-derived pancreatic cancer-on-a-chip recapitulates the tumor microenvironment. Microsyst Nanoeng 2022;8:36

59.

Wang

Sun

Pei

. Microfluidic-based 3D engineered microvascular networks and their applications in vascularized microtumor models. Micromachines 2018;9:493

60.

Lim

Ching

Yoon

Jeon

Kim

. Microvascularized tumor organoids-on-chips: advancing preclinical drug screening with pathophysiological relevance. Nano Converg 2021;8:12

61.

Shirure

Curtis

Lezia

Goedegebuure

Aft

Fields

George

. Tumor-on-a-chip platform to investigate progression and drug sensitivity in cell lines and patient-derived organoids. Lab Chip 2018;18:3687–702

62.

Lai Benjamin

Lu Rick

Davenport

Dou

Wang

Radulovich

Tsao

Sun

Radisic

. Recapitulating pancreatic tumor microenvironment through synergistic use of patient organoids and organ-on-a-chip vasculature. Adv Funct Mater 2020;30:2000545

63.

Mintz

Sowers

Brown

Hilmer

Mazza

Huvos

Meyers

Lafleur

McDonough

Henry

Ramsey

Antonescu

Chen

Healey

Daluski

Berens

Macdonald

Gorlick

Stephan

. An expression signature classifies chemotherapy-resistant pediatric osteosarcoma. Cancer Res 2005;65:1748–54

64.

van Kempen

Rijntjes

Mamor-Cornelissen

Vincent-Naulleau

Gerritsen

Ruiter

van Dijk

Geffrotin

van Muijen

. Type I collagen expression contributes to angiogenesis and the development of deeply invasive cutaneous melanoma. Int J Cancer 2008;122:1019–29

65.

Acerbi

Cassereau

Dean

Shi

Park

Chen

Liphardt

Hwang

Weaver

. Human breast cancer invasion and aggression correlates with ECM stiffening and immune cell infiltration. Integr Biol (Camb) 2015;7:1120–34

66.

Provenzano

Inman

Eliceiri

Knittel

Yan

Rueden

White

Keely

. Collagen density promotes mammary tumor initiation and progression. BMC Med 2008;6:11

67.

Mammoto

Jiang

Panigrahy

Kieran

Mammoto

. Role of collagen matrix in tumor angiogenesis and glioblastoma multiforme progression. Am J Pathol 2013;183:1293–305

68.

Porsch

Bernert

Mehić

Theocharis

Heldin

. Efficient TGFβ-induced epithelial-mesenchymal transition depends on hyaluronan synthase HAS2. Oncogene 2013;32:4355–65

69.

Henke

Nandigama

Ergün

. Extracellular matrix in the tumor microenvironment and its impact on cancer therapy. Front Mol Biosci 2019;6:160

70.

Vukicevic

Kleinman

Luyten

Roberts

Roche

Reddi

. Identification of multiple active growth factors in basement membrane Matrigel suggests caution in interpretation of cellular activity related to extracellular matrix components. Exp Cell Res 1992;202:1–8

71.

Huch

Knoblich

Lutolf

Martinez-Arias

. The hope and the hype of organoid research. Development 2017;144:938–41

72.

Blondel

Lutolf

. Bioinspired hydrogels for 3D organoid culture. Chimia (Aarau) 2019;73:81–5

73.

Park

Lewis

Gerecht

. Bioinspired hydrogels to engineer cancer microenvironments. Annu Rev Biomed Eng 2017;19:109–33

74.

LeValley

Kloxin

. Chemical approaches to dynamically modulate the properties of synthetic matrices. ACS Macro Lett 2019;8:7–16

75.

Guarnieri

De Capua

Ventre

Borzacchiello

Pedone

Marasco

Ruvo

Netti

. Covalently immobilized RGD gradient on PEG hydrogel scaffold influences cell migration parameters. Acta Biomater 2010;6:2532–9

76.

Martinez-Garcia

Fischer

Hayn

Mierke

Burgess

Harmsen

. A Beginner’s guide to the characterization of hydrogel microarchitecture for cellular applications. Gels 2022;8:535

77.

Martinez-Garcia

de Hilster

RHJ

Sharma

Borghuis

Hylkema

Burgess

Harmsen

. Architecture and composition dictate viscoelastic properties of organ-derived extracellular matrix hydrogels. Polymers (Basel) 2021;13:3113

78.

de Hilster

RHJ

Sharma

Jonker

White

Gercama

Roobeek

Timens

Harmsen

Hylkema

Burgess

. Human lung extracellular matrix hydrogels resemble the stiffness and viscoelasticity of native lung tissue. Am J Physiol Lung Cell Mol Physiol 2020;318:L698–704

79.

Liguori

TTA

de Moraes

Sinkunas

Terlizzi

van Dongen

Sharma

Moreira

LFP

Harmsen

. Molecular and biomechanical clues from cardiac tissue decellularized extracellular matrix drive stromal cell plasticity. Front Bioeng Biotechnol 2020;8:520

80.

Antoine

Vlachos

Rylander

. Tunable collagen I hydrogels for engineered physiological tissue micro-environments. PLoS ONE 2015;10:e0122500

81.

Wang

Zhao

Zhang

Yang

Jia

. A novel poly(amido amine)-dendrimer-based hydrogel as a mimic for the extracellular matrix. Adv Mater 2014;26:4163–7

82.

Collier

Segura

. Evolving the use of peptides as components of biomaterials. Biomaterials 2011;32:4198–204

83.

Kessler

Gehrke

Winnefeld

Huber

Hoch

Walter

Wyrwa

Schnabelrauch

Schmidt

Kückelhaus

Lehnhardt

Hirsch

Jacobsen

. Methacrylated gelatin/hyaluronan-based hydrogels for soft tissue engineering. J Tissue Eng 2017;8:2041731417744157

84.

Krishnamoorthy

Noorani

. Effects of encapsulated cells on the physical-mechanical properties and microstructure of gelatin methacrylate hydrogels. Int J Mol Sci 2019;20:5061

85.

Loessner

Meinert

Kaemmerer

Martine

Yue

Levett

Klein

Melchels

Khademhosseini

Hutmacher

. Functionalization, preparation and use of cell-laden gelatin methacryloyl-based hydrogels as modular tissue culture platforms. Nat Protoc 2016;11:727–46

86.

Sun

Wang

Guo

Yang

. Synthesis and properties of gelatin methacryloyl (GelMA) hydrogels and their recent applications in load-bearing tissue. Polymers (Basel) 2018;10:1290

87.

Pepelanova

Kruppa

Scheper

Lavrentieva

. Gelatin-methacryloyl (GelMA) hydrogels with defined degree of functionalization as a versatile toolkit for 3D cell culture and extrusion bioprinting. Bioengineering (Basel) 2018;5:55

88.

Arya

Hallur

Karkisaval

Gudipati

Rajendiran

Dhavale

Ramachandran

Jayaprakash

Gundiah

Chaubey

. Gelatin methacrylate hydrogels as biomimetic three-dimensional matrixes for modeling breast cancer invasion and chemoresponse in vitro. ACS Appl Mater Interfaces 2016;8:22005–17

89.

Griffith

. Emerging design principles in biomaterials and scaffolds for tissue engineering. Ann N Y Acad Sci 2002;961:83–95

90.

Breslin

O’Driscoll

. The relevance of using 3D cell cultures, in addition to 2D monolayer cultures, when evaluating breast cancer drug sensitivity and resistance. Oncotarget 2016;7:45745–56

91.

Moroni

Casettari

Lamprou

. 3D and 4D printing in the fight against breast cancer. Biosensors (Basel) 2022;12:568

92.

Fernandez-Vicente

Calle

Ferrandiz

Conejero

. Effect of infill parameters on tensile mechanical behavior in desktop 3D printing. 3D Print Addit Manufact 2016;3:183–92

93.

Lubombo

Huneault

. Effect of infill patterns on the mechanical performance of lightweight 3D-printed cellular PLA parts. Mater Today Commun 2018;17:214–28

94.

Bhuskute

Shende

Prabhakar

. 3D printed personalized medicine for cancer: applications for betterment of diagnosis, prognosis and treatment. AAPS PharmSciTech 2021;23:8

95.

Hull

. Apparatus for production of three dimensional objects by stereolithography. US4575330A, USA, 2000

96.

Klebe

. Cytoscribing: a method for micropositioning cells and the construction of two- and three-dimensional synthetic tissues. Exp Cell Res 1988;179:362–73

97.

Landers

Hübner

Schmelzeisen

Mülhaupt

. Rapid prototyping of scaffolds derived from thermoreversible hydrogels and tailored for applications in tissue engineering. Biomaterials 2002;23:4437–47

98.

Dhariwala

Hunt

Boland

. Rapid prototyping of tissue-engineering constructs, using photopolymerizable hydrogels and stereolithography. Tissue Eng 2004;10:1316–22

99.

Kang

Lee

Kengla

Yoo

Atala

. A 3D bioprinting system to produce human-scale tissue constructs with structural integrity. Nat Biotechnol 2016;34:312–9

100.

Jayasinghe

Qureshi

Eagles

. Electrohydrodynamic jet processing: an advanced electric-field-driven jetting phenomenon for processing living cells. Small 2006;2:216–9

101.

Norotte

Marga

Niklason

Forgacs

. Scaffold-free vascular tissue engineering using bioprinting. Biomaterials 2009;30:5910–7

102.

Gao

Liu

. Coaxial nozzle-assisted 3D bioprinting with built-in microchannels for nutrients delivery. Biomaterials 2015;61:203–15

103.

Noor

Shapira

Edri

Gal

Wertheim

Dvir

. 3D printing of personalized thick and perfusable cardiac patches and hearts. Adv Sci (Weinh) 2019;6:1900344

104.

Lee

Hudson

Shiwarski

Tashman

Hinton

Yerneni

Bliley

Campbell

Feinberg

. 3D bioprinting of collagen to rebuild components of the human heart. Science 2019;365:482–7

105.

Hakimi

Cheng

Leng

Sotoudehfar

Bakhtyar

Amini-Nik

Jeschke

Günther

. Handheld skin printer: in situ formation of planar biomaterials and tissues. Lab Chip 2018;18:1440–51

106.

Owens

Marga

Forgacs

Heesch

. Biofabrication and testing of a fully cellular nerve graft. Biofabrication 2013;5:045007

107.

Yao

Wei

Guo

Jin

Yan

Zhou

Wang

. Design, construction and mechanical testing of digital 3D anatomical data-based PCL-HA bone tissue engineering scaffold. J Mater Sci Mater Med 2015;26:5360

108.

Pati

Song

Rijal

Jang

Kim

Cho

. Ornamenting 3D printed scaffolds with cell-laid extracellular matrix for bone tissue regeneration. Biomaterials 2015;37:230–41

109.

Kesti

Eberhardt

Pagliccia

Kenkel

Grande

Boss

Zenobi-Wong

. Bioprinting complex cartilaginous structures with clinically compliant biomaterials. Adv Funct Mater 2015;25:7406–17

110.

Kundu

Shim

Jang

Kim

Cho

. An additive manufacturing-based PCL-alginate-chondrocyte bioprinted scaffold for cartilage tissue engineering. J Tissue Eng Regen Med 2015;9:1286–97

111.

Herreros-Pomares

Zhou

Calabuig-Fariñas

Lee

Torres

Esworthy

Hann

Jantus-Lewintre

Camps

Zhang

. 3D printing novel in vitro cancer cell culture model systems for lung cancer stem cell study. Mater Sci Eng C Mater Biol Appl 2021;122:111914

112.

Zhao

Yao

Ouyang

Ding

Zhang

Cheng

Sun

. Three-dimensional printing of Hela cells for cervical tumor model in vitro. Biofabrication 2014;6:035001

113.

Lin

Yang

Yuan

Yang

Zhang

Tang

. Multi-omics analysis based on 3D-bioprinted models innovates therapeutic target discovery of osteosarcoma. Bioact Mater 2022;18:459–70

114.

Lopez

Ruiz-Toranzo

Antich

Chocarro-Wrona

López-Ruiz

Jiménez

Marchal

. Biofabrication of a tri-layered 3D-bioprinted CSC-based malignant melanoma model for personalized cancer treatment. Biofabrication 2022;15:035016

115.

Wang

Song

Perez

MEM

Wang

Cao

Maharjan

Anderson

Chauhan

Zhang

. A 3D-bioprinted multiple myeloma model. Adv Healthc Mater 2022;11:e2100884

116.

Baka

Godier

Lamy

Mallick

Gribova

Figarol

Bezdetnaya

Chateau

Magne

Stiefel

Louaguef

Lavalle

Gaffet

Joubert

Alem

. A coculture based, 3D bioprinted ovarian tumor model combining cancer cells and cancer associated fibroblasts. Macromol Biosci 2022;23:e2200434

117.

Neufeld

Yeini

Reisman

Shtilerman

Ben-Shushan

Pozzi

Madi

Tiram

Eldar-Boock

Ferber

Grossman

Ram

Satchi-Fainaro

. Microengineered perfusable 3D-bioprinted glioblastoma model for in vivo mimicry of tumor microenvironment. Sci Adv 2021;7:eabi9119

118.

Dey

Kim

Nagamine

Karhan

Kozhaya

Dogan

Unutmaz

Ozbolat

. Biofabrication of 3D breast cancer models for dissecting the cytotoxic response of human T cells expressing engineered MAIT cell receptors. Biofabrication 2022;14:044105

119.

Han

Huang

Wei

Yin

Jiang

. The application of 3D bioprinting in urological diseases. Mater Today Bio 2022;16:100388

120.

Holzapfel

Wagner

Loessner

Holzapfel

Thibaudeau

Crawford

Ling

Clements

Russell

Hutmacher

. Species-specific homing mechanisms of human prostate cancer metastasis in tissue engineered bone. Biomaterials 2014;35:4108–15

121.

Bock

Shokoohmand

Kryza

Röhl

Meijer

Tran

Nelson

Clements

Hutmacher

. Engineering osteoblastic metastases to delineate the adaptive response of androgen-deprived prostate cancer in the bone metastatic microenvironment. Bone Res 2019;7:13

122.

Ding

Lee

Tang

Gasvoda

Alsberg

. 4D cell-condensate bioprinting. Small 2022;18:e2202196