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Unlocking the Potential of Spheroids in Personalized Medicine: Systematic Review of Seeding Methodologies

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Abstract
Three-dimensional (3D) spheroid models have revolutionized in vitro cancer research by offering more physiologically relevant alternatives to traditional two-dimensional (2D) cultures. This systematic review evaluates methods for spheroid formation and cellular sources used, highlighting diverse applications and preferences in the field. The five most investigated cancer origins for spheroid seeding are breast, colon, lung, ovary, and brain cancers, reflecting their clinical importance and research focus. Among seeding methodologies, forced-floating and scaffold-based methods predominate, demonstrating reliability and versatility in spheroid generation. Other techniques, including microfluidics, bioprinting, hanging drop and suspension culture also play significant roles, each with distinct advantages and limitations. This review underscores the growing adoption of spheroid models and the need for standardization in methodologies to enhance reproducibility and translational potential in cancer research.
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1. Introduction

In recent years, there has been a paradigm shift in biomedical research towards developing more clinically relevant models to study human physiology and diseases. Personalized medicine, aiming to tailor medical interventions to individual patient characteristics, has gained prominence in the quest for more effective and targeted treatments. Within this context, three-dimensional cell culture models, particularly spheroids, have emerged as valuable tools for bridging the gap between traditional two-dimensional cell cultures and in vivo studies. Spheroids, characterized by their spherically shaped cellular aggregates, exhibit enhanced physiological relevance by recreating cell-cell and cell-matrix interactions found in native tissues. This article aims to explore the developing field of spheroid research, focusing on their potential applications in personalized medicine and elucidating methodologies employed for spheroid seeding.
Traditional cell culture systems are often inadequate in reproducing the complexity of in vivo tissue structures and functions. Spheroids, formed through the self-assembly of cells, provide a closer representation of the native tissue microenvironment. This three-dimensional architecture facilitates cell-cell interactions, nutrient gradients, and spatial organization, closely mimicking the in vivo conditions. As a result, spheroids have gained prominence as an advanced in vitro model that bridges the gap between conventional cell cultures and in vivo studies.

1.1. Summary of Models for In Vitro Studies

The concept of growing cells outside of the human body began in the early 20th century. In 1907, Ross Harrison obtained the first successful tissue culture by growing nerve fibers from frog embryos. This work paved the way for cell culture techniques that have since become foundational in biomedical research [1].
Furthermore, the establishment of the first continuous human cell line, HeLa cells, by George Otto Gey in 1951 marked a revolutionary step in cancer research. Derived from cervical cancer cells, HeLa provided researchers with an immortal cell line capable of indefinite growth under proper conditions. This breakthrough enabled consistent and reproducible experiments, fostering a deeper understanding of cancer progression and therapeutic responses [2].
The 2D monolayer culture technique dominated in vitro cancer research for much of the 20th century. 2D monolayer cultures have been the cornerstone of in vitro cancer research for decades due to their simplicity, cost-effectiveness, and adaptability to high-throughput screening. In these systems, cancer cells are grown on flat, rigid substrates, providing uniform exposure to nutrients, oxygen, and drugs. The standardized conditions in 2D cultures enable reproducible experiments and straightforward readouts, making them ideal for initial mechanistic studies and large-scale drug screening. Cells are grown on flat plastic or glass surfaces in a single layer, making it possible to study their morphology, growth, and responses to drugs in a controlled environment. These models were integral to early breakthroughs in cancer biology, such as identifying signaling pathways and testing chemotherapeutics. However, their limitations became increasingly apparent. The two-dimensional format failed to replicate the complexity of the tumor microenvironment, cell-cell interactions, and gradients of nutrients and oxygen present, and cellular architecture found in vivo. Cells grown in 2D often exhibit altered morphology, gene expression, and behavior compared to their in vivo counterparts [3].
The limitations of 2D models drifted the development of 3D models. In recent years, three-dimensional (3D) culture systems, including spheroids, organoids, and other, have emerged as advanced in vitro models that better mimic the in vivo tumor microenvironment. Spheroids, first described in the 1970s, allowed researchers to grow cells in a structure that mimics the spatial architecture of tumors. Spheroids, for instance, are self-organizing aggregates of cancer cells that develop gradients of oxygen, nutrients, and waste products, closely resembling the structural and functional characteristics of solid tumors. These models better simulate cell-cell and cell-matrix interactions, as well as the nutrient and oxygen gradients found in actual tumors. This advancement has significantly improved the study of tumor biology and drug resistance [4].
Today, 2D and 3D models are commonly used in tandem, each complementing the other’s strengths. 2D cultures remain essential for high-throughput screening due to their simplicity and reproducibility. In contrast, 3D models provide a more physiologically relevant context, making them indispensable for studying tumor progression, metastasis, and resistance to therapy. Hybrid approaches combining 2D and 3D cultures, as well as emerging technologies like organ-on-a-chip and patient-derived organoids, are bridging the gap between in vitro and in vivo systems. These models aim to capture the advantages of both 2D simplicity and 3D physiological relevance, providing a more comprehensive understanding of tumor biology and therapeutic responses. While 2D cultures remain essential for preliminary studies due to their simplicity and efficiency, incorporating 3D models enhances the translational potential of in vitro research by mimicking critical aspects of tumor biology. The complementary use of both systems, along with advances in hybrid models, offers a robust framework for cancer research, drug discovery, and personalized medicine [5,6,7].
However, there is an emerging consensus that research should transition from reliance on traditional 2D models to the adoption of more physiologically relevant 3D models [8,9].

1.2. Comparison of 2D and 3D Models

In vitro models are indispensable tools for studying cancer biology, screening therapeutic agents, and elucidating disease mechanisms. Among these, traditional two-dimensional (2D) cancer cell cultures and advanced three-dimensional (3D) models are widely utilized. Each model possesses distinct advantages and limitations. The most appropriate model selection should be made based on the specific context of the application. Both models also represent defined potentials. Table 1 highlights how each model is best suited to specific research objectives, emphasizing the importance of selecting the appropriate system based on the experimental needs [5,6,7,8,10,11,12,13].

1.3. Spheroids in Personalized Medicine

Personalized medicine aims to customize healthcare interventions based on individual patient characteristics, and spheroids emerge as a powerful tool in this endeavor. The inherent heterogeneity within patient populations can be more accurately represented using spheroids, enabling the development of personalized therapeutic strategies. By incorporating patient-specific cells into spheroid models, researchers can assess drug responses and tailor treatment regimens for improved clinical outcomes [14].
Spheroids have emerged as a pivotal three-dimensional (3D) in vitro model in cancer research, offering a significant leap forward in replicating the complexity of in vivo tumor biology. Unlike traditional two-dimensional (2D) monolayer cultures, spheroids self-assemble into multicellular aggregates, creating a structurally and functionally relevant microenvironment that mimics many key aspects of solid tumors. This enhanced physiological relevance makes spheroids an invaluable tool for advancing our understanding of cancer biology and improving preclinical evaluations of therapeutic agents [15].
The defining characteristic of spheroids is their ability to form gradients of oxygen, carbon dioxide, nutrients, and metabolites. These gradients lead to the development of distinct cellular zones within the spheroid [15].
Cellular zones of spheroids are visualized and presented in Figure 1. Three cellular zones of spheroids are:
  • Proliferative outer layer: Consisting of actively dividing cells, with high accessibility to oxygen and nutrients.
  • Quiescent intermediate layer: Consisting of quiescent and senescent cells with reduced metabolic activity due to limited nutrient and oxygen availability.
  • Hypoxic apoptotic core: Consisting of cells in apoptotic state due to severe nutrient and oxygen deprivation. Core environment mimics what is observed in poorly vascularized tumor regions in vivo.
This zonal architecture replicates the heterogeneous microenvironment of solid tumors, which is critical for studying tumor progression, metastasis, and resistance to therapies.

1.4. Applications of Spheroids Models

Spheroids are widely utilized in cancer research as robust models for examining critical biological processes in a three-dimensional context. They provide significant insights into tumor progression by enabling detailed investigation of invasion, metastasis, and interactions between the tumor and surrounding stroma. In the realm of therapeutic screening, spheroids facilitate the evaluation of anti-cancer drug efficacy, penetration dynamics within the tumor microenvironment, and mechanisms of drug resistance. They are also essential for modeling tumor responses to hypoxia and radiation therapy, offering a physiologically relevant system that closely mimics in vivo conditions. Additionally, spheroids play a pivotal role in immunotherapy research by supporting the study of immune cell-tumor interactions, thereby providing a more representative alternative to conventional two-dimensional culture models [15,16]

2. Materials and Methods

A comprehensive search was conducted in the PubMed database to identify relevant articles available until December 2024. The search utilized specific free words and Medical Subject Headings (MeSH) terms, including key terms such as 'spheroid,' 'cancer,' 'drug,' 'patient-derived,' and 'tumor.' Exclusion terms 'co-culture' and 'xenograft' were applied. Only articles published in English were considered for inclusion.
Inclusion criteria encompassed studies involving spheroids formed from patient-derived cancer cells, while exclusion criteria covered articles that did not meet these inclusion criteria, reviews, case reports, and works focusing on the application or use of spheroids in areas other than drug screening.
Data extraction from included articles comprised information on authors, publication year, title, cancer type, cell aggregation protocol, culture conditions, spheroid measurements, in vitro functional properties, therapeutic effects in vivo, and study model employed.
The inclusion criterion for English-language publications may introduce potential bias, excluding relevant literature in other languages. Consequently, the findings should be interpreted cautiously, acknowledging the potential limitations associated with the language-based selection criteria.

3. Results

3.1. Database Screening

Following a screening of 190 articles retrieved through searches in PubMed pertaining to seeding of spheroids from human cancer cells for drug sensitivity screening, only 143 articles were evaluated for eligibility based on the search strategy outlined in the materials and methods section. The selection process is illustrated in Figure 2.

3.2. Systematic Review

Table 2 displays the selected 143 articles along with their fundamental details, including: first author and publication year, cancer type by type of tissue in which cancer originates (histological type) and by primary site, spheroid seeding method.

3.2.1. Source of Spheroids

Spheroids derived from various cancer types are extensively utilized in research to mimic in vivo tumor characteristics, providing insights into diverse cancer-specific processes. The ability to generate spheroids from a variety of cell sources, including patient-derived tumor cells, further enhances their value in studying personalized therapeutic responses. These models allow researchers to recreate the complexity of individual tumors and test specific treatment regimens in vitro, paving the way for advances in precision and personalized medicine. In the present systematic review, the most common cell sources of spheroids were identified. Five most investigated cancer origins associated with spheroids were breast (n=46, accounting for 25% of all investigated cancers), followed by colon (n=23, 12%), lung (n=21, 11%), ovary (n=19, 10%), and brain (n=18, 10%). A complete summary of systematic review results is presented in Figure 3 and Table 3.

Breast Cancer

Spheroids derived from breast cancer cells represent one of the most extensively studied in vitro models, reflecting the prominence of breast cancer as both a clinical challenge and leading research focus. Systematic review of the literature revealed that breast cancer cell lines and patient-derived cells were the most frequently used sources for spheroid generation.
Breast cancer spheroid models facilitate the exploration of unique tumor characteristics (e.g. variations in growth dynamics, gene expression profiles, and interactions with the tumor microenvironment) and aspects of cancer biology (e.g. immortality, telomerase activation, antiapoptotic strategy) [20,28,48,156].
Moreover, this approach facilitates the exploration of therapies targeting estrogen-metabolizing enzymes and receptors, enabling the discovery of novel treatments that may prevent tumor initiation or inhibit cancer growth [26].
Additionally, this methodology supports the development of patient-specific drugs, thereby aligning with the principles of precision medicine to optimize therapeutic outcomes for individual breast cancer patients [59].

Colon Cancer

Colon cancer is the second most common source of cells used for spheroid generation, reflecting its critical role in cancer research.
To enhance the utility of human 3D colorectal cancer spheroid models in preclinical drug assessment, there is the need for standardized and validated methodologies. While monoculture spheroids are useful for high-throughput drug screening due to their simplicity, spheroids provide deeper insights into tumor biology and chemoresistance mechanisms, offering a more accurate preclinical tool for evaluating therapeutic efficacy and developing new drug candidates [33,157].
3D cultures still face challenges in clinical implementation, and advancements in co-culture techniques, addressing tumor heterogeneity, and improving laboratory protocols are essential for enhancing reproducibility and drug testing reliability in colorectal cancer research [158]. Moreover, collecting cells during biopsy from different tumor sites might provide more comprehensive representation of tumor subclones, offering greater insight into the tumor's diverse properties and improving the accuracy of preclinical models for drug testing and personalized medicine [158].

Lung Cancer

Lung cancer represents the third most common source of cells for generating spheroids. Lung cancer-derived spheroids are utilized to investigate key aspects of tumor biology.
Lung cancer spheroids are particularly valuable for studying the progression of both non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC), which differ significantly in their biological behavior and response to therapy [159,160].
Therapeutically, lung cancer spheroids serve as platforms for evaluating the efficacy of novel anti-cancer agents, including small molecules, biologics, and combination therapies. Their three-dimensional structure facilitates studies of drug delivery systems aimed at overcoming barriers such as limited penetration into solid tumors [40,47,49,67,77,119].

Ovarian Cancer

Ovarian cancer is the fourth most common source of cells used for spheroid generation. Spheroids derived from ovarian cancer cells are utilized in research to study processes central to ovarian cancer pathology, such as peritoneal metastasis, chemoresistance, and interactions with the tumor microenvironment. Given the propensity of ovarian cancer to spread via the peritoneal cavity through multicellular aggregates, spheroids serve as a physiologically relevant model to replicate these metastatic behaviors in vitro [31,52,76,106,107].
Moreover, patient-derived ovarian cancer spheroids are increasingly used for precision oncology, allowing for the evaluation of personalized therapeutic strategies tailored to the molecular profiles of individual tumors [113,148].

Brain Cancer

Brain cancers, including glioblastoma and other gliomas, rank as the fifth most common source of cells used for spheroid generation.
These three-dimensional models are pivotal for studying the unique microenvironment and invasive properties of brain tumors, which are characterized by their aggressive behavior and resistance to standard therapies. Brain cancer-derived spheroids closely mimic the in vivo conditions of brain tumors, providing insights into key processes such as tumor invasion, therapeutic resistance, and interactions with the extracellular matrix (ECM). Glioblastoma-derived spheroids are among the most studied in this category. They are particularly valuable for investigating the highly invasive nature of glioblastoma cells, which infiltrate surrounding healthy brain tissue, making complete surgical resection nearly impossible [24,63,74,93,104].
Recent advancements include patient-derived brain cancer spheroids, which preserve the genetic and phenotypic heterogeneity of primary tumors. These models are increasingly used for personalized medicine, enabling the testing of individualized therapeutic regimens in a controlled in vitro setting [30,64,147].

3.2.2. Spheroid Seeding Methods

The successful implementation of spheroids in personalized medicine relies on robust and reproducible methodologies for their generation. The generation of three-dimensional (3D) spheroids as in vitro models requires careful consideration of seeding methods to ensure reproducibility, scalability, and physiological relevance. A variety of techniques have been developed to create spheroids, ranging from traditional methods to advanced approaches incorporating cutting-edge technologies. An overview of the most common and recent seeding methods used for the seeding of spheroids from human cancer cells is presented below.
In conclusion, this article aims to provide a thorough understanding of the methodologies employed in spheroid seeding and highlights the manifold applications of spheroids in advancing personalized medicine.
Our systematic review revealed that, among spheroid seeding methodologies, the most common were forced floating (n=70), scaffold-based methods (n=41), recent advances (n = 20), hanging drop (n=14) and suspension culture (n=4). A summary of systematic review results is presented in Figure 4 and Table 4.
Based on the systematic review, a summary of the most common spheroid seeding methods is illustrated in Figure 5. The figure visualizes the most utilized spheroid seeding methods such as hanging drop (1), forced-floating (2), magnetic levitation (3), scaffold-based (4), suspension culture (5), and recent scientific advances (6) methods: microencapsulation (6a), bioprinting (6b), nanoparticles (6c), chips and microfluidics (6d).

Forced Floating

The forced floating method is the most employed technique for spheroid formation due to its simplicity and scalability. This approach uses non-adhesive surfaces to prevent cell attachment, encouraging cells to aggregate and form three-dimensional (3D) spheroids. The technique involves seeding cells in multi-well plates that have been treated to inhibit surface adhesion, either through coating with low-attachment materials like poly-HEMA (Poly(2-hydroxyethyl methacrylate)) or using ultra-low attachment (ULA) culture plates designed specifically for this purpose. In the absence of adhesion sites, cells naturally aggregate in the medium, forming spheroids under the influence of gravity and intercellular interactions. The process begins with the preparation of a single-cell suspension of the desired cell density, typically ranging from 103 to 105 cells per well, depending on the type of cells and the intended spheroid size. The cell suspension is then distributed into the wells of the plate. Over the course of 24–96 hours, depending on the cell type and experimental conditions, the cells self-assemble into compact spheroids [22,100,138,163].
The forced floating method is particularly advantageous for producing uniform spheroids with consistent size and morphology, making it suitable for high-throughput applications such as drug screening and toxicity assays. Moreover, one of the significant benefits of the forced floating method is its compatibility with automated systems, allowing for large-scale spheroid generation and analysis. Additionally, this method does not require specialized equipment beyond the plates or coatings, making it accessible for most laboratories. However, the method has certain limitations. The reliance on non-adhesive surfaces can lead to variability in spheroid integrity and size if the cell density or culture conditions are not carefully optimized. Additionally, long-term culture may be constrained by limited nutrient and oxygen diffusion, necessitating periodic medium exchange or supplementation with perfusion systems [7,31 55,57,92,139,113].

Scaffold-Based

The scaffold-based method for spheroid seeding is the second most utilized method for generating three-dimensional (3D) cellular aggregates. This method uses biomaterials, known as scaffolds, that mimic the extracellular matrix (ECM) to provide the structural support and environment conducive to cell adhesion, proliferation, and aggregation into spheroids. Scaffolds can be fabricated from a wide range of materials, including natural polymers such as collagen, gelatin, and alginate, as well as synthetic polymers like PLGA (poly(lactic-co-glycolic acid)) and PEG (polyethylene glycol). The process typically begins with the preparation of the scaffold material, which may be in the form of hydrogels, porous matrices, or microcarriers. Cells are then seeded onto or encapsulated within the scaffold. Once seeded, the cells interact with the scaffold material and with one another, eventually forming spheroid structures. The scaffold not only facilitates cell aggregation, but it also supports nutrient and oxygen diffusion, which is crucial for maintaining cell viability and function in 3D cultures [140,165,166].
Scaffold-based methods offer significant advantages, including ability to recreate a more physiologically relevant microenvironment compared to non-adhesive-based techniques. The structural and biochemical properties of the scaffold can be engineered to closely mimic the in vivo ECM, supporting the growth and differentiation of specific cell types. This makes the method particularly suitable for modeling complex tissues and for co-culture systems involving multiple cell types. Additionally, scaffold-based systems are compatible with long-term culture, as the scaffold provides a sustained environment for nutrient and waste exchange. However, there are limitations to this approach. The use of scaffolds introduces variability in spheroid size and shape, depending on the uniformity of the material and the seeding protocol. The composition and mechanical properties of the scaffold can also influence cellular behavior, which may complicate the interpretation of results. Furthermore, the cost and complexity of scaffold fabrication, particularly for advanced synthetic materials, may be a barrier for some applications [7,165].

Hanging Drop

The hanging drop method is a robust and third most utilized technique for generating three-dimensional (3D) spheroids in vitro, particularly valued for its ability to produce uniform and physiologically relevant cellular aggregates. This method capitalizes on gravity-driven cellular self-assembly within droplets of culture medium, facilitating interactions that mimic those found in vivo. To implement this approach, a cell suspension of the desired density is prepared, often ranging from 10² to 10⁴ cells per droplet. Droplets, typically 20–50 μL in volume, are then dispensed onto the inner surface of an inverted petri dish lid. The droplets are retained by surface tension, allowing them to remain suspended. This setup is placed over a dish containing a hydrating agent, such as phosphate-buffered saline (PBS) or water, to maintain humidity and prevent evaporation during incubation. Over 24 to 72 hours under standard culture conditions, the suspended cells settle at the bottom of the droplets and aggregate into spheroids through intercellular adhesion and natural cell-cell interactions [17,34,53,113,115,143].
The hanging drop method is particularly advantageous due to its simplicity, low cost, and minimal equipment requirements. This method offers significant benefits, including enhanced cellular aggregation and adhesion driven by gravitational forces, which minimize mechanical damage to spheroids. It also allows for precise control over the spheroid size and cell composition by adjusting the initial cell density and droplet volume. However, this technique has limitations, such as the potential disruption of spheroids during transfer to conventional culture plates due to mechanical stress. Moreover, it is labor-intensive and not easily scalable for high-throughput applications, as each droplet must be individually prepared and managed. Additionally, nutrient and waste exchange are limited by the small volume of medium, necessitating careful monitoring to maintain spheroid viability. It has also been adapted for co-culture systems to explore interactions between different cell types, such as tumor and stromal cells [7,53,58,113,132,167].

Suspension Culture

The suspension culture method is the fourth most utilized approach for generating spheroids in in vitro studies, particularly in cancer research, developmental biology, and drug discovery. This technique relies on culturing cells in a liquid medium without a solid substrate, allowing them to aggregate and form spheroids due to intercellular adhesion and natural aggregation tendencies. Typically, the suspension culture is conducted in low-attachment culture vessels, such as non-adherent plates or spinner flasks, to prevent cell adhesion to the container surface and promote spheroid formation [140,168].
The process begins with the preparation of a single-cell suspension at a defined density, which is a critical parameter for achieving uniform spheroid size and morphology. These vessels prevent cells from adhering to the surface and maintain them in suspension. Spinner flasks or bioreactors are dynamic systems, where gentle agitation or rotation keeps the cells suspended and evenly distributed, which can enhance the uniformity of spheroid formation and improve mass transport of nutrients and oxygen [23,140,168].
The suspension culture method offers several advantages. It is relatively simple and cost-effective, requiring minimal specialized equipment beyond vessels. The method is highly versatile, accommodating various cell types and allowing for easy incorporation of co-culture systems to model complex cell-cell interactions, such as those between tumor and stromal cells. Furthermore, the suspension culture can be adapted for high-throughput applications, making it suitable for large-scale drug screening and toxicity testing. Despite its strengths, the suspension culture method has limitations. Nutrient and oxygen diffusion can be inadequate in larger spheroids, leading to hypoxic or necrotic cores. This limitation necessitates careful control of spheroid size and medium composition to maintain viability. Additionally, while the method is relatively straightforward, achieving consistent spheroid size and morphology can be challenging without precise control over cell seeding density and culture conditions. Moreover, prolonged culture durations may require frequent medium changes or the use of perfusion systems to sustain spheroid health [7,168].

Recent Advances in Spheroid Seeding Methods

Recent advances in spheroid seeding methods are represented by microencapsulation, bioprinting, nanoparticle-assisted techniques, microfluidics and lab-on-a-chip methods.
Microencapsulation encapsulates cells in biocompatible hydrogels like alginate, mimicking the extracellular matrix (ECM) and facilitating spheroid formation. It promotes intercellular interactions within a controlled microenvironment, protecting cells from shear stress and supporting co-culture systems. However, challenges include nutrient diffusion limitations and difficulties in spheroid retrieval [157,169].
Bioprinting is a method utilizing 3D printing technologies, allowing for the precise placement of cells and biomaterials to replicate native tissue architecture. It offers exceptional control over spheroid organization and is particularly effective for high-throughput applications and heterotypic co-cultures. Limitations include the need for bioink optimization and high costs of equipment [170,171].
Nanoparticle-assisted methods precisely guide cell aggregation into spheroids by leveraging functionalized nanoparticles. Magnetic nanoparticles enable external manipulation, while adhesive ligands support aggregation. It offers reproducibility and integration with imaging or therapeutic applications but raises concerns about nanoparticle cytotoxicity and scalability [39,66,130,172].
Microfluidics and lab-on-a-chip are technologies that provide highly controlled environments for spheroid formation, mimicking in vivo conditions through precise nutrient gradients and mechanical control. Microfluidics supports real-time monitoring and complex co-cultures, although challenges include high costs, technical expertise, and scalability [28,34,50,83,87,101,173].

Magnetic Levitation

The magnetic levitation method is a less frequently used approach to spheroid formation. This method utilizes leveraging magnetic fields to promote cellular aggregation and 3D structure development. This technique involves the use of magnetic nanoparticles that are internalized by cells through incubation. The nanoparticles are typically composed of biocompatible materials such as iron oxide and may be functionalized with extracellular matrix (ECM) proteins or other molecules to enhance cellular uptake and minimize toxicity. After the cells have internalized the nanoparticles, they are exposed to a magnetic field, which forces them to aggregate and suspend in the culture medium. The magnetic field enables the controlled formation of compact spheroids by facilitating cell-cell and cell-ECM interactions [168,174].
Magnetic levitation offers several advantages. It allows for rapid and reproducible spheroid generation and provides a high degree of control over spheroid size and structure. Additionally, this method supports the formation of co-culture spheroids by enabling the simultaneous aggregation of different cell types, which is particularly useful for modeling tumor-stroma or tumor-immune cell interactions. The technique also facilitates the incorporation of ECM components, improving the physiological relevance of the spheroid microenvironment. Furthermore, magnetic levitation is amenable to high-throughput applications and can be easily scaled up for drug screening or other large-scale studies. Despite its advantages, the method has limitations. The requirement for magnetic nanoparticles introduces potential concerns regarding biocompatibility and cellular toxicity, particularly for long-term studies. Additionally, the uniformity of nanoparticle uptake among cells can vary, potentially leading to inconsistencies in spheroid formation. The cost of magnetic nanoparticles and specialized magnetic devices may also be a barrier for some laboratories [7,168,174].

Summary of Spheroid Seeding Method

A summary of advantages and limitations of selected spheroid seeding methods is presented in Table 5.

4. Conclusions

The findings of this systematic review underscore the growing interest in 3D cancer cell models, particularly spheroids, for cancer research, therapeutic testing, and personalized medicine.
Breast cancer emerged as the most investigated cancer source for spheroid seeding, accounting for 25% of the studies included in this review, followed by colon, lung, ovary, and brain cancers. This distribution reflects the cancers' high clinical relevance, particularly in research into tumor progression, drug resistance, and the need for better preclinical models to predict patient responses to therapies.
Among the various methods for spheroid formation, forced floating and scaffold-based methods were the most employed, each used in 71 (32% of all methods) and 41 studies (19% of all methods), respectively. These approaches provide reproducible, easy-to-implement techniques for spheroid generation. Forced floating involves the aggregation of cells in suspension, which then self-assemble into spheroids. This technique has been adopted due to its simplicity and ability to consistently produce spheroids across different cancer types. The use of this method across a wide variety of cancer types underscores its applicability in generating tumor models for drug discovery and testing. Scaffold-based methods involve embedding cells in a 3D matrix, are well-established and widely adopted in cancer research. Both methods facilitate the development of spheroids that closely resemble in vivo tumor environments, with the ability to evaluate drug efficacy and tumor microenvironment interactions. In recent years, more advanced techniques have emerged, contributing to the versatility of spheroid culture. Notably, the hanging drop method is becoming increasingly popular, offering distinct advantages. Hanging drop, which involves placing small drops of cell suspension on an inverted culture dish lid, results in the spontaneous aggregation of cells into 3D spheroids due to gravity and surface tension. While this method is more labor-intensive than forced floating or scaffold-based methods, it offers more physiologically relevant 3D structures and is gaining traction for use in drug screening and tumor modeling.
Whereas these established methods have significantly advanced the field of cancer research, there are still several challenges and limitations in spheroid culture. One major issue is the inherent difficulty in achieving the necessary level of reproducibility and standardization for large-scale therapeutic testing. While methods like forced floating and scaffold-based systems provide relatively consistent spheroid formation, techniques such as hanging drop are more prone to variability depending on experimental conditions. Standardizing spheroid protocols, particularly for high-throughput drug screening, remains an ongoing challenge in the field.
Interestingly, the review also highlighted the increasing application of patient-derived spheroids, which offer a more clinically relevant model by capturing the genetic and phenotypic variability of individual tumors. The ability to generate spheroids from different regions of the same tumor has the potential to capture tumor heterogeneity, which could be critical for personalized medicine approaches. This is especially important for cancers like breast and colon cancer, where the tumor microenvironment and its interactions with various cell types play a key role in metastasis, drug resistance, and immune evasion.
In conclusion, spheroid culture techniques, particularly those employing forced floating, scaffold-based methods, have proven valuable in the study of cancer biology and the testing of novel therapies. However, to move towards more clinically translatable models, additional research is needed to refine the methods, particularly in terms of reproducibility, standardization, and incorporation of tumor heterogeneity. The adoption of patient-derived and co-culture spheroid models may significantly improve the predictive power of in vitro drug testing and lead to better-targeted therapies for cancer patients. This section is not mandatory but can be added to the manuscript if the discussion is unusually long or complex.

Author Contributions

All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Acknowledgments

Not applicable.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
2D Two-dimensional
3D Three-dimensional
ECM Extracellular Matrix
NSCLC Non-small cell lung lymphoma
PEG Polyethylene glycol
Poly-HEMA Poly(2-hydroxyethyl methacrylate
PLGA poly(lactic-co-glycolic acid
SCLC Small cell lung cancer
ULA Ultra-low attachment

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Figure 1. Cellular structure of spheroid.
Figure 1. Cellular structure of spheroid.
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Figure 2. Selection Process.
Figure 2. Selection Process.
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Figure 3. Summary of spheroid sources.
Figure 3. Summary of spheroid sources.
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Figure 4. Summary of spheroid seeding methods.
Figure 4. Summary of spheroid seeding methods.
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Figure 5. Techniques for creation of spheroids.
Figure 5. Techniques for creation of spheroids.
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Table 1. Advantages, limitations and potentials of 2D and 3D models.
Table 1. Advantages, limitations and potentials of 2D and 3D models.
2D models 3D models
Advantages
  • Simplicity and ease of use.
  • Cost-effective and widely available.
  • High-throughput capability.
  • Closer mimicry of in vivo conditions.
  • Replicates tumor microenvironment and cellular interactions (e.g. cell-cell and cell-matrix interactions, hypoxic core).
  • Better simulation of drug penetration and resistance (drug diffusion barriers and heterogeneous cellular responses).
  • Represents gene and protein expression profile that reflects tumors.
Limitations
  • Lack of physiological relevance.
  • Limited replication of cell-cell and cell-matrix interactions.
  • Fails to simulate gradients of oxygen, nutrients, and metabolites.
  • Higher cost and technical complexity.
  • Longer culture time.
  • Scalability challenges.
  • Reproducibility issues in some systems.
Potentials
  • Effective for initial drug screening and basic mechanistic studies.
  • Suitable for large-scale studies with consistent and reproducible outputs.
  • Ideal for studying tumor progression, metastasis, and resistance mechanisms.
  • Promising for personalized medicine applications, including patient-derived models.
Table 2. Articles selected for systematic review.
Table 2. Articles selected for systematic review.
Reference Cancer primary site (histological type) Cell line Spheroid formation method
Agastin S, 2011 [17] Colon (adenocarcinoma), Breast (adenocarcinoma) Colo205, MDA-MB-231 Hanging drop
Alhasan L, 2016 [18] Breast (carcinoma) BT-474 Scaffold-based methods
An HJ, 2020 [19] Kidney (carcinoma) A498 Scaffold-based methods
Árnadóttir SS, 2018 [20] Colon Patient-derived Forced-floating (not defined)
Baek N, 2016 [21] Prostate (carcinoma), Bone (neuroblastoma), Lung (carcinoma), Cervix (adenocarcinoma), Bone (osteosarcoma) DU145, SH-SY5Y, A549, HeLa, HEp2, 0U-2OS Forced-floating (agar coated plates)
Barone RM, 1981 [22] Colon (adenocarcinoma) HT-29 Suspension culture
Bartholomä P, 2005 [23] Breast (carcinoma) T-47D Suspension culture
Boo L, 2020 [24] Breast (adenocarcinoma) MCF-7 Forced-floating (agar coated plates)
Brooks EA, 2019 [25] Ovary (adenocarcinoma) Patient-derived, AU565, BT549, SKOV-3 Scaffold-based methods
Bruns J, 2022 [26] Brain (glioblastoma) Patient-derived, U87 Scaffold-based methods
Calori IR, 2022 [27] Brain (glioblastoma, medulloblastoma) U87, T98G, A172, UW473 Forced-floating (ULA)
Chang S, 2022 [28] Breast (adenocarcinoma) MCF-7 Recent advances
Chen G, 2022 [29] Breast (adenocarcinoma) MCF-7 Forced-floating (ULA)
Chen MC, 2010 [30] Breast (melanoma) LCC6/Her-2 Recent advances
Chen Z, 2021 [31] Breast (adenocarcinoma) MDA-MB-231 Forced-floating (ULA)
Cheng V, 2015 [32] Brain (glioblastoma) U87, U251 Forced-floating (ULA)
Close DA, 2022 [33] Oral (squamous cell carcinoma) Cal33, FaDu, UM-22B, OSC-19 Forced-floating (ULA)
Das T, 2013 [34] Ovary (adenocarcinoma) TOV112D Hanging drop
Das V, 2016 [35] Colon (carcinoma), Colon (adenocarcinoma), Bone (osteosarcoma), Cervix (adenocarcinoma), Colon (adenocarcinoma), Liver (carcinoma) HCT116, HT29, U-2OS, HeLa, Caco-2, HepG2 Forced-floating (liquid overlay)
Das V, 2017 [36] Colon (carcinoma) HCT116 Forced-floating (liquid overlay)
De Angelis ML, 2018 [37] Colon Patient-derived Forced-floating (ULA)
Dhamecha D, 2021 [38] Lung (carcinoma), Bone (osteosarcoma) A549, MG-63 Scaffold-based methods
Dias DR, 2016 [39] Cervix (adenocarcinoma) HeLa Recent advances
Domenici G, 2021 [40] Bone (sarcoma) Patient-derived Forced-floating (ULA)
Dufau I, 2012 [41] Pancreas (adenocarcinoma) Capan-2 Forced-floating (poly-HEMA)
Eetezadi S, 2018 [42] Ovary (carcinoma), Ovary (adenocarcinoma) UWB1.289, UWB1.289+BRCA1, OV-90, SKOV3, PEO1, PEO4, COV362 Forced-floating (ULA)
Eguchi H, 2022 [43] Lung (carcinoma) A549 Forced-floating (ULA)
Eimer S, 2012 [44] Brain (glioblastoma) Patient-derived Forced-floating (ULA)
El-Sadek IA, 2021 [45] Breast (adenocarcinoma) MCF-7 Forced-floating (ULA)
Enmon RM Jr, 2001 [46] Prostate (carcinoma) DU 145 Forced-floating (agar plates)
Flørenes VA, 2019 [47] Skin (Melanoma) Patient-derived Forced-floating (ULA)
Fu J, 2020 [48] Liver (carcinoma), Prostate (carcinoma), Lung (carcinoma), Breast (adenocarcinoma) HepG2, DU 145, A549, MCF-7, MDA-MB-231 Scaffold-based methods
Fu JJ, 2018 [49] Prostate (carcinoma) DU 145, LNCap Scaffold-based methods
Gao Y, 2022 [50] Lung (carcinoma) A549 Recent advances
Gencoglu MF, 2018 [51] Breast (adenocarcinoma), Breast (carcinoma), Prostate (carcinoma), Prostate (adenocarcinoma), Ovary (adenocarcinoma) AU565, BT549, BT474, HCC 1419, HCC 1428, HCC 1806, HCC 1954, HCC 202, HCC 38, ZR75 1, HCC 70, LNCaPcol, PC3, SKOV3 Scaffold-based methods, Microwells, Suspension culture
Gendre DAJ, 2021 [52] Lung (mesothelioma), Lung (adenocarcinoma) H2052, H2052/484, H2452, LuCa1, LuCa61, LuCa62 Scaffold-based methods
Gheytanchi E, 2021 [53] Colon (adenocarcinoma) HT-29, Caco-2 Hanging drop, Forced-floating (Poly-HEMA)
Goisnard A, 2021 [54] Breast (carcinoma), Breast (adenocarcinoma) SUM1315, MDA-MB-231, HCC1937, SW527, DU4475 Forced-floating (ULA)
Guo X, 2019 [55] Ovary (adenocarcinoma), Colon (adenocarcinoma), Pancreas (carcinoma), Prostate (adenocarcinoma) OVCAR3, SW620, PANC-1, PC3 Scaffold-based methods
Hagemann J, 2017 [56] Oral (carcinoma) FaDu, Cal27, UPCI-SCC-154 Forced-floating (ULA), Hanging drop
Han S, 2022 [57] Liver Patient-derived Forced-floating (ULA)
Harmer J, 2019 [58] Brain (glioblastoma) U251, KNS42 Scaffold-based methods
Herter S, 2017 [59] Colon (adenocarcinoma) LS174T, LoVo Hanging drop
Ho WY, 2012 [60] Breast (adenocarcinoma) MCF-7 Forced-floating (liquid overlay)
Ho WY, 2021 [61] Breast (adenocarcinoma) MCF-7 Scaffold-based methods
Hofmann S, 2022 [62] Breast Patient-derived Forced-floating (ULA)
Hornung A, 2016 [63] Colon (adenocarcinoma) HT-29 Scaffold-based methods
Huang Z, 2020 [64] Breast (adenocarcinoma) MDA-MB-231 Scaffold-based methods
Jove M, 2019 [65] Breast (adenocarcinoma) Colorectal (adenocarcinoma) MCF-7, DLD-1 Scaffold-based methods
Ju FN, 2023 [66] Brain (glioblastoma) U87 Recent advances
Karamikamkar S, 2018 [67] Breast (adenocarcinoma) MCF-7 Scaffold-based methods
Karlsson H, 2012 [68] Colon (carcinoma) HCT-116 Forced-floating (ULA)
Karshieva SS, 2022 [69] Colon (carcinoma), Liver (carcinoma) HCT-116, Huh7 Forced-floating (ULA)
Kato EE, 2021 [70] Lung (carcinoma) A549 Hanging drop
Kim CH, 2020 [71] Liver (carcinoma) HepG2 Recent advances
Ko J, 2019 [72] Brain (glioblastoma) U87 Scaffold-based methods
Kochanek SJ, 2019 [73] Oral (carcinoma) Cal33, Cal27, FaDu, UM-22B, BICR56, OSC-19, PCI-13, PCI-52, Detroit-562, UM-SCC-1, and SCC-9 Forced-floating (ULA)
Kochanek SJ, 2020 [74] Oral (carcinoma) Cal33, FaDu, UM-22B, BICR56, OSC-19 Forced-floating (ULA)
Koshkin V, 2016 [75] Breast (adenocarcinoma) MCF-7 Scaffold-based methods
Kroupová J, 2022 [76] Colon (adenocarcinoma) HT-29 Forced-floating (not defined)
Kudláčová J, 2020 [77] Brain (glioblastoma) U87 Forced-floating (ULA)
Kumari P, 2017 [78] Cervix (adenocarcinoma), Lung (carcinoma) HeLa, A549 Scaffold-based methods
Lal-Nag M, 2017 [79] Ovary (adenocarcinoma) Hey-A8–GFP Forced-floating (ULA)
Lama R, 2013 [80] Lung (carcinoma) H292 Scaffold-based methods
Landgraf L, 2022 [81] Prostate (adenocarcinoma), Brain (glioblastoma) PC-3, U87 Forced-floating (liquid overlay)
Le VM, 2016 [82] Lung (carcinoma), Colon (carcinoma), Brain (glioblastoma) 95-D, HCT-116, U87 Scaffold-based methods
Lee SW, 2019 [83] Lung (carcinoma) A549 Recent advances
Lee Y, 2022 [84] Lung (carcinoma) H460, A549 Forced-floating (ULA)
Lemmo S, 2014 [85] Breast (adenocarcinoma) MDA-MB-231 Scaffold-based methods
Li M, 2019 [86] Cervix (carcinoma) C-33-A, DoTC2 4510 Forced-floating (ULA)
Lim W, 2018 [87] Colon (carcinoma), Brain (glioblastoma) HCT-116, U87 Recent advances
Lin ZT, 2021 [88] Breast (adenocarcinoma) MDA-MB-436 Scaffold-based methods
Liu X, 2021 [89] Sarcoma HS-SY-II Recent advances
Lorenzo C, 2011 [90] Pancreas (adenocarcinoma) Capan-2 Forced-floating (poly-HEMA)
Luan Q, 2022 [91] Lung (adenocarcinoma), Lung (carcinoma) HCC4006, H1975, A549 Scaffold-based methods, Forced-floating (ULA)
Madsen NH, 2021 [92] Breast (adenocarcinoma), Colon (adenocarcinoma), Pancreas (carcinoma) MCF-7, HT-29, PANC-1, MIA PaCa-2 Forced-floating (ULA)
Marshall SK, 2022 [93] Bone (osteosarcoma) MG-63 Forced-floating (ULA)
Maruhashi R, 2018 [94] Lung (carcinoma) A549 Forced-floating (ULA)
Melnik D, 2020 [95] Thyroid (carcinoma) FTC-133 Suspension culture
Molyneaux K, 2021 [96] Brain (glioblastoma) LN229, U87, Gli36 Forced-floating (not defined)
Monazzam A, 2007 [97] Breast (adenocarcinoma) MCF-7 Forced-floating (agar plates)
Morimoto T, 2023 [98] Gastric Patient-derived Scaffold-based methods
Mosaad EO, 2018 [99] Prostate (cancer), Prostate (carcinoma) C42B, LNCaP Recent advances
Mueggler A, 2023 [100] Lung Patient-derived Scaffold-based methods
Nashimoto Y, 2020 [101] Breast (adenocarcinoma) MCF-7 Recent advances
Nigjeh SE, 2018 [102] Breast (adenocarcinoma) MDA-MB-231 Forced-floating (agar plates), Forced-floating (ULA)
Nittayaboon K, 2022 [103] Colon (carcinoma) PMF-k014 Forced-floating (poly-HEMA)
Ohya S, 2021 [104] Prostate (carcinoma) LNCaP Forced-floating (ULA)
Oliveira MS, 2016 [105] Breast (adenocarcinoma), Ovary (adenocarcinoma) MCF-7/Adr, NCI/Adr Forced-floating (liquid overlay)
Ono K, 2022 [106] Oral (carcinoma) SAS, HSC-3, HSC-4, OSC-19 Forced-floating (ULA)
Pampaloni F, 2017 [107] Brain (glioblastoma) U343 Forced-floating (liquid overlay)
Park MC, 2016 [108] Brain (glioblastoma) Patient-derived and PC14PE6, PC14PE6_LvBr3, D54, LN428, LN751, U251E4, U87E4, SN-12C, SNU-119, SNU-216, SNU-668, SNU-719, HCC1171, HCC1195, HCC15, HCC1588, HCC2108, HCC44 Forced-floating (not defined)
Pattni BS, 2016 [109] Ovary (adenocarcinoma) NCI/ADR-RES Forced-floating (liquid overlay)
Perche F, 2012 [110] Ovary (adenocarcinoma) NCI/ADR-RES Forced-floating (liquid overlay)
Preda P, 2023 [111] Breast (adenocarcinoma), Brain (glioblastoma) MDA-MB-231, U87 Scaffold-based methods
Pulze L, 2020 [112] Breast (adenocarcinoma) MCF-7 Forced-floating (ULA)
Raghavan S, 2016 [113] Breast (adenocarcinoma), Ovary (adenocarcinoma) MCF-7, OVCAR8 Hanging drop, Forced-floating (liquid overlay)
Raghavan S, 2019 [114] Ovary (adenocarcinoma) A2780, OVCAR3 Hanging drop
Ralph ACL, 2020 [115] Breast (adenocarcinoma), Breast (carcinoma) MCF-7, MDA-MB-231, T47D Hanging drop
Roering P, 2022 [116] Ovary (adenocarcinoma) Patient-derived, CAOV3, OVCAR8 Forced-floating (ULA)
Roudi R, 2016 [117] Lung (carcinoma) A549 Forced-floating (poly-HEMA)
Rouhani M, 2014 [118] Breast (carcinoma) T47D Forced-floating (liquid overlay)
Sakumoto M, 2018 [119] Sarcoma Patient-derived Forced-floating (ULA)
Salehi F, 2020 [120] Breast (adenocarcinoma), Breast (carcinoma) MDA-MB-231, T47D, MCF-7 Forced-floating (liquid overlay), Hanging drop
Sambi M, 2020 [121] Breast (adenocarcinoma) MDA-MB-231 Scaffold-based methods
Sankar S, 2021 [122] Lung (carcinoma) A549 Recent advances
Särchen V, 2022 [123] Sarcoma RH30 Forced-floating (ULA)
Sarıyar E, 2023 [124] Liver (carcinoma) Huh7 Hanging drop
Sauer SJ, 2017 [125] Breast (carcinoma), Breast (adenocarcinoma) SUM149, SUM190, T47D, MCF-7 Forced-floating (ULA)
Shaheen S, 2016 [126] Colon (carcinoma) HCT-116 Forced-floating (not defined)
Shen K, 2014 [127] Breast (adenocarcinoma) MDA-MB-231 Scaffold-based methods
Sheth DB, 2019 [128] Breast (adenocarcinoma) MCF-7 Recent advances
Shortt RL, 2023 [129] Colon (carcinoma) HCT-116 Scaffold-based methods
Singh A, 2020 [130] Breast (adenocarcinoma) MCF-7 Scaffold-based methods
Suhito IR, 2021 [131] Bone (neuroblastoma), Brain (glioblastoma) SH-SY5Y, U-87 Recent advances
Tanenbaum LM, 2017 [132] Ovary (adenocarcinoma) UCI101, A2780 Forced-floating (not defined)
Tang S, 2017 [133] Colon (adenocarcinoma), Ovary (adenocarcinoma) HT-29, SKOV-3 Hanging drop
Taubenberger AV, 2019 [134] Breast (adenocarcinoma) MCF-7 Scaffold-based methods
Terrones M, 2024 [135] Lung (adenocarcinoma) HCC78 Forced-floating (ULA)
Tevis KM, 2017 [136] Breast (adenocarcinoma) MDA-MB-231 Scaffold-based methods
To HTN, 2022 [137] Stomach (carcinoma) SNU-216, SNU-484, SNU-601, SNU-638, SNU-668, and SNU-719 Forced-floating (ULA)
Torisawa YS, 2007 [138] Breast (adenocarcinoma), Liver (carcinoma) MCF-7, HepG2 Recent advances
Uematsu N, 2018 [139] Breast (adenocarcinoma) MCF-7 Recent advances
Varan G, 2021 [140] Lung (carcinoma), Liver (carcinoma) A549, HepG2 Forced-floating (poly-HEMA)
Vinci M, 2012 [141] Brain (glioblastoma), Oral (carcinoma), Breast (adenocarcinoma) U87, KNS42, LICR-LON-HN4, MDA-MB-231 Forced-floating (ULA), Agarose plates
Wan X, 2016 [142] Colon (adenocarcinoma), Ovary (adenocarcinoma) DLD-1, NCI/ADR Scaffold-based methods
Wang Y, 2014 [143] Cervix (adenocarcinoma) HeLa Scaffold-based methods
Ware MJ, 2016 [144] Pancreas (carcinoma) PANC-1, AsPc-1, BxPC-3, Capan-1, MIA PaCa-2 cells Hanging drop
Wen Z, 2013 [145] Pancreas (carcinoma) MIAPaCa-2, PANC-1 Scaffold-based methods
Wenzel C, 2014 [146] Breast (carcinoma) T47D Forced-floating (liquid overlay)
Weydert Z, 2020 [147] Ovary (adenocarcinoma) HEY, SKOV-3 Hanging drop
Wu G, 2019 [148] Liver (carcinoma) HepG2, Huh7 Scaffold-based methods
Wu KW, 2020 [149] Bladder (carcinoma), Lung (carcinoma), Liver (carcinoma) T24, A549, Huh-7 Recent advances
Xia H, 2020 [150] Brain (glioblastoma) LN229, U87 Scaffold-based methods
Xiong Q, 2023 [151] Bladder Patient-derived Forced-floating (ULA)
Yamawaki K, 2021 [152] Ovary Patient-derived Forced-floating (ULA)
Yoshida T, 2019 [153] Bladder Patient-derived Scaffold-based methods
Yu L, 2015 [154] Breast (adenocarcinoma) MCF-7 Recent advances
Yu Q, 2021 [155] Breast (adenocarcinoma) MDA-MB-436, MDB-MB-231 Scaffold-based methods
Zhang JZ, 2012 [156] Colon (adenocarcinoma), Ovary (teratocarcinoma) DLD-1, PA-1 ovarian cancer cells Forced-floating (liquid overlay)
Zhang JZ, 2012 [157] Colon (adenocarcinoma) DLD-1 Forced-floating (liquid overlay)
Zhang X, 2005 [158] Breast (adenocarcinoma) MCF-7 Recent advances
Zuchowska A, 2017 [159] Liver (carcinoma) HepG2 Recent advances
Table 3. Summary of spheroid sources.
Table 3. Summary of spheroid sources.
Spheroid formation method Number of studies Percentage of total number of studies
Forced-floating 70 31.8%
Scaffold-based 41 18.6%
Recent advances 21 9.5%
Hanging drop 14 6.4%
Suspension culture 4 1.8%
Magnetic levitation 0 0.0%
Table 4. Summary of spheroid seeding methods.
Table 4. Summary of spheroid seeding methods.
Spheroid formation method Number of studies Percentage of total number of studies
Forced-floating 70 31.8%
Scaffold-based 41 18.6%
Recent advances 21 9.5%
Hanging drop 14 6.4%
Suspension culture 4 1.8%
Magnetic levitation 0 0.0%
Table 5. Summary of advantages and limitations of different seeding methods.
Table 5. Summary of advantages and limitations of different seeding methods.
Method Advantages Limitations
Forced floating method
  • Simple and scalable
  • Produces uniform spheroids
  • Compatible with automation
  • Cost-effective
  • Spheroid integrity varies with cell density
  • Limited nutrient and oxygen diffusion for large spheroids
Scaffold-based
  • Mimics extracellular matrix (ECM)
  • Supports long-term cultures
  • Allows co-cultures
  • Highly physiological
  • Variability in size and shape
  • High cost of scaffolds
  • Complexity in interpreting scaffold-induced effects
Hanging drop method
  • Low cost
  • Produces uniform spheroids
  • Minimal mechanical damage
  • Control over spheroid size
  • Labor-intensive
  • Limited scalability
  • Potential damage during transfer
  • Limited nutrient exchange
Suspension culture
  • Versatile
  • Simple and cost-effective
  • Suitable for high-throughput
  • Closer mimicry of in vivo conditions
  • Nutrient and oxygen limitations in large spheroids
  • Consistency challenges in spheroid size
Microencapsulation
  • Provides controlled microenvironment
  • Supports co-cultures
  • Protects from shear stress
  • Nutrient diffusion limitations
  • Challenges in retrieving spheroids
Bioprinting
  • Precise spheroid placement
  • High control over architecture
  • Effective for high-throughput applications
  • Requires optimization of bioinks
  • Expensive equipment
Nanoparticle-assisted techniques
  • Enable precise aggregation
  • Integrate with imaging/therapeutics
  • Reproducible
  • Potential cytotoxicity of nanoparticles
  • Scalability concerns
Microfluidics and lab-on-a-chip
  • Controlled environment
  • Mimics in vivo gradients
  • Real-time monitoring
  • Supports co-cultures
  • High cost
  • Requires technical expertise
  • Limited scalability
Magnetic levitation
  • High control over size
  • Supports co-cultures
  • Possible to adapt to high-throughput
  • Rapid and reproducible
  • Potential toxicity of nanoparticles
  • Inconsistencies in particle uptake
  • Equipment costs
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