Revolutionizing cancer care: Bioprinting prostate cancer stem cells for targeted treatments

Abstract

Prostate cancer (PCa), one of the leading causes of cancer-related mortality in men worldwide, presents significant challenges due to its heterogeneity and the presence of cancer stem cells (CSCs), which contribute to therapy resistance and metastasis. Advances in three-dimensional (3D) bioprinting have ushered in a new era of precision medicine by enabling the recreation of complex tumor microenvironments. This review highlights the transformative potential of 3D bioprinting technology in modelling prostate cancer stem cells (PCSCs) to identify therapeutic vulnerabilities and develop targeted treatments. By integrating bioinks with PCSCs and their niche components, 3D bioprinting offers a robust platform to investigate the molecular and cellular mechanisms underlying PCa progression and resistance. Furthermore, it allows high-throughput drug screening, cellular cross talks, facilitating the discovery of novel interventions aimed at eradicating CSCs while preserving healthy tissue. The review also discusses the challenges of scalability, bioink optimization, and clinical translation, alongside emerging technologies such as organ-on-chip systems and bioprinted metastatic models. This review underscores the promise of bioprinting as a disruptive innovation in cancer care, capable of redefining therapeutic approaches and offering hope for better patient outcomes in PCa.

Key Words: 3D bioprinting; Prostate cancer stem cells; Cancer therapy; Precision medicine; Tumor microenvironment; Drug screening

Core Tip: Three-dimensional (3D) bioprinting is revolutionizing prostate cancer (PCa) research by replicating tumor microenvironments, enabling drug screening, and advancing personalized medicine. By mimicking the extracellular matrix and incorporating stromal and immune components, bioprinted models enhance physiological relevance. This technology facilitates targeted therapies by screening novel drugs tailored to individual patient profiles. However, challenges such as scalability, bioink optimization, and regulatory frameworks remain. Advances in microfluidic-assisted printing and artificial intelligence driven optimization can improve reproducibility. Integrating bioprinted models with organ-on-a-chip systems further enhances translational research. Collaborative efforts will accelerate clinical applications, positioning 3D bioprinting as a game-changer in personalized PCa treatment.

INTRODUCTION

PCa and the challenge of CSCs

Prostate cancer (PCa) is among the most prevalent malignancies in men and remains the second leading cause of cancer-related mortality worldwide. PCa alone accounts for 30% of diagnoses of all incident cases in men[1]. Adding to its complexity, PCa exhibits at least seven distinct molecular subtypes, which significantly complicates treatment strategies[2,3]. While localized PCa can often be managed through surgery or radiotherapy, advanced and metastatic disease presents a far greater therapeutic challenge. Despite advancements in treatment and diagnostic methods, PCa remains a significant healthcare burden due to its heterogeneity and resistance to conventional chemo- and radiotherapies. A major contributor to this resistance is the presence of prostate cancer stem cells (PCSCs), a tumor-initiating subpopulation with self-renewal and differentiation capabilities[4]. PCSCs drive therapy resistance, recurrence, and metastasis, highlighting the urgent need for advanced models that can enhance our understanding of their biology and facilitate the screening of targeted interventions[5].

Need for advanced models in cancer research

PCa is a heterogeneous malignancy with a complex cellular composition, consisting of both differentiated cancer cells and a subpopulation of therapy-resistant CSCs[6]. PCSCs express key stemness markers such as CD44, CD133, and ALDH1, which contribute to their tumor-initiating potential and resistance to chemotherapy and radiation therapy[7,8]. These characteristics make PCSCs a critical target for developing more effective therapeutic strategies. Conventional cancer models, such as two-dimensional (2D) cell cultures and xenografts, fail to replicate the intricate and dynamic interactions between PCSCs and the tumor microenvironments (TME)[9]. This limitation contributes to inconsistencies in drug response studies and impedes progress in understanding tumor development. Additionally, animal models often exhibit species-specific differences that restrict their direct applicability to human diseases, making it challenging to translate preclinical research findings into clinical applications[10-12]. PCSCs are a rare yet pivotal subpopulation within prostate tumors, defined by their ability to self-renew and differentiate into multiple cell types. These properties contribute significantly to tumor heterogeneity, progression, and long-term maintenance[13,14]. PCSCs are identified by a specific set of surface and intracellular markers, including CD44, CD133, integrin α2β1, OCT4, SOX2, NANOG, EZH2, and c-MYC. These markers not only help distinguish PCSCs from other tumor cells but are also functionally involved in maintaining their stem-like state[13,15]. Several signaling pathways are found to be hyperactivated in PCSCs, such as PTEN/Akt/PI3K, Notch, RAS-RAF-MEK-ERK, and Hedgehog. These cascades promote survival, proliferation, and resistance to treatment, making PCSCs particularly difficult to eliminate through conventional therapy[15]. In vitro, PCSCs demonstrate high clonogenicity and can form spheres under non-adherent culture conditions—features that underscore their tumor-initiating potential[16,17]. Additionally, PCSCs display plasticity, enabling them to undergo phenotypic changes such as epithelial–mesenchymal transition (EMT) and to adapt in response to therapeutic or microenvironmental pressures[13]. One of the most clinically concerning aspects of PCSCs is their resistance to standard therapies like chemotherapy, radiotherapy, and androgen deprivation therapy. These treatments often fail to eliminate PCSCs, allowing them to survive, repopulate the tumor, and lead to relapse or metastasis. In some cases, treatment-induced damage may even trigger the activation of dormant PCSCs, accelerating disease progression[14,15]. Given these characteristics, targeting PCSCs directly is considered a promising avenue to overcome resistance and achieve long-term remission in PCa patients.

Plasticity and subtype differentiation potential of PCSCs

PCSCs exhibit remarkable plasticity, enabling them to differentiate into various cell types within the prostate, including basal, luminal, and neuroendocrine cells. This differentiation capacity contributes to the tumor’s heterogeneity and complexity. Studies have shown that PCSCs can adapt to different microenvironmental cues, influencing their differentiation pathways and potentially leading to the emergence of diverse molecular subtypes of PCa. Advancements in three-dimensional (3D) bioprinting technology offer a promising platform to replicate the intricate TME of the prostate. By precisely controlling the spatial arrangement of cells, extracellular matrix (ECM) components, and signaling molecules, 3D bioprinted models can mimic the in vivo conditions that influence PCSC behavior. While direct evidence of PCSCs differentiating into all seven recognized molecular subtypes within a bioprinted model is still emerging, the technology provides a valuable tool for studying the factors that drive subtype specification and for developing personalized therapeutic strategies[18].

3D BIOPRINTING: AN EMERGING TOOL IN CANCER RESEARCH

3D bioprinting is a groundbreaking technology that constructs biological scaffolds through the layer-by-layer deposition of bioinks composed of living cells and biomaterials. This approach enables the fabrication of intricate, tissue-like structures that closely mimic human tissues, making it highly valuable for cancer research[19]. One of its most significant advantages is its ability to generate tumor models that accurately reflect in vivo tumor development. These models offer more profound insights into cancer progression and facilitate the development of precise drug testing. For instance, researchers can bioprint miniature tumor constructs and analyze their response to various treatments in a controlled environment[20]. Another promising application of 3D bioprinting is in personalized medicine. By utilizing a patient’s own cells, clinicians can bioprint tumor models tailored to an individual's cancer profile. This approach enables the preclinical testing of multiple therapeutic options, reducing reliance on trial-and-error methods and optimizing treatment selection. Such advancements hold great potential for enhancing precision medicine and improving patient outcomes[9,21]. To address these limitations, 3D bioprinting has emerged as a cutting-edge approach capable of replicating TMEs with high fidelity. This technology enables the precise spatial arrangement of cells, ECM structures, and bioactive molecules within printed tumor spheroids, providing a robust platform for studying PCSC behavior and screening novel therapeutic compounds. By accurately mimicking the native TME, 3D bioprinting holds great promise for advancing personalized treatment strategies and overcoming therapy resistance in PCa. 3D bioprinting has emerged as an innovative solution to overcome these barriers. By generating physiologically relevant tumor models, 3D bioprinted systems provide a more accurate representation of human tumor biology, enabling a deeper understanding of cancer progression and facilitating the development of more effective therapeutic strategies[22]. This technology holds great promise for enhancing cancer research, drug screening, and precision medicine approaches in the treatment of PCa.

BIOPRINTING PCSCS

The ability to generate patient-specific 3D bioprinted tumor models in a clinically relevant timeframe is critical for enabling personalized treatment strategies. Encouragingly, recent technologies such as the patient tumor-3D bioprinting platform have significantly shortened this timeline. Studies have shown that functional tumor constructs can be created in as little as 8 days, which is fast enough to inform early treatment planning, even before standard therapies begin[23]. This approach has already been tested with high success rates across multiple cancers, including ovarian, colorectal, and hepatobiliary cancers, making it highly adaptable for PCa applications as well[23]. The process includes tissue collection, cell isolation, 3D model design using patient imaging, bioprinting with bioinks, and a brief maturation phase to establish a functional TME (Figure 1)[24]. While the availability of viable patient-derived cells can influence the timeline, the overall workflow has become increasingly efficient and reproducible[24]. This advancement brings us closer to a future where clinicians could use bioprinted models not only to understand tumor behavior, but also to test treatments in real-time, enabling personalized decisions during a critical treatment window[23,24]. The cost of developing patient-specific 3D bioprinted tumor models can vary widely depending on several factors, including the type of bioprinter used, the complexity of the tissue being replicated, and the level of customization required. High-resolution, multi-material bioprinters—essential for creating intricate, functional tumor constructs—can cost anywhere from $100000 to over $1 million, depending on their features and capacity[25]. Additionally, bioinks composed of patient-derived cells, growth factors, and ECM components incur significant recurring costs, with pricing influenced by both the biological composition and printing volume[26]. Other crucial expenses include advanced imaging and modeling software, laboratory infrastructure, and trained technical personnel—all of which are essential to ensure precision, sterility, and reproducibility in the printing process[27]. While simpler 3D printed models for surgical planning or teaching purposes may cost just $100 to $1000 per model, generating complex, patient-specific tumor replicas for clinical decision-making is considerably more resource-intensive[28]. These models often require several days of cell expansion, post-printing tissue maturation, and functional validation—all of which add to the cost and labor. Still, as the technology continues to advance, many of these costs are expected to decrease, especially with standardization of protocols and broader access to bioprinting platforms[26,27]. In the long run, the potential of 3D bioprinted models to improve therapeutic precision and reduce trial-and-error treatments could make them not only scientifically valuable, but also cost-effective from a healthcare perspective.

Figure 1 Workflow of patient-specific 3D bioprinting of prostate cancer stem cells: The schematic illustrates the stepwise workflow involved in generating patient-specific 3D bioprinted models of prostate cancer stem cells. The process begins with tissue collection from prostate cancer patients, followed by cell isolation and enrichment of prostate cancer stem cells (PCSCs). Patient imaging data (e.g., magnetic resonance imaging/computed tomography scans) are used to design anatomically relevant 3D models. Using optimized bioinks, the PCSCs are bioprinted into spatially organized constructs that replicate the native tumor microenvironment. A brief maturation phase allows the construct to stabilize and develop key structural and functional properties, enabling applications in drug screening, mechanistic studies, and personalized therapy design.

Bioinks and their role in tumor microenvironment recreation

Advancements in bioinks have revolutionized 3D bioprinting, enabling the recreation of physiologically relevant TMEs. Bioinks, composed of natural or synthetic biomaterials, serve as a supportive matrix that replicates the ECM while facilitating precise cellular interactions, biochemical gradients, and mechanical properties crucial for tumor progression studies[29]. Decellularized ECM (dECM)-based bioinks closely mimic native tissue environments, preserving biochemical cues essential for tumor growth. Studies have demonstrated that dECM bioinks derived from various tissues enhance cell adhesion, proliferation, and differentiation, providing an optimal microenvironment for cancer cell behavior studies[30]. Similarly, hydrogel-based bioinks—such as those formulated from alginate, gelatin, and hyaluronic acid—are widely used due to their biocompatibility and ability to support tumorstromal cell co-cultures[29,31]. Additionally, hybrid bioinks incorporating both natural and synthetic polymers offer enhanced mechanical stability without compromising bioactivity, enabling long-term cancer modeling[32]. In TME research, bioprinted models incorporating bioinks have successfully replicated vascularized tumor niches, immune interactions, and drug resistance mechanisms[30,32]. These models serve as advanced platforms for drug screening and precision oncology, accurately capturing tumor-immune crosstalk and ECM remodeling. Further refinement of bioinks—prioritizing biomimicry, mechanical stability, and printability—will be essential for establishing 3D bioprinting as a transformative tool in cancer research[30].

Understanding the PCSC niche and its role in therapy resistance

The TME—and specifically the PCSC niche—plays a crucial role in preserving PCSC properties such as self-renewal, differentiation, and resistance to conventional therapies. It is a highly dynamic and complex system composed of multiple interacting components, including stromal cells, immune cells, and the ECM. These elements continuously communicate to regulate cancer stemness, influence cellular behavior, and shape tumor responses to therapy. Notably, the PCSC niche serves as a protective reservoir, shielding PCSCs from standard treatments such as chemotherapy and radiation[33]. Stromal cells within the PCSC niche, including endothelial cells and fibroblasts, provide essential support through direct cell–cell interactions and the secretion of signaling molecules. Immune cells, such as myeloid-derived suppressor cells and tumor-associated macrophages (TAMs), play a dual role in either promoting or inhibiting PCSC proliferation while also contributing to drug resistance mechanisms. The ECM, acting as a structural scaffold, not only maintains tumor integrity but also facilitates biochemical signaling that governs PCSC maintenance, migration, and survival[33]. One of the most critical factors within the PCSC niche is hypoxia, or low oxygen levels, a hallmark of solid tumors. Due to rapid proliferation and inadequate vascularization, tumor cells—particularly PCSCs—are frequently subjected to hypoxic conditions. Hypoxia triggers a cascade of molecular responses, primarily through the activation of hypoxia-inducible factors (HIFs). Among them, HIF-1α plays a pivotal role in metabolic reprogramming, angiogenesis, and therapy resistance. Hypoxia-driven mechanisms enhance PCSC survival by: (1) Upregulating drug efflux pumps, which reduce intracellular drug accumulation; (2) Modulating cell cycle checkpoints, allowing PCSCs to evade chemotherapy-induced cell death; and (3) Inducing EMT, a process that enhances invasiveness and metastatic potential. These adaptations significantly contribute to chemoresistance and radioresistance, making hypoxia a key therapeutic challenge in PCa treatment[34]. Cytokine signaling pathways and their role in PCSC maintenance Cytokine signaling plays a crucial role in the maintenance of PCSCs and the regulation of stemness. Several key signaling pathways—Wnt, Notch, and Hedgehog—are particularly responsible for sustaining PCSC self-renewal and proliferative capacity. Dysregulation of these pathways has been strongly associated with therapy resistance, tumor relapse, and metastasis.

WNT SIGNALING AND PCSC SURVIVAL

The Wnt signaling pathway is a key regulator of stem cell fate, survival, and proliferation. Its dysregulation has been implicated in numerous cancers, leading to the enrichment of PCSC populations and their resistance to chemotherapy-induced apoptosis. In particular, the Wnt/β catenin pathway enhances the expression of stemness-associated and drug-resistant genes, including those involved in cell cycle regulation and DNA repair[35].

NOTCH SIGNALING AND TUMOR RELAPSE

The Notch signaling pathway is essential for the preservation of the stem cell niche, controlling PCSC self-renewal and differentiation. Aberrant Notch signaling results in PCSC accumulation within tumors, significantly contributing to tumor relapse and metastasis following treatment. Targeting Notch signaling has been proposed as a promising therapeutic strategy to reduce PCSC populations and enhance tumor sensitivity to chemotherapy[36].

HEDGEHOG SIGNALING AND DRUG RESISTANCE

Originally recognized for its role in developmental processes, the Hedgehog signaling pathway also plays a critical role in cancer stem cell regulation. Hedgehog activation sustains and expands PCSC populations, promoting drug resistance. By activating downstream targets, this pathway enables PCSCs to evade chemotherapy, maintain an undifferentiated state, and drive tumor regrowth and metastasis[33].

THE ROLE OF THE TME IN THERAPY RESISTANCE

The interaction between PCSCs and their microenvironment plays a pivotal role in the development of therapy resistance. The complex network of cytokines, growth factors, and cellular components within the PCSC niche protects CSCs from the cytotoxic effects of therapy. For example, the interaction between PCSCs and TAMs can enhance immunosuppression within the tumor, weakening the immune response and increasing resistance to immunotherapies. Additionally, ECM components may physically shield PCSCs from chemotherapy drugs, further reducing treatment efficacy[35]. Moreover, the dynamic nature of the tumor niche allows PCSCs to rapidly adapt following treatment. Therapy-induced stress can trigger the release of cytokines and growth factors, activating pro-survival signaling pathways in PCSCs. This adaptation enhances their ability to withstand harsh conditions, further contributing to drug resistance, particularly against therapies targeting rapidly proliferating cells[22].

STRATEGIES FOR BIOPRINTING PCSCS AND THEIR MICROENVIRONMENT

Bioprinting holds significant potential in advancing our understanding of PCa growth, metastasis, and treatment resistance. However, it remains a complex process since tumors are composed not only of cancer cells but also various supporting structures, including stromal cells, blood vessels, and signaling molecules, all of which influence tumor behavior[37,38].

Key steps in bioprinting PCSCs

Selection of an appropriate bioink: A crucial step in bioprinting PCSCs is choosing a suitable bioink. The selected bioink must support cell viability and promote physiologically relevant behavior. Hydrogel-based bioinks, such as alginate and gelatin, are commonly used as they provide a cushioning, tissue-like matrix conducive to cell growth. The mechanical properties of the bioink are critical—if too rigid, cells may not function naturally, while if too soft, the structure may lack stability and deform[38,39].

Incorporation of growth factors: Growth factors are essential in maintaining the stemness of PCSCs and mimicking the TME. The inclusion of factors such as epidermal growth factor and fibroblast growth factor in bioprinted models enhances the survival, proliferation, and self-renewal capacity of PCSCs, closely resembling the physiological TME[37].

Co-culturing with stromal cells: Stromal cells, which naturally exist within tumors, play a vital role in cancer progression and drug resistance. By co-culturing PCSCs with stromal cells in a bioprinted model, researchers can better study the cellular interactions that drive tumor development and therapeutic resistance[39,40].

UTILIZING ADVANCED BIOPRINTING TECHNIQUES

Not all bioprinting methods are equally effective in creating realistic tumor models. Extrusionbased bioprinting is commonly employed as it allows for precise spatial arrangement of different cell types within the tumor structure. This technique is particularly valuable for replicating the heterogeneous cellular composition of tumors, thereby enhancing the model’s relevance for drug testing and cancer research[38,40].

IMMUNE COMPONENT INTEGRATION

The addition of TAMs and regulatory T cells (Tregs) to 3D bioprinted models of PCa is now widely seen as crucial in terms of accurately modeling the TME. TAMs, especially those with an M2-like profile, support cancer development by inducing angiogenesis, matrix remodeling, and immune suppression through the release of cytokines like interleukin-10 and transforming growth factor beta[41-43]. In parallel, Tregs, as defined by FOXP3 expression, suppress immunosuppression by downregulating cytotoxic T cell responses and are often enriched in highly aggressive prostate tumors[44,45]. The lack of these immune cell subsets restricts the physiological significance of in vitro models, especially when investigating immune evasion or assessing immunotherapies. Incorporation of TAMs and Tregs within 3D bioprinted structures facilitates the modeling of intricate cellular interaction within the TME, thus improving the platform's predictive ability for drug testing and mechanistic studies[38,46].

APPLICATIONS OF 3D BIOPRINTING IN PCA THERAPY

The use of PCSCs in 3D bioprinting enables the creation of highly representative tumor models that closely mimic the TME in terms of cellular composition, structural organization, and biochemical gradients[9]. Personalized tumor models generated through 3D bioprinting significantly improve drug screening efficiency by allowing for high-throughput testing of multiple therapeutic agents simultaneously. Unlike traditional 2D cell culture models, which fail to replicate the complexities of tumors, bioprinted models provide a more physiologically relevant platform to evaluate the response of PCa cells to treatment. This can lead to better predictions of drug efficacy, as well as the identification of biomarkers indicative of treatment response or resistance (Table 1)[5]. Bioprinted models can handle multiple drug candidates simultaneously, speeding up the process of identifying promising compounds. Assess tumor-specific responses: Since each model can be patient-specific, drugs can be tested on models derived from a variety of patient samples, leading to insights into how different genetic profiles respond to therapy. Model complex biological processes: With 3D models that look super realistic and mimic the environment tumors live in, scientists are studying how drugs actually work better. This research actually simulates things like how a drug passes through the body, how fast it spreads through that body, and how it is processed internally. This new method is definitely elevating accuracy levels greatly[19]. Essentially, 3D bioprinted PCa models allow for the quick discovery of drug candidates with potential for clinical use, streamlining the screening process and potentially making it more predictive of actual therapeutic results. Personalized Medicine and Therapeutic Optimization: Perhaps the most exciting potential for 3D bioprinting in the treatment of PCa is as a tool in personalized medicine. PCa is extremely heterogeneous, with varying genetic mutations, molecular profiles, and therapeutic responses among patients. Personalized medicine seeks to tailor treatment plans based on these variations, providing the patient with the best therapy for their individual tumor profile. With 3D bioprinting, patient-derived cells can be used to create personalized PCa models, enabling the production of individualized models representative of the patient's own cancer biology. This method enables the establishment of patient-specific therapeutic strategies. Let's take an example of how patient specific stem cells called PCSCs are really useful. Scientists use them to make models of tumors that mirror precisely the same genetic and molecular makeup of the cancer in the specific patient they're studying. So it’s like cloning cancer just right down to its genetic details - something that can tell them a huge amount about a particular cancer and help them find better treatments. This allows us to directly test different treatments on the tumor model that the patient has in order to figure out which is the best approach (Figure 2). The individualized nature of such 3D models makes it possible for researchers to test single drug responses: Using 3D bioprinted models that have been derived from a patient's tumor, clinicians can evaluate the efficacy of current as well as potential drugs prior to giving them to the patient. Rationalize treatment regimens: Scientists can make treatments really effective by trying different groups of doctors' drugs or adjusting the amount of drugs according to what makes certain tumors resistant, and this tumor resistance can also be tested using models that look three dimensions like a real tumor Bioprinted models can be utilized over time to monitor the progression of a patient's tumor and its response to therapy, gaining important information about how the tumor changes and if resistance arises. PCSCs are associated with drug resistance and recurrence. Using models based on PCSCs, scientists make sense of how different treatments influence stem cell populations and whether new drugs can go after those that are very resistant and so help stop relapses. The personalized kind of treatment is critical for dealing with PCa. Treatments vary a lot among different people it’s very important to treat each patient with care and in their own unique way. Through the use of 3D bioprinted tumor models, researchers and clinicians can better anticipate therapeutic success, minimizing the trial-and-error approach of existing PCa treatments and enhancing patient outcomes[9,47-49]. Therapeutic Development: Beyond just test for medicine and deciding how to treat individual patients, 3D bioprinting plays a big role helping to develop new ways to treat PCa. This can involve things like targeting cancer directly, letting the body's own immune system fight off the cancer cells as well as using changes to genetic material to go after it. So when new ways to treat different diseases crop up and evolve, 3D printing has big ideas for making this happen better, faster and allowing for a more tailored approach. For instance, targeted therapies: Scientists can also use 3D printed things that look a lot like actual living cells to try out super specific medicines to fix PCa. By pricking away at those cancer cells directly through the creations, doctors can see if the right medicine to target those specific changes really works in those cells. For example, targeting androgen receptor signaling, which is commonly dysregulated in PCa, can be assayed in a more in vivo-like setting. Immunotherapy: Immunotherapies for cancer, such as checkpoint inhibitors and CAR-T cell treatments, need a complete knowledge of the tumor environment. 3D models of PCa enable assessment of how immune cells influence tumor cells, including gaining a deeper insight into immune reactions and optimal ways to carry out immunotherapy[22]. Gene therapies: Gene changes may be tried using 3D bioprinted models to evaluate the efficacy of gene-directed therapies for mutation correction or in improving the capacity of the immune system to target cancer[39].

Figure 2 Standard vs personalized medicine in cancer treatment: The figure illustrates the distinction between standard and personalized medicine approaches in cancer treatment. A: Standard medicine: Patients receive generalized treatment based on broad clinical guidelines, often leading to variable responses due to tumor heterogeneity; B: Personalized medicine: Patient-derived tumor cells are used to create bioprinted tumor models, enabling preclinical drug testing tailored to the individual’s cancer profile. This approach enhances treatment efficacy, minimizes adverse effects, and optimizes therapeutic outcomes.

Table 1 Comparison of Traditional and 3D bioprinted models in exploring prostate cancer stem cell microenvironment and therapeutic resistance.

Traditional models	3D bioprinted models
2D cell cultures- lack tumor architecture- no microenvironment mimicry	3D architecture- mimics in vivo structures- maintains ECM and gradients
Animal models-species differences- limited personalization	Patient-specific models- derived from patient cells- enables personalized medicine
Simplistic TME- Incomplete PCSC interactions- low cell heterogeneity	Complex TME- includes stromal & immune cells- High fidelity of PCSC niche
Static drug testing- poor predictability- no adaptive mechanisms	Dynamic drug screening- mimics drug diffusion & hypoxia- Real-time therapy testing
Limited resistance modeling- misses EMT, hypoxia response	Therapy resistance replication- includes hypoxia, EMT, cytokine crosstalk
Slow, costly translational gaps	High-throughput & scalable- faster treatment planning- organ-on-chip integration possible

PCSC: Prostate cancer stem cell; EMT: Epithelial–mesenchymal transition.

INVESTIGATING TUMOR PROGRESSION AND METASTASIS

One of the most remarkable applications of 3D bioprinting in cancer research is its ability to replicate the complex processes of tumor growth and metastasis. Bioprinted tumor models enable the creation of highly biologically accurate structures that closely mimic real tumor behavior. By utilizing patient-derived PCSCs, these models allow scientists to study cancer progression from a localized tumor to metastatic disease with greater precision. Comprehensive TME Modeling: Bioprinted models can incorporate tumor cells, stromal cells, immune cells, and vascular structures, providing a more realistic TME for research. One of the most critical aspects of cancer metastasis is angiogenesis, as tumors require functional blood vessels to grow and spread. In bioprinted tumor models, the inclusion of vascular networks is essential for understanding how cancer cells invade surrounding tissues and disseminate through the bloodstream. Additionally, integrating immune cells into bioprinted scaffolds creates a dynamic model that helps unravel the mechanisms by which PCa cells—particularly PCSCs—evade immune detection. Cancer cells often develop strategies to alter immune recognition, allowing them to escape destruction. By studying these immune-tumor interactions in a controlled 3D environment, researchers can investigate the molecular basis of immune evasion and identify potential therapeutic targets to enhance immune system recognition and response. Implications for Cancer Therapy: The ability to study tumor migration, invasion, and immune evasion in a controlled 3D bioprinted model provides critical insights into metastasis mechanisms. These insights can aid in: (1) Identifying therapeutic targets to block metastatic progression; (2) Developing novel strategies to enhance immune system detection of PCa cells; and (3) Testing potential treatments aimed at disrupting cancer cell invasion or amplifying immune responses for more effective tumor eradication. By leveraging 3D bioprinting, researchers can explore innovative anti-metastatic therapies, paving the way for more precise and effective cancer treatments.

UNRAVELLING CELLULAR CROSSTALK IN THE TME

The TME is a highly dynamic and complex ecosystem composed of multiple interacting cell types that collectively influence tumor behavior, growth, and treatment response. Tumor cells coexist with various non-tumor-associated cell types, including stromal cells, immune cells, endothelial cells, and ECM components. These cellular elements play a crucial role in tumor progression, metastasis, and resistance to therapy by regulating intricate crosstalk within the TME[50].

3D BIOPRINTING: A SUPERIOR TOOL FOR TME MODELING

Bioprinting offers an advanced approach to replicating the complexities of the TME compared to conventional simulation techniques. By developing 3D co-culture platforms, researchers can bioprint tissue constructs that enable the study of cellular interactions within the TME[48]. For example, bioprinted models of PCa can integrate stromal cells, such as fibroblasts, which are known to promote tumor progression, invasion, and drug resistance. Additionally, immune cells—such as TAMs and T cells—can be incorporated to investigate how the TME suppresses immune activity and facilitates immune evasion, a key factor in cancer progression[22]. Furthermore, bioprinted models enable the study of endothelial cells in tumor angiogenesis, the process by which new blood vessels form from preexisting ones, a critical step in tumor development and metastasis. Understanding how cancer cells interact with endothelial cells to induce angiogenesis is vital for developing therapeutic strategies aimed at cutting off the tumor’s nutrient supply.

MODELING BIOCHEMICAL GRADIENTS AND TUMOR EVOLUTION

3D bioprinted co-culture systems also replicate the physical and biochemical gradients that define tumor physiology—such as nutrient, oxygen, and pH gradients. These gradients influence key cancer traits, including invasion, stemness, plasticity, and therapeutic resistance. Studying how these gradients affect cellular interactions in bioprinted TME models can provide novel insights into cancer evolution and resistance mechanisms[30]. Additionally, bioprinted models allow for the investigation of individual genetic alterations in both tumor cells and the TME, enabling researchers to explore how genetic variability shapes cellular interactions and therapeutic responses. By developing patient-specific bioprinted models, scientists can tailor treatment approaches to individual tumor profiles, advancing the field of personalized medicine.

ADVANCING TARGETED CANCER THERAPIES

The ability to study complex interactions among different cell types in a tumor-mimicking environment is key to unraveling the mechanistic basis of cancer progression and metastasis. By leveraging 3D bioprinting, researchers can identify new therapeutic targets, optimize treatment strategies, and develop more precise, personalized, and effective anti-cancer therapies.

CHALLENGES AND FUTURE PERSPECTIVES: SCALABILITY AND STANDARDIZATION OF BIOPRINTED MODELS

To transition from experimental studies to widespread medical and industrial applications, 3D bioprinting faces significant challenges related to scalability and standardization. While the technology has advanced considerably, producing bioprinted tissues and organoids at a reproducible large scale remains difficult. One of the major hurdles lies in the variability of bioink properties—factors such as viscosity, crosslinking characteristics, and cell distribution can differ from batch to batch, leading to inconsistencies in both function and structure. Even minor changes in bioink composition can significantly alter cell behavior, tissue mechanics, and the ability of printed constructs to mature and heal[51]. To address these challenges, researchers are integrating high-throughput bioprinters that use multi-nozzle extrusion and computer-controlled droplet-based printing, allowing for the simultaneous fabrication of multiple constructs with high precision[52]. Additionally, microfluidic-assisted printing has improved scalability by offering greater control over bioink deposition, ensuring uniform structures. AI-driven feedback mechanisms are also being incorporated into next-generation bioprinters, enabling real-time monitoring and adjustments of extrusion pressure, bioink consistency, and printing conditions to enhance reproducibility[51]. Equally important is the standardization of bioprinting protocols. Scientists are working toward universal guidelines for bioink composition, structural integrity, and post-printing maturation to ensure bioprinted tissues exhibit predictable biological behavior[51]. Advances in machine vision systems allow real-time imaging and analysis of bioprinted structures, identifying defects during the printing process, while nanoindentation techniques help assess mechanical properties[52]. Another promising approach involves bioreactor-based maturation, where bioprinted tissues develop in simulated environments that closely resemble in vivo conditions, enhancing their functionality and stability[51]. As regulatory bodies work to establish safety and quality standards, the future of bioprinting will be defined by automation, real-time monitoring, and innovative biofabrication approaches. Overcoming the challenges of scalability and standardization will be crucial for moving bioprinting beyond proof-of-concept studies, enabling its widespread application in regenerative medicine, personalized drug testing, and even the engineering of functional human organs[51].

CONTROL OF OXYGEN, NUTRIENT, AND PH GRADIENTS

The maintenance of proper oxygen, nutrient, and pH gradients is essential for the survival and functionality of prostate cancer cells in 3D bioprinted tissue models. Oxygen gradients are usually tackled through the use of microvascular networks or oxygen-releasing compounds such as perfluorocarbons in the bioinks, which supports the localized delivery of oxygen to replicate in vivo conditions[53-55]. Nutrient gradients that cause cell death toward the interior of dense constructs are controlled by the use of perfusion bioreactors, nutrient-hydrogels, and microsphere-delivery systems to provide a constant supply of vital molecules[56-58]. Moreover, pH gradients, which are influenced by cancer cells' high metabolic activity, are regulated by pH-buffering bioinks and acid-responsive materials that provide a stable microenvironment[59,60]. All these efforts combined help establish more realistic and viable 3D prostate cancer models, leading to cancer research and therapeutic innovation.

BIOINK OPTIMIZATION AND BIOMECHANICAL CONSTRAINTS

Optimizing bioink is one of the most significant challenges in 3D bioprinting, requiring a delicate balance between printability, biocompatibility, and biomechanical stability. A bioink must be fluid enough for extrusion while retaining structural integrity after deposition. Additionally, it should support cell viability, tissue maturation, and remodeling over time. Achieving this level of optimization is difficult because many commonly used hydrogels lack sufficient mechanical strength, making printed structures prone to deformation or collapse[61,62]. To address these limitations, researchers are developing reinforced bioinks by incorporating nanomaterials such as graphene oxide, cellulose nanofibers, and hydroxyapatite, which enhance mechanical stability without compromising biological function[63,64]. Another promising strategy involves dual-crosslinking, where a combination of physical and chemical crosslinking improves structural stability while maintaining the necessary flexibility for tissue growth and remodeling[65]. Bioink viscosity is also a critical factor, as high shear forces during extrusion can damage embedded cells. Shear-thinning bioinks, which become less viscous during extrusion and regain viscosity afterward, have been engineered to protect cell integrity[66]. Additionally, microgel-based bioinks, composed of cell-laden microparticles, provide enhanced control over mechanical properties and shape fidelity, allowing for the precise fabrication of complex tissue structures[61,67]. Beyond printing, post-processing techniques are crucial for improving biomechanical functionality. Mechanical conditioning using bioreactors, which apply controlled mechanical loads to printed tissues, has been shown to enhance ECM formation and tissue maturation, particularly in load-bearing scaffolds such as cartilage and bone tissue[64,66]. Future advancements in bioink composition will focus on bridging the gap between experimental models and clinically viable tissue constructs. By integrating novel biomaterials, intelligent crosslinking methods, and biomechanical conditioning approaches, researchers are advancing 3D bioprinting toward the fabrication of robust, functional tissues capable of withstanding physiological conditions[62,65,67].

CLINICAL TRANSLATION: FROM LAB TO PATIENT CARE

The journey of 3D bioprinting from research labs to actual patient care is filled with both promise and complexity. While bioprinted tissues have demonstrated remarkable potential in preclinical studies, replicating the functionality of native human tissues at a clinically viable scale remains a significant challenge. The transition is hindered by several obstacles, including vascularization, ensuring structural and functional stability, and navigating the stringent regulatory approval process[68,69]. One of the most critical challenges is vascularization—the process of ensuring that bioprinted tissues develop functional blood vessels to keep cells alive and integrate seamlessly with the body. Microfluidic bioprinting and co-axial extrusion techniques have facilitated the creation of intricate vascular networks within printed constructs, improving nutrient and oxygen delivery[70]. Additionally, bioreactor-based preconditioning, where tissues are cultured under controlled mechanical and biochemical conditions before transplantation, has been shown to promote better cell maturation and enhance functional stability[51]. Beyond biological challenges, regulatory approval remains a major hurdle. Unlike traditional synthetic medical implants, bioprinted tissues involve living cells, necessitating rigorous safety testing to assess immunogenicity, mechanical strength, and long-term viability. To address this, researchers are developing standardized protocols for fabricating living tissues and employing robotic systems to monitor tissue growth in real time, ensuring quality control and consistency in compliance with strict regulatory standards[51,69]. Scalability is another pressing issue. While patient-specific bioinks—which incorporate a patient’s own cells—offer a personalized approach to regenerative medicine, mass production of bioprinted tissues requires significant advancements in large-scale bioprinting and rapid stem cell expansion. These innovations could lead to ready-made skin grafts, drastically improving burn treatments, wound healing, and reconstructive surgery. In the long run, bioprinting advancements might even reduce the need for full organ transplants, revolutionizing the field of regenerative medicine[68,70]. Despite these challenges, bioprinting is steadily advancing toward real-world medical applications. With each innovation in vascularization, tissue maturation, and large-scale manufacturing, bioprinted tissues are moving closer to becoming a standard tool in hospitals. The focus has shifted from merely proving feasibility to ensuring bioprinted tissues are safe, reliable, and accessible for patients in need (Table 2)[51,70].

Table 2 Challenges in bioprinting prostate cancer stem cell models: Technical and clinical perspectives.

Category	Challenge	Scientific context
Bioink engineering	Inadequate mimicry of prostate ECM and mechanical inconsistencies	Balancing stiffness and porosity to maintain PCSC phenotype and niche interactions
Cell viability and distribution	Cellular stress during extrusion and uneven cell dispersal	Shear stress impairs PCSC survival and may affect expression of stemness-related markers
Recapitulation of niche	Incomplete integration of stromal cells, hypoxia and cytokine signaling	Limitation in modeling immune- evasive and therapy -resistant PCSC microenvironment
Standardization & scalability	Difficulty in reproducing constructs with consistent geometry and cellular organization	Affects comparative drug screening and reproducibility across platforms
Vascularization limitations	Lack of functional vasculature in vitro impedes nutrient perfusion and long-term culture	Hinders tumor model viability for chronic drug studies and metastasis research
Clinical translation	Limited alignment with clinical tumor heterogeneity and patient-specific responses	Necessitates integration with omits data and patient-derived cells to improve predictive value

PCSC: Prostate cancer stem cell; ECM: Extracellular matrix.

EMERGING TECHNOLOGIES IN CANCER BIOPRINTING

Organ-on-a-chip (OoC) systems and bioprinted metastatic models are revolutionizing cancer research and treatment by providing physiologically relevant platforms for studying tumor biology, drug resistance, and personalized therapy. Traditional models, such as 2D cultures and animal testing, often fail to replicate the complexity of human tumors, leading to poor translation of preclinical findings to clinical success. These advanced technologies bridge that gap by recreating key aspects of the TME, improving our ability to test treatments, understand metastasis, and develop more effective cancer therapies[71,72]. OoC technology has emerged as a powerful tool for precision oncology by integrating human tumor cells into microfluidic devices that simulate organ-level functions. Unlike static petri dish cultures, these dynamic systems allow for continuous nutrient and drug flow, mimicking the way tumors behave in the body. Vascularized tumor-on-a-chip models enable real-time observation of cancer progression, immune cell infiltration, and drug penetration, providing unprecedented insight into how tumors evolve and respond to treatments[73,74]. Additionally, linking tumor chips with liver or kidney chips offers a more accurate prediction of drug metabolism, toxicity, and side effects, allowing for safer and more targeted therapeutic strategies[73]. Bioprinted metastatic models further enhance cancer research by replicating the 3D structure, cellular heterogeneity, and mechanical properties of metastatic tumors. Using extrusion-based bioprinting and microgel-based bioinks, researchers can create tumor spheroids embedded within a supportive matrix that mimics the extracellular environment. These models include stromal cells, immune components, and vascular networks, providing a more realistic setting to study how cancer cells spread, invade, and develop resistance to therapy[72,75]. Hydrogel-based invasion assays also allow scientists to track cancer cell migration and test the effectiveness of anti-metastatic drugs[76]. These technologies are transforming cancer treatment development and testing. Patient-derived tumor-on-a-chip systems allow for personalized drug screening, helping oncologists select the most effective therapies for individual patients before administering them, thereby reducing the risk of ineffective treatments and minimizing unnecessary side effects[71,74]. Artificial intelligence (AI)-driven image analysis further enhances these models by enabling automated monitoring of tumor responses, improving the speed and accuracy of drug screening[73,75]. By providing a more predictive and scalable approach to studying cancer, OoC systems and bioprinted metastatic models are paving the way for more precise, effective, and personalized cancer treatments. As these technologies continue to evolve, they hold immense potential to replace ineffective animal models, accelerate drug development, and improve survival rates for cancer patients worldwide[73,76]. AI and machine learning (ML) are revolutionizing 3D bioprinting by making it more precise, reproducible, and predictive, particularly in cancer research. These technologies are addressing some of the major hurdles in bioprinting, including optimizing bioink composition, enhancing print fidelity, and simulating how printed tissues will interact under biological conditions. In PCSCs bioprinting, AI-driven methodologies have tremendous potential to expedite targeted treatments by developing more physiologically relevant tumor models[77,78]. One of the most promising applications of AI in bioprinting is bioink optimization. Deep learning algorithms process massive datasets on bioink rheology, cell viability, and mechanical strength to predict the optimal composition for printing PCSCs. This ensures that printed structures not only support tumor growth but also mimic the stiffness and biochemical gradients of native tissues, which is crucial for understanding tumor progression and drug resistance[79,80]. Another advancement is AI-powered image analysis for improving print accuracy. High-resolution imaging combined with convolutional neural networks enables real-time correction of printing defects, ensuring that cancer models retain their intended structure and cellular organization. This is especially critical in PCa research, where minor differences in tumor architecture can significantly impact drug response[78,81]. Machine learning is also revolutionizing drug screening in bioprinted PCa models. Traditional drug testing often fails to capture patient-specific responses, but ML models applied to bioprinted tumor-on-a-chip systems can analyze how PCSCs react to different therapies. Reinforcement learning algorithms further refine this process by continuously adjusting drug dosages and combinations to identify the most effective treatment strategies[77,82]. Additionally, AI is facilitating vascularization strategies in bioprinting. The ability of bioprinted prostate tumors to develop functional blood vessels is crucial for maintaining longterm viability and accurately replicating metastasis. Generative adversarial networks are being employed to design complex vascular networks that optimize nutrient supply, improving the realism of bioprinted tumor models[80,81]. By integrating AI into PCa bioprinting, researchers can create highly detailed, patient-specific tumor models that better predict treatment responses. This convergence of machine learning and bioprinting is paving the way for more targeted and efficient cancer therapies, reducing reliance on traditional models that often fail to capture the complexity of tumor growth and drug resistance[79,82].

CONCLUSION

3D bioprinting has emerged as a transformative tool in PCa research, providing an advanced platform for studying TMEs, PCSCs, and therapeutic responses. By precisely replicating the cellular and molecular complexity of PCa, 3D bioprinting enables high-throughput drug screening, personalized medicine, and a deeper understanding of PCSC-driven therapy resistance. The integration of bioinks that accurately mimic the ECM, along with co-cultured stromal and immune components, enhances the physiological relevance of bioprinted tumor models. Another significant advantage of 3D bioprinting is its potential to revolutionize targeted therapies by allowing for the screening of novel drugs and combination treatments specifically tailored to the unique profile of individual patients.

Despite its promise, the widespread clinical application of 3D bioprinting in PCa treatment faces several challenges, including scalability, bioink optimization, and standardization. Advances in bioprinting technologies, such as microfluidic-assisted printing and AI-driven optimization, are expected to improve reproducibility and functional accuracy. Organ-on-a-chip systems integrated with bioprinted PCa models can further enhance translational research by enabling real-time analysis of tumor progression and drug response in physiologically relevant conditions. Additionally, regulatory frameworks need to be established to facilitate the transition of bioprinted models from research settings to clinical applications. Collaboration among researchers, clinicians, and industry professionals is crucial in accelerating the development and application of bioprinting technologies. As these advancements continue, 3D bioprinting holds immense potential to redefine PCa treatment paradigms, ultimately improving patient outcomes and advancing the field of personalized cancer therapy.

ACKNOWLEDGEMENTS

The author acknowledges GSBTM, Govt. of Gujarat and Center for Predictive Human Model Systems (CPHMS) Atal Incubation Centre - Centre for Cellular and Molecular Biology (AIC-CCMB) Hyderabad for providing the opportunity to gain research experience in 3D bioprinting through the workshop and bootcamp.