Generation of Functional β Cells from Pluripotent Stem Cells: Advances and Applications

Zenith Khashim; Quinn P. Peterson

doi:10.5772/intechopen.1011979

Abstract

The generation of functional pancreatic β-cells from pluripotent stem cells (PSCs), including embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs), offers transformative opportunities in diabetes research and regenerative medicine, as primary human pancreatic β-cells are scarce and difficult to maintain in vitro. Stem cell-based differentiation has emerged as a scalable and renewable strategy to produce insulin-secreting β-like cells. This chapter provides an overview of the stepwise differentiation protocols that mimic human embryonic pancreatic β-cell development, highlighting the key signaling pathways and transcription factors involved at each stage. It also addresses critical challenges in achieving full β-cell maturation, including strategies such as 3D culture, co-culture systems, and environmental conditioning. Methods for isolating and enriching functional stem cell-derived β cells (SC-β), such as surface marker-based sorting, metabolic assays like glucose-stimulated insulin secretion (GSIS), and reaggregation into islet-like clusters, are discussed in detail. Functional validation techniques, including immunostaining, GSIS, and mitochondrial assessments, are emphasized to confirm SC-β cells identity and physiological function. Finally, this chapter highlights the use of SC-β cells in drug screening, disease modeling, and cell replacement therapies for diabetes. Continued advancements in differentiation protocols are positioning SC-β cells as vital resources for deepening our knowledge of diabetes and driving the development of effective cell replacement therapies.

Keywords

pluripotent stem cells induced pluripotent stem cells
pancreatic β-cells
insulin
differentiation
definitive endoderm
glucose-stimulated insulin secretion
diabetes
cell replacement therapy
regenerative medicine

Author Information

Show +

Zenith Khashim
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, United States of America
Quinn P. Peterson *
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, United States of America

*Address all correspondence to: peterson.quinn@mayo.edu

1. Introduction

Primary cells play a crucial role in both basic and translational research by offering physiologically relevant models to investigate tissue-specific functions, disease pathways, and responses to therapies. In diabetes research, the pancreas plays a vital role in maintaining glucose balance, primarily through the secretion of hormones by the [1, 2]. Among these hormones, insulin, secreted by pancreatic β-cells, plays a crucial role in lowering blood glucose levels. In human islets, β-cell account for roughly 55–70% of the total cell population and release insulin in response to rising glucose concentrations [3, 4, 5]. Although functional human β-cells are essential for both research and therapy, their acquisition remains a major challenging. Harvesting islet from pancreatic tissue is limited by scarce donor availability, poor cell viability during culture process, and difficulties in expanding cell numbers to meet experimental or clinical demands. These constraints have impeded progress in developing cell replacement therapies, a promising strategy to restore insulin production in individuals with diabetes by transplanting functional β-cells [6, 7]. The discovery of pluripotent stem cells, like embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs), offers a renewable and scalable source for generating stem cell-derived β (SC-β) cells in vitro [8]. Using stepwise differentiation protocols that recapitulate embryonic pancreatic development, ESCs and iPSCs can be directed to form insulin producing β-like cells with both physiological relevance and therapeutic potential. These advances not only accelerate the development of cell replacement therapies but also expand opportunities for disease modeling, drug screening, and personalized regenerative medicine. This chapter examines the evolution from traditional islet isolation methods to the generation of SC-β cells from ECS/iPSC, emphasizing recent progress in differentiation techniques, functional assessment, and the growing utility of SC-β cells in both diabetes research and therapeutic applications. It also discusses current challenges, technological innovations, and future perspectives aimed at improving SC-β cell maturation, scalability, and clinical translation for effective diabetes treatment.

2. Islet isolation: Overview and limitations

The isolation of pancreatic islets has long served as a critical technique for studying β-cell biology, diabetes pathophysiology, and potential therapeutic interventions. Traditionally, human and animal islets are isolated from donor pancreata using enzymatic and mechanical methods that separate the islets from the surrounding exocrine tissue. The most employed protocol involves collagenase digestion, which enzymatically disrupts the extracellular matrix, followed by density gradient centrifugation to enrich islet populations based on their buoyant density. After centrifugation, islets are typically handpicked under a microscope to ensure purity for downstream applications [9, 10, 11]. Islet isolation remains technically challenging despite decades of optimization, with extracting viable islets from donor pancreases particularly difficult. As a result, only about 50% of processed pancreata yield enough islets suitable for transplantation [12, 13]. The limited availability of donor organs continues to severely constrain the supply of primary islets for both clinical use and research. Even when donor tissue is obtainable, isolated β-cells experience rapid declines in viability and function due to physical stress, restricting their application in long-term cultures and functional assays [14, 15]. In addition, this approach lacks the scalability needed to meet the demands of widespread therapeutic use, especially since each clinical transplant requires millions of functional β-cells [16, 17]. These limitations highlight the urgent need for alternative, renewable sources capable of producing high-quality β-cells at a scale suitable for clinical applications. In this context, the development of pluripotent stem cell technologies, including ESCs and iPSCs, offers a promising solution. These platforms allow the in vitro generation of SC-β cells through directed differentiation protocols that mimic developmental cues, thereby providing an expandable, donor-independent source of insulin-producing cells [8, 18, 19]. As a result, stem cell-based methods are gaining popularity as a more effective alternative to overcome the challenges of isolating primary islets. They offer new opportunities for studying disease, testing drugs, and developing cell replacement therapies to treat diabetes.

3. Pluripotent stem cells as sources for pancreatic β-cell generation

The discovery of human pluripotent stem cells (hPSCs) has transformed regenerative medicine and drug development by enabling the in vitro generation of replacement cells and tissues for therapeutic use [8]. Owing to their unique ability to differentiate into any cell type in the human body, pluripotent stem cells offer significant promise for advancing diabetes research. Importantly, these pluripotent stem cells can be directed to generate functional pancreatic β-cells, which are essential for insulin production and maintaining blood glucose homeostasis [8, 20]. They broadly fall into two categories: those derived from early-stage embryos (ESCs) and those reprogrammed from adult somatic cells (iPSC). ESCs are derived from an inner cell mass (ICM) of the human blastocyst, a hollow structure that forms approximately 5–6 days after fertilization. At this stage, the human embryo contains about 70–100 cells and is composed of two main components: ICM, which gives rise to the embryo proper and serves as the source of ESCs, and the trophoblast, which develops into the placenta [21, 22]. ESCs are naturally pluripotent and were the first human stem cells to be studied extensively in research. They have the remarkable ability to self-renew indefinitely and to differentiate into all three germ layers: ectoderm, mesoderm, and endoderm [21, 23, 24]. Importantly, since the endoderm gives rise to pancreatic tissue, ESCs serve as an ideal source for generating insulin-producing β-like cells in vitro [8] for diabetes research and potential therapy (Figure 1).

Figure 1.
Derivation of embryonic stem cells (ESCs) from early human embryo development. The image illustrates the sequential stages of preimplantation embryonic development, starting from the 2-cell zygote (Day 1), progressing through the 8-cell stage (Day 3) and morula (Day 4), and culminating in the formation of the blastocyst (Day 5). The blastocyst’s inner cell mass (ICM) gives rise to ESCs when isolated and cultured *in vitro*. ESCs derived from the ICM are pluripotent and capable of differentiating into all three germ layers.

iPSCs are generated by reprogramming adult somatic cells, such as skin fibroblasts or blood cells, back into a pluripotent state. This is typically achieved by introducing a set of transcription factors, most commonly Oct4 (Octamer-binding transcription factor 4), Sox2 (SRY-box transcription factor 2), Klf4 (Kruppel-like factor 4), and c-Myc (cellular Myc proto-oncogene), which reset the cell’s gene expression and epigenetic profile [25, 26]. This technology offers several important advantages.

iPSCs present a key ethical advantage by circumventing the use of human embryos, thus enhancing their acceptance in both clinical and research contexts. Moreover, iPSCs enable the generation of patient specific cell lines, which are valuable in the field of personalized medicine [27]. In the context of diabetes, somatic cells from affected individuals can be reprogrammed into iPSCs and differentiated into pancreatic SC-β cells [28, 29]. These personalized cells provide a powerful platform for uncovering disease mechanisms, evaluating individual drug responses, and serving as autologous grafts for transplantation markedly reducing the risk of immune rejection (Figure 2).

Figure 2.
Generation of induced pluripotent stem cells (iPSCs) from adult somatic cells. This schematic illustrates the reprogramming of an adult somatic cell, such as a skin fibroblast or blood cell, into an iPSC. The reprogramming is achieved by adding transcription factors that revert the somatic cell to a pluripotent state. The resulting iPSCs can differentiate into different cell types.

PSCs hold immense promise in regenerative medicine, especially for developing personalized therapies aimed at chronic diseases such as diabetes, cardiovascular disorders, and neurodegenerative conditions. Progress in reprogramming techniques, gene editing technologies like CRISPR-Cas9, and optimized differentiation protocols has expanded the clinical and research utility of iPSC-based systems [30, 31]. Like ESCs, iPSCs exhibit self-renewal and pluripotency, enabling unlimited expansion and differentiation into cells of all three germ layers ectoderm, mesoderm, and endoderm [21, 25, 32]. These distinctive characteristics make PSCs invaluable for studying early human development, modeling diseases, testing drugs, screening therapeutics, and advancing regenerative medicine. One of their most promising applications is the generation of insulin-producing SC-β cells. Through stepwise differentiation protocols that recapitulate embryonic pancreatic development, ESCs and iPSCs can be guided to produce functional SC-β cells capable of glucose-stimulated insulin secretion [8]. This scalable platform addresses the critical limitations associated with donor-derived β-cells and opens new avenues for innovative diabetes therapies.

4. Pluripotent stem cells directed differentiation toward β cells

The generation of functional pancreatic β-cells from hPSCs, including ESCs and iPSCs, relies on directed differentiation protocols that closely mimic the sequential developmental stages of pancreas formation during embryogenesis. This approach, pioneered by researchers such as Melton and colleagues [8] has become a foundational strategy in the production of insulin-producing β-cells for use in diabetes research, drug screening, and potential cell replacement therapies. During the embryonic development process, the pancreas arises from the definitive endoderm, a germ layer formed early in gastrulation. To emulate this developmental trajectory in vitro, differentiation protocols employ stage-specific combinations of growth factors and small molecules that activate or inhibit key signaling pathways such as Nodal/Activin, BMP (Bone morphogenetic protein), FGF (Fibroblast growth factor), Notch, and retinoic acid (RA) to guide cells through precise lineage transitions. Each stage is marked by the expression of defined transcription factors that reflect cellular identity and maturation status. Based on current knowledge and widely adopted methods, the differentiation process typically involves a six-stage progression, designed to replicate the embryological sequence leading to β-cell development [8, 18, 20, 33, 34].

4.1 Stage 1: Definitive endoderm induction

The initial step in guiding pluripotent stem cells toward the pancreatic β-cell lineage involves the induction of definitive endoderm (DE). This embryonic germ layer gives rise to key organs such as the pancreas, liver, lungs, and gastrointestinal tract. In vivo, DE arises from the primitive streak during gastrulation, where cells undergo epithelial to mesenchymal transition (EMT) under the control of tightly regulated signaling pathways, particularly Nodal/TGF-β and Wnt. In vitro, this process is replicated by exposing pluripotent stem cells to cues that activate these same pathways. For example, Activin A a TGF-β family ligand activates the Smad2/3 signaling pathway, effectively mimicking Nodal function to initiate endodermal differentiation. Concurrent activation of the Wnt/β-catenin pathway further enhances the efficiency of DE induction. The success of this stage is evaluated by the expression of key DE markers, most notably SRY-box transcription factor 17 (SOX17), a master regulator of endoderm fate, and Forkhead box protein A2 (FOXA2), which is essential for patterning and later organ-specific differentiation. Under optimized conditions, more than 80% of cells typically adopt a SOX17⁺/FOXA2⁺ phenotype within 2–3 days [8, 35, 36, 37]. Precise signal timing, concentration, and duration control are essential for consistent DE formation.

4.2 Stage 2: Primitive gut tube and posterior foregut formation

Following DE induction, the next key step in β-cell differentiation is directing the cells to form the primitive gut tube and progress into the posterior foregut, the developmental region that gives rise to the pancreas. This stage mimics the third and fourth weeks of human embryogenesis and requires precise modulation of key signaling pathways, particularly FGF, BMP, and retinoic acid (RA). Growth factors like FGF10 and FGF7 support the expansion and maintenance of foregut progenitors [37]. BMP signaling is carefully balanced, neither overly activated nor strongly inhibited, to prevent misdirection toward intestinal fates. Meanwhile, RA plays a vital role by repressing anterior endoderm identities (such as lung and thyroid) and promoting pancreatic gene programs. As cells undergo morphogenesis into a 3D tube-like structure, they begin expressing transcription factors such as hepatocyte nuclear factor-1 beta (HNF1B), hepatocyte nuclear factor-4 alpha (HNF4A), SOX9, and FOXA2, which mark successful posterior foregut patterning. This stage typically spans 2–3 days and represents a developmental decision point. Proper signaling ensures that cells are primed to initiate PDX1 expression in the next stage, committing to the pancreatic lineage [8].

4.3 Stage 3: Pancreatic progenitor 1 (PP1) specification

During this stage, gut tube cells are directed toward an early pancreatic progenitor fate, marked by the upregulation of pancreatic duodenal homeobox 1 (PDX1). This transition is guided by a defined set of signaling cues, including retinoic acid (RA), which plays a key role in promoting posterior foregut identity and initiating pancreatic lineage specification. The culture conditions at this stage are optimized to suppress non-pancreatic fates and support the emergence of pancreatic-committed cells [38, 39].

4.4 Stage 4: Pancreatic progenitor 2 (PP2) maturation

Following the PP1 stage, cells continue to mature and begin to co-express PDX1 along with a subset expressing NKX homeobox 1 (NKX6.1), indicating progression toward a committed pancreatic progenitor state. Although the overall signaling conditions remain similar, the concentration of retinoic acid (RA) is reduced to fine-tune pathway activity and improve lineage specificity. This adjustment facilitates the expansion of a bipotent progenitor population that is more precisely directed toward endocrine lineages in the next stage [8].

4.5 Stage 5: Endocrine progenitor differentiation

Following the establishment of pancreatic progenitor identity, the next critical step involves directing these cells toward the endocrine lineage, which gives rise to hormone-producing islet cells, including insulin-secreting β-cells. This transition is initiated by the upregulation of Neurogenin-3 (NGN3), a Basic helix-loop-helix (bHLH) transcription factor that serves as the master regulator of endocrine differentiation. Transient expression of NGN3 is essential, as it triggers a cascade of gene expression changes leading to islet cell specification. The emergence of endocrine progenitors is confirmed by the co-expression of NGN3, Chromogranin A (CHGA), a general marker of neuroendocrine cells, alongside PDX1 and NKX6.1, which are retained from the pancreatic progenitor stage [40, 41].

Notch signaling is actively inhibited to promote this transition, commonly using γ-secretase inhibitors, since active Notch signaling maintains cells in an undifferentiated progenitor state. Inhibition of this pathway permits NGN3 upregulation and endocrine lineage commitment [42]. Precise control of timing and dosage of differentiation cues at this stage is critical; premature endocrine induction can compromise subsequent β-cell maturation and function. This stage lays the groundwork for the final maturation phase, where committed endocrine progenitors acquire the specialized features of glucose-responsive β-cells. This transition is driven by the transient upregulation of NGN3, a master regulator of endocrine specification [43, 44]. The induction of NGN3 initiates a transcriptional cascade that commits cells to the endocrine fate, with emerging progenitors typically co-expressing NGN3, CHGA, and retained markers PDX1 and NKX6.1. To promote this transition, Notch signaling is actively suppressed often through γ-secretase inhibition as sustained Notch activity preserves cells in an undifferentiated state [45, 46, 47]. The differentiation medium at this stage is supplemented with factors that support endocrine induction, including modulators of TGF-β (Transforming growth factors), SHH (Sonic Hedgehog), and thyroid hormone pathways, along with reduced retinoic acid levels. The combination of these cues facilitates efficient NGN3 expression while maintaining lineage specificity [48].

4.6 Stage 6: SC-β cell maturation

The final stage of differentiation focuses on transforming endocrine progenitors into functionally mature, glucose-responsive β-cells that can secrete insulin in a regulated manner, mimicking the physiological behavior of native human islet β-cells. During this phase, cells begin to express key β-cell markers such as INS (insulin), C-peptide, NKX6.1, and most notably, MAF bZIP transcription factor A (MAFA), a transcription factor strongly associated with β-cell functional maturity and responsiveness to glucose stimulation. The co-expression of INS, MAFA, and NKX6.1, along with C-peptide, a byproduct of proinsulin processing, indicates successful acquisition of β-cell identity [8, 18]. At this stage, the derived β-cells acquire the ability to respond to GSIS, a critical functional hallmark of matured pancreatic β-cells (Figure 3).

Figure 3.
Directed differentiation of hPSCs into SC-β cells. Schematic representation of the six-stage protocol used to generate insulin-producing SC-β-cells from hPSCs. Each stage mimics sequential steps of pancreatic development, guiding cells through definitive endoderm (DE), gut tube (GT), early and late pancreatic progenitors (PP1 and PP2), and endocrine (EN) stages to produce functional SC-β cells.

5. Maturation of stem cell derived β-cells

The maturation of SC-β cells is a critical step in the development of functionally competent insulin-producing cells for use in regenerative therapies and diabetes research. While current differentiation protocols can generate cells expressing key β-cell markers such as INS, NKX6.1, and C-peptide, these cells often remain functionally immature. Specifically, they frequently exhibit impaired GSIS and lack the dynamic insulin release patterns characteristic of native adult β-cells. To enhance functional maturation, SC-β cells are typically transitioned from two-dimensional (2D) monolayer cultures to three-dimensional (3D) systems that more closely mimic the native islet microenvironment. Among these, 3D spinner flask cultures are widely used due to their scalability and ability to support the formation of uniform islet-like clusters. These dynamic 3D environments improve nutrient diffusion, promote cell-cell and cell-matrix interactions, and provide mechanical cues that contribute to SC β-cell maturation. In addition to spinner flasks, spheroid plates, and other microwell-based platforms are also employed to facilitate reaggregation after stage 6 differentiation, allowing precise control over cluster size and density [8, 18, 19].

The 3D culture environment supports critical aspects of SC-β cell maturation, including the establishment of apical-basal polarity, enhanced mitochondrial activity, increased insulin granule density, and improved GSIS. Despite these advances, SC-β cell populations often remain heterogeneous, with subsets of cells displaying immature, fetal-like transcriptional profiles. To address this, ongoing studies are exploring strategies to further optimize the in vitro maturation process. These include modulating culture media composition by introducing dynamic glucose cycling, fatty acids, and thyroid hormone (e.g., T3), as well as adjusting oxygen tension to better replicate in vivo conditions. Co-culture with endothelial cells, mesenchymal stromal cells, or other islet cell types is also under investigation to provide supportive paracrine signals that enhance maturation [49, 50, 51, 52, 53]. In vivo transplantation remains the gold standard for evaluating the functional maturity of SC-β cells. Transplanted cells consistently exhibit enhanced maturation and insulin secretion compared to their in vitro counterparts, underscoring the critical influence of host-derived systemic and tissue-specific cues. Insights from these in vivo models are now being applied to optimize in vitro differentiation protocols, to produce uniformly mature, glucose-responsive SC-β cells suitable for both clinical and research applications.

6. Isolation and enrichment of β-cells

Given the heterogeneity that arises from in vitro differentiation, isolation and enrichment of functional β-cells is essential to enhance the purity, safety, and performance of these cells in both experimental and therapeutic settings. Post-differentiation, cultures often contain a mix of SC-β cells, other endocrine and non-endocrine cell types, and residual progenitors or off-target populations. To address this, several enrichment strategies have been developed. One widely used approach is surface marker-based sorting. For example, β-cell-specific markers such as CD49a (integrin α1) enable selective isolation using fluorescence-activated cell sorting (FACS) or magnetic-activated cell sorting (MACS) [54, 55]. In addition, functional selection techniques such as GSIS assays are employed to identify and retain cells with proper stimulus-secretion coupling, ensuring functional relevance [56, 57]. Reporter-based enrichment is another effective method, wherein gene reporters (e.g., GFP) driven by insulin promoters are introduced into pluripotent stem cells to visually track and sort insulin-producing cells [58]. Moreover, reaggregation of sorted cells into islet-like clusters has been shown to enhance cell-cell interactions, restore structural integrity, and improve functional properties such as insulin granule formation, synchronized calcium signaling, and glucose responsiveness features that closely mimic the native islet microenvironment. Implementing these enrichment strategies enhances the consistency and reliability of SC-β cell products, reduces the risk of undesired differentiation or teratoma formation, and improves the precision of disease modeling and drug screening [59, 60, 61]. These approaches are vital for advancing the clinical translation of SC-β cells and ensuring their therapeutic efficacy in diabetes treatment.

7. Functional validation of β-cells

The maturation of the SC-β cells must be evaluated to confirm their identity and functional maturity. Immunostaining and flowcytometry is typically performed to detect β cell-specific markers such as insulin, C-peptide, PDX1, NKX6.1, and MAFA, indicating proper lineage commitment and maturity. However, the expression of these transcription factors alone does not guarantee physiological function. Therefore, functional validation is critical, and GSIS remains the gold standard assay for assessing β cell activity. In a typical GSIS assay, β cells are sequentially exposed to low (e.g., 3.3 mM) and high (e.g., 16.7 mM) glucose concentrations, and insulin or C-peptide levels in the culture supernatant are measured, usually by human insulin ELISA [8] . Mature SC-β cells exhibit a low basal insulin release at low glucose, followed by a sharp increase in secretion when stimulated with high glucose [8, 62]. This biphasic insulin response reflects proper metabolic coupling, where glucose metabolism increases ATP production, closes ATP-sensitive potassium (K⁺) channels and leads to membrane depolarization, calcium influx, and insulin granule exocytosis. In some cases, KCl or arginine may be used as depolarizing controls to test stimulus-secretion coupling independently of glucose metabolism (Figure 4A and B). To further assess SC-β cell potency, mitochondrial assays such as oxygen consumption rate (OCR) and ATP production are used to confirm that the cells have an intact oxidative metabolism, which is essential for ATP-sensitive insulin release [56]. In addition, calcium imaging or dynamic perifusion assays can be used to examine the kinetics and robustness of the insulin response, providing deeper insight into SC-β cell function at single-cell or population levels [63].

Figure 4.
Schematic overview of GSIS in β cells. (A) High glucose levels are metabolized by β-cells, increasing ATP production, which closes KATP channels, triggers calcium influx, and stimulates insulin exocytosis. (B) A typical GSIS profile shows an increased insulin release at high glucose compared to basal levels.

Moreover, the downregulation of progenitor markers like NGN3 and the upregulation of genes related to β-cell maturity (e.g., MAFA) further confirm functional differentiation. For translational relevance, in vivo validation, such as transplantation into streptozotocin (STZ)-induced diabetic mice, can demonstrate the ability of SC-β cells to restore normoglycemia and maintain glucose homeostasis over time [8, 18, 64]. Collectively, these multidimensional assessments evaluate whether SC-β cells are phenotypically authentic and metabolically competent. The main objective is to confirm the ability of the cell to perform GSIS, which is a hallmark of functional β-cells. Establishing this capability is critical for their use in drug discovery for disease and diabetes, and the development of future clinical therapies for diabetes.

8. Applications for SC-β cells in regenerative research

SC-β cells have broad applications in regenerative medicine, particularly in diabetes treatment and disease modeling. Their ability to restore insulin secretion through cell replacement therapy makes them a valuable tool in translational research. Building on this potential, SC-β cells are being used in disease modeling using genetic engineering, high-throughput drug screening, and in the development of immune evasion and encapsulation strategies to enhance graft survival and functio.

8.1 Translational and therapeutic applications

SC-β cells have emerged as a powerful platform for both basic research and translational applications in diabetes. Using patient-specific iPSCs, researchers can generate SC-β cells that reflect the genetic and metabolic diversity observed in individuals with diabetes. These in vitro models provide critical insights into the molecular mechanisms of β-cell dysfunction and disease progression in a patient-relevant context [8, 18].

Several ongoing clinical trials (e.g., NCT03163511, NCT04786262) are evaluating the safety, efficacy, and long-term viability of SC-β cell transplantation. Many of these studies incorporate micro or macro encapsulation technologies to protect transplanted cells from immune rejection, with the goal of reducing or eliminating the need for lifelong immunosuppressive therapy. Recent advances in generating SC-β cells from stem cells have strengthened their potential to improve our understanding of diabetes, support the discovery of more effective therapies, and contribute to the development of regenerative treatments that may offer a long-term cure [8]. Beyond disease modeling, SC-β cells enable high-throughput drug screening to identify compounds that preserve β-cell identity, enhance insulin secretion, or promote regeneration. This capability also enables the design of personalized therapies based on individual disease characteristics. Creating functional, glucose-responsive SC-β cells is a promising step toward cell-based therapy for diabetes. These cells can help restore the body’s ability to produce insulin and keep blood sugar levels in check, which may reduce or even eliminate the need for insulin injections.

8.2 Genetic engineering and disease modeling

Genetic engineering tools, especially CRISPR-Cas9, have transformed the ability to precisely modify the genome of hPSCs, allowing detailed studies of gene function and disease mechanisms in pancreatic β-cell biology. Through targeted correction of mutations in ESCs or iPSCs, researchers can effectively model both monogenic and polygenic forms of diabetes in vitro. This approach has proven especially powerful in studying condition like neonatal diabetes, maturity-onset diabetes of the young (MODY), and syndromic forms of the disease that arise from single-gene defects [65].

Patient-derived iPSCs carrying disease-relevant mutations can be differentiated into SC-β cells, which then serve as platforms to examine how these mutations affect β-cell development, insulin secretion, and metabolic regulation. For example, iPSC models of MODY caused by mutations in genes such as HNF1A, GCK (Glucokinase), and INS have revealed disease-specific phenotypes such as altered insulin gene expression, impaired glucose sensing, and increased susceptibility to cellular stress. Gene correction using CRISPR-Cas9 in these same lines has been shown to restore normal function, providing a valuable system to test personalized therapeutic approaches [66, 67, 68]. In addition to nuclear gene disorders, iPSC models are now being used to study mitochondrial diseases that affect β-cell function. One prominent example is MELAS (Mitochondrial Encephalomyopathy, Lactic Acidosis, and Stroke-like episodes), a disorder commonly caused by the m.3243A > G mutation in mitochondrial tRNA^Leu (UUR). This mutation is strongly associated with mitochondrial diabetes. iPSCs derived from MELAS patients, which often harbor different levels of heteroplasmy, can be differentiated into SC-β cells to study how mitochondrial dysfunction impairs β-cell bioenergetics, insulin secretion, and stress responses. These models offer valuable insights into heteroplasmy-dependent phenotypes and allow for testing metabolic interventions, such as mitochondrial antioxidants, NAD⁺ (nicotinamide adenine dinucleotide) boosters, or even mitochondrial transfer strategies, to rescue β-cell function [69, 70]. Furthermore, engineered hPSCs have also been used to generate reporter cell lines, where fluorescent or luminescent reporters are placed under the control of SC-β cells specific promoters (e.g., INS or MAFA). These reporter lines facilitate real-time monitoring of differentiation efficiency, β-cell identity, and functional status and are especially useful in high-throughput drug screening and lineage tracing studies [71, 72]. The combination of genome editing and stem cell technologies provides a powerful tool for modeling diverse forms of diabetes like exploring β-cell pathophysiology, developing targeted and creating patient-specific therapies. These models bridge the gap between genotype and cellular phenotype, offering insights that are not easily obtainable from animal models or primary human tissue.

8.3 Immune evasion and encapsulation strategies

A major challenge in translating SC-β cells therapies into clinical treatments is immune rejection. Transplanted SC-β cells are recognized as foreign by the recipient’s immune system, leading to graft destruction unless immunosuppressive drugs are administered. However, long-term use of immunosuppressive drugs carries significant risk, including infections, increased cancer risk, and organ damage [73, 74]. As a result, developing strategies to protect transplanted SC-β cells without systemic immunosuppression has become a central goal in regenerative medicine.

One promising approach is genetic engineering to generate hypoimmunogenic SC-β cells. Deletion of major histocompatibility complex (MHC) class I and II molecules reduce antigen presentation and limits recognition by cytotoxic and helper T cells. However, the absence of MHC class I molecules can trigger natural killer (NK) cell mediated cytotoxicity. To counteract this, immune-inhibitory ligands such as HLA-E or CD47 have been introduced to suppress NK cell activation. These combinatorial gene-editing strategies show considerable potential for enabling transplantation across MHC barriers with reduced risk of immune rejection [75, 76]. Another strategy to protect transplanted β-cells from immune attack is biomaterial-based encapsulation, which forms a physical barrier that prevents immune cell infiltration while allowing the diffusion of oxygen, nutrients, glucose, and insulin [64, 77]. Encapsulation technologies are generally categorized into microencapsulation and macroencapsulation. Microencapsulation involves embedding individual cells or small clusters within semi-permeable hydrogels, often alginate-based, which are chemically modified to reduce fibrosis and immune activation. In contrast, macroencapsulation devices enclose larger cell aggregates within implantable and retrievable chambers made from advanced polymers or membranes engineered with defined porosity. These devices support molecular exchange while shielding the enclosed cells from immune surveillance [78, 79].

Several clinical trials are investigating encapsulation technologies. For example, ViaCyte has developed encapsulation devices such as the Encaptra™ system to protect stem cell-derived β-cells from immune rejection (NCT03163511), while Vertex Pharmaceuticals is evaluating VX-880 (NCT04786262), a stem cell-derived β-cell therapy, both with and without systemic immunosuppression. Additionally, emerging platforms are exploring co-encapsulation with immunomodulatory agents, such as cytokine blockers or immune checkpoint inhibitors, to locally suppress immune responses and reduce the need for systemic immunosuppressive drugs (NCT05210530). Despite promising progress, significant challenges remain. SC-β cell therapies still face major hurdles, including fibrotic overgrowth, hypoxia within encapsulation devices, and incomplete immune protection. Overcoming these barriers will be critical for achieving durable and widespread clinical success in diabetes therapy.

9. Challenges in clinical translation

SC-β cell technologies hold great promise for treating diabetes; several key challenges must be addressed before these therapies can be widely adopted in clinical practice. One of the foremost challenges is functional heterogeneity within differentiated cell populations. Despite significant improvements in directed differentiation protocols, SC-β cell preparations often contain a mixture of mature SC-β cells, other endocrine and non-endocrine cells, and residual progenitor off-target populations [8, 18]. This variability poses risks for inconsistent therapeutic outcomes and complicates product standardization.

Immature or non-functional cells within the graft can lead to failure of transplant or trigger adverse host responses. A major safety concern is the risk of tumorigenicity, as pluripotent stem cells have the potential for unlimited proliferation. If differentiation is incomplete, residual undifferentiated or misdirected cells may persist in the graft and form teratomas or other tumors [59, 60, 61, 80]. Minimizing this risk requires complete differentiation of pluripotent cells and the use of robust purification techniques, such as surface marker-based sorting, to eliminate undifferentiated or aberrant cells. At the same time, immune rejection remains a major challenge, especially in allogeneic settings. While strategies like encapsulation and immune-evasive genetic engineering are under active investigation, reliably achieving long-term graft survival without systemic immunosuppression is still difficult. In addition, for patients with type 1 diabetes, autoimmune responses may re-emerge and attack even autologous SC-β cells, underscoring the need for therapies that also address the root causes of immune dysregulation [64].

From a manufacturing and regulatory perspective, clinical-grade SC-β cells must be produced under good manufacturing practice (GMP) conditions, which require rigorous quality control, reproducibility, and compliance with safety standards [81, 82]. This includes the validation of reagents, scalability of production platforms (e.g., bioreactors, suspension culture), and the establishment of release criteria for clinical batches based on potency assays such as GSIS. Furthermore, complicated translations are the challenges of long-term engraftment and vascularization. SC-β cells require a supportive microenvironment and stable vascular integration to function effectively in vivo as poor oxygenation, nutrient limitations, and inadequate innervation can impair graft performance over time. Ongoing efforts to optimize transplantation sites, co-deliver supporting cell types (e.g., endothelial cells, mesenchymal stromal cells), and engineer pro-vascular niches are critical to improving long-term outcomes [83]. Personalized autologous therapies, while offering patient-specific benefits, are hindered by high costs and prolonged manufacturing times. In contrast, universal allogeneic approaches offer broader applicability but encounter significant hurdles related to immune compatibility and regulatory approval. To ensure widespread accessibility, it is essential to develop platforms that are not only scalable and cost-effective but also ethically sustainable.

10. Ethical and societal considerations

As SC-β cell therapies move toward clinical use, it’s important to think carefully about the ethical and social questions raised. These include the source of stem cells, how informed consent is handled, who gets access to treatment, concerns about long-term safety, the moral debate around embryo use, and the risk of conflicts of interest in both research and commercial development. While human ESCs have been instrumental in SC-β research, their derivation from early-stage embryos raises ethical concerns for many who view embryos as possessing moral status. In contrast, iPSCs, generated by reprogramming adult somatic cells, avoid embryo-related concerns. However, iPSCs introduce their own challenges, including donor consent, ownership and use of biological material, variability in differentiation efficiency, and the ethical implications of genetic modifications [84, 85]. Additional concerns include donor anonymity, the long-term traceability of transplanted cells, and the protection of patient data. The high cost of SC-β therapies may also limit accessibility due to affordability and the potential to exacerbate existing health disparities. Ensuring that clinical trials and future therapeutic access reflect population diversity will be critical for equity and inclusion [86].

Safety remains a major priority. Risks such as tumorigenicity, immune rejection, off-target effects from gene editing, and unintended cellular behavior must be carefully assessed through long-term preclinical and clinical evaluation. Regulatory frameworks must also evolve to address advancements in encapsulation technologies, genome editing, and engineered transplant platforms. Public perception is equally important. Misleading claims, lack of poor communication can erode trust and delay the adoption of otherwise transformative therapies. Fostering public confidence will require clear, accurate, and inclusive dialog among researchers, clinicians, policymakers, and the broader community [87, 88]. Strong ethical oversight and responsible communication are essential to ensure the safe, effective, and equitable integration of SC-β therapies into clinical practice.

11. Future directions and emerging technologies

As SC-β cell therapies continue to evolve, a new generation of technologies is emerging to address current limitations and drive clinical translation forward. A significant area of focus is improving differentiation protocols to increase the yield, purity, and functional maturation of SC-β cells. Researchers are refining these processes by mimicking in vivo developmental cues through dynamic signaling pathways, the precise timing of transcription factor activation, and advanced culture systems. Integration of single-cell transcriptomics and spatial multi-omics has enabled the identification of rare subpopulations, maturation bottlenecks, and new biomarkers that can be targeted to enhance SC-β cell function [89].

Artificial intelligence (AI) and machine learning are also being used to analyze large-scale omics data, predict differentiation outcomes, and optimize protocols with greater efficiency and consistency [90, 91]. In parallel, organoid and islet-on-a-chip platforms are offering more physiologically relevant in vitro models that replicate the 3D architecture, cellular diversity, and microvascular features of native human islets. These systems facilitate real-time analysis of insulin secretion, immune interactions, and drug responses under dynamic glucose conditions [92]. Bioprinting and tissue engineering are advancing the generation of vascularized, transplantable islet-like constructs by integrating SC-β cells with endothelial and stromal support cells in controlled architectures. Genetic engineering enables the design of SC-β cells with enhanced glucose responsiveness, immune evasion capabilities, and safety features such as programmable gene circuits and biosensors [93, 94]. Meanwhile, personalized regenerative therapies using patient-derived iPSCs are making it possible to tailor SC-β cell therapies to individual patients, particularly for monogenic and select forms of type 1 and type 2 diabetes. Future approaches may also involve integrating SC-β cells with implantable biosensors or closed-loop insulin delivery systems to improve therapeutic precision and real-time metabolic control. Collectively, these advances underscore the integration of stem cell science, engineering innovations, artificial intelligence, and personalized medicine paving the way for SC-β cell therapy to emerge as a scalable and potentially transformative treatment for diabetes.

12. Conclusions

The generation of functional pancreatic SC-β cells from pluripotent stem cells marks a major milestone in both diabetes research and therapy. Over the past two decades, substantial progress has been achieved in mimicking embryonic pancreatic development using stepwise differentiation protocols. These advances have enabled the production of insulin-secreting β-like cells that closely resemble in vivo counterparts in phenotype and, to a growing extent, in function. Despite these achievements, several challenges remain. Current SC-β cell populations often exhibit functional immaturity and cellular heterogeneity, which can limit their utility in both translational research and clinical applications. Efforts to address these issues through 3D culture systems, co-culture strategies, dynamic nutrient conditions, and in vivo validation continue to improve the physiological performance of SC-β cells. Furthermore, the integration of emerging technologies such as CRISPR-based disease modeling, biomaterial-driven encapsulation systems, and patient-specific iPSC platforms is expanding the applications of SC-β cells in disease modeling, drug screening, and personalized cell therapy. At the same time, ethical, immunological, and regulatory considerations must be carefully addressed to enable safe and equitable clinical translation. As differentiation protocols continue to improve and become more standardized, SC-β cells are increasingly positioned to become a foundational element of regenerative medicine for diabetes, with the ability to restore endogenous insulin production. These cells hold the promise to significantly reshape diabetes treatment and represent one of the most promising frontiers in biomedical research today.

Conflict of interest

QPP is holds intellectual property licensed by Vertex Pharmaceuticals and serves on the Scientific Advisory Board of Mellicell.

References

1. Campbell JE, Newgard CB. Mechanisms controlling pancreatic islet cell function in insulin secretion. Nature Reviews. Molecular Cell Biology. 2021;22(2):142-158
2. Röder PV et al. Pancreatic regulation of glucose homeostasis. Experimental & Molecular Medicine. 2016;48(3):e219
3. Pisania A et al. Quantitative analysis of cell composition and purity of human pancreatic islet preparations. Laboratory Investigation. 2010;90(11):1661-1675
4. Bosco D et al. Unique arrangement of alpha- and beta-cells in human islets of Langerhans. Diabetes. 2010;59(5):1202-1210
5. Segerstolpe Å et al. Single-cell transcriptome profiling of human pancreatic islets in health and type 2 diabetes. Cell Metabolism. 2016;24(4):593-607
6. Hogrebe NJ, Ishahak M, Millman JR. Developments in stem cell-derived islet replacement therapy for treating type 1 diabetes. Cell Stem Cell. 2023;30(5):530-548
7. Wang S et al. Transplantation of chemically induced pluripotent stem-cell-derived islets under abdominal anterior rectus sheath in a type 1 diabetes patient. Cell. 2024;187(22):6152-6164.e18
8. Pagliuca FW et al. Generation of functional human pancreatic β cells in vitro. Cell. 2014;159(2):428-439
9. Ricordi C et al. Automated method for isolation of human pancreatic islets. Diabetes. 1988;37(4):413-420
10. Lehmann R et al. Superiority of small islets in human islet transplantation. Diabetes. 2007;56(3):594-603
11. Lakey JR, Mirbolooki M, Shapiro AM. Current status of clinical islet cell transplantation. Methods in Molecular Biology. 2006;333:47-104
12. Kin T et al. Enhancing the success of human islet isolation through optimization and characterization of pancreas dissociation enzyme. American Journal of Transplantation. 2007;7(5):1233-1241
13. Ichii H et al. Rescue purification maximizes the use of human islet preparations for transplantation. American Journal of Transplantation. 2005;5(1):21-30
14. Toso C et al. Factors affecting human islet of Langerhans isolation yields. Transplantation Proceedings. 2002;34(3):826-827
15. Shapiro AM, Pokrywczynska M, Ricordi C. Clinical pancreatic islet transplantation. Nature Reviews. Endocrinology. 2017;13(5):268-277
16. Lemos JRN, Skyler JS. Challenges in beta cell replacement for type 1 diabetes. Hormone Research in Pædiatrics. 2025;98:435-449
17. Matsumoto S. Clinical allogeneic and autologous islet cell transplantation: Update. Diabetes and Metabolism Journal. 2011;35(3):199-206
18. Rezania A et al. Reversal of diabetes with insulin-producing cells derived in vitro from human pluripotent stem cells. Nature Biotechnology. 2014;32(11):1121-1133
19. Nair GG et al. Recapitulating endocrine cell clustering in culture promotes maturation of human stem-cell-derived β cells. Nature Cell Biology. 2019;21(2):263-274
20. Jin W, Jiang W. Stepwise differentiation of functional pancreatic β cells from human pluripotent stem cells. Cell Regeneration. 2022;11(1):24
21. Thomson JA et al. Embryonic stem cell lines derived from human blastocysts. Science. 1998;282(5391):1145-1147
22. Rossant J. Stem cells and early lineage development. Cell. 2008;132(4):527-531
23. Murry CE, Keller G. Differentiation of embryonic stem cells to clinically relevant populations: Lessons from embryonic development. Cell. 2008;132(4):661-680
24. Evans MJ, Kaufman MH. Establishment in culture of pluripotential cells from mouse embryos. Nature. 1981;292(5819):154-156
25. Takahashi K, Yamanaka S. Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell. 2006;126(4):663-676
26. Takahashi K et al. Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell. 2007;131(5):861-872
27. Maehr R et al. Generation of pluripotent stem cells from patients with type 1 diabetes. Proceedings of the National Academy of Sciences of the United States of America. 2009;106(37):15768-15773
28. Millman JR et al. Generation of stem cell-derived β-cells from patients with type 1 diabetes. Nature Communications. 2016;7:11463
29. Yamada M et al. Human oocytes reprogram adult somatic nuclei of a type 1 diabetic to diploid pluripotent stem cells. Nature. 2014;510(7506):533-536
30. Schwank G et al. Functional repair of CFTR by CRISPR/Cas9 in intestinal stem cell organoids of cystic fibrosis patients. Cell Stem Cell. 2013;13(6):653-658
31. Lian Q et al. Functional mesenchymal stem cells derived from human induced pluripotent stem cells attenuate limb ischemia in mice. Circulation. 2010;121(9):1113-1123
32. Yu J et al. Induced pluripotent stem cell lines derived from human somatic cells. Science. 2007;318(5858):1917-1920
33. Kumar SS et al. Recent developments in β-cell differentiation of pluripotent stem cells induced by small and large molecules. International Journal of Molecular Sciences. 2014;15(12):23418-23447
34. Jiang W et al. In vitro derivation of functional insulin-producing cells from human embryonic stem cells. Cell Research. 2007;17(4):333-344
35. Loh KM et al. Efficient endoderm induction from human pluripotent stem cells by logically directing signals controlling lineage bifurcations. Cell Stem Cell. 2014;14(2):237-252
36. D'Amour KA et al. Efficient differentiation of human embryonic stem cells to definitive endoderm. Nature Biotechnology. 2005;23(12):1534-1541
37. Zorn AM, Wells JM. Vertebrate endoderm development and organ formation. Annual Review of Cell and Developmental Biology. 2009;25:221-251
38. Arroyave F, Uscátegui Y, Lizcano F. From iPSCs to pancreatic β cells: Unveiling molecular pathways and enhancements with vitamin C and retinoic acid in diabetes research. International Journal of Molecular Sciences. 2024;25(17):9654
39. Johannesson M et al. FGF4 and retinoic acid direct differentiation of hESCs into PDX1-expressing foregut endoderm in a time- and concentration-dependent manner. PLoS One. 2009;4(3):e4794
40. Gu G, Dubauskaite J, Melton DA. Direct evidence for the pancreatic lineage: NGN3+ cells are islet progenitors and are distinct from duct progenitors. Development. 2002;129(10):2447-2457
41. Jennings RE et al. Human pancreas development. Development. 2015;142(18):3126-3137
42. Shih HP et al. A Notch-dependent molecular circuitry initiates pancreatic endocrine and ductal cell differentiation. Development. 2012;139(14):2488-2499
43. Scavuzzo MA et al. Endocrine lineage biases arise in temporally distinct endocrine progenitors during pancreatic morphogenesis. Nature Communications. 2018;9(1):3356
44. Cai Q et al. Prospectively isolated NGN3-expressing progenitors from human embryonic stem cells give rise to pancreatic endocrine cells. Stem Cells Translational Medicine. 2014;3(4):489-499
45. Murtaugh LC et al. Notch signaling controls multiple steps of pancreatic differentiation. Proceedings of the National Academy of Sciences of the United States of America. 2003;100(25):14920-14925
46. Silva IBB et al. Stem cells differentiation into insulin-producing cells (IPCs): Recent advances and current challenges. Stem Cell Research & Therapy. 2022;13(1):309
47. Memon B et al. Enhanced differentiation of human pluripotent stem cells into pancreatic progenitors co-expressing PDX1 and NKX6.1. Stem Cell Research & Therapy. 2018;9(1):15
48. Sali S et al. A perfect islet: Reviewing recent protocol developments and proposing strategies for stem cell derived functional pancreatic islets. Stem Cell Research & Therapy. 2025;16(1):160
49. Velazco-Cruz L et al. Acquisition of dynamic function in human stem cell-derived β cells. Stem Cell Reports. 2019;12(2):351-365
50. Talavera-Adame D et al. Endothelial cells in co-culture enhance embryonic stem cell differentiation to pancreatic progenitors and insulin-producing cells through BMP signaling. Stem Cell Reviews and Reports. 2011;7(3):532-543
51. Barsby T, Otonkoski T. Maturation of beta cells: Lessons from in vivo and in vitro models. Diabetologia. 2022;65(6):917-930
52. Feyen DAM et al. Metabolic maturation media improve physiological function of human iPSC-derived cardiomyocytes. Cell Reports. 2020;32(3):107925
53. Aguayo-Mazzucato C et al. Thyroid hormone promotes postnatal rat pancreatic β-cell development and glucose-responsive insulin secretion through MAFA. Diabetes. 2013;62(5):1569-1580
54. Molakandov K et al. Selection for CD26(−) and CD49A(+) cells from pluripotent stem cells-derived islet-like clusters improves therapeutic activity in diabetic mice. Frontiers in Endocrinology (Lausanne). 2021;12:635405
55. Parent AV et al. Development of a scalable method to isolate subsets of stem cell-derived pancreatic islet cells. Stem Cell Reports. 2022;17(4):979-992
56. Davis JC et al. Glucose response by stem cell-derived β cells in vitro is inhibited by a bottleneck in glycolysis. Cell Reports. 2020;31(6):107623
57. Jang D et al. Single cell glucose-stimulated insulin secretion assay using nanowell-in-microwell plates. Lab on a Chip. 2024;24(18):4232-4241
58. Zanfrini E et al. Generation and application of novel hES cell reporter lines for the differentiation and maturation of hPS cell-derived islet-like clusters. Scientific Reports. 2024;14(1):19863
59. Shilleh AH, Beard S, Russ HA. Enrichment of stem cell-derived pancreatic beta-like cells and controlled graft size through pharmacological removal of proliferating cells. Stem Cell Reports. 2023;18(6):1284-1294
60. Barra JM et al. Cryopreservation of stem cell-derived β-like cells enriches for insulin-producing cells with improved function. Diabetes. 2024;73(10):1687-1696
61. King AJ et al. Normal relationship of beta- and non-beta-cells not needed for successful islet transplantation. Diabetes. 2007;56(9):2312-2318
62. Peterson QP et al. A method for the generation of human stem cell-derived alpha cells. Nature Communications. 2020;11(1):2241
63. Jun Y et al. Engineered vasculature induces functional maturation of pluripotent stem cell-derived islet organoids. Developmental Cell. 20 May 2025:S1534-5807(25)00262-X. DOI: 10.1016/j.devcel.2025.04.024
64. Vegas AJ et al. Long-term glycemic control using polymer-encapsulated human stem cell-derived beta cells in immune-competent mice. Nature Medicine. 2016;22(3):306-311
65. Balboa D et al. Insulin mutations impair beta-cell development in a patient-derived iPSC model of neonatal diabetes. eLife. 2018;7:e38519
66. Hua H et al. iPSC-derived β cells model diabetes due to glucokinase deficiency. The Journal of Clinical Investigation. 2017;127(3):1115
67. Cujba AM et al. An HNF1α truncation associated with maturity-onset diabetes of the young impairs pancreatic progenitor differentiation by antagonizing HNF1β function. Cell Reports. 2022;38(9):110425
68. Kachamakova-Trojanowska N, Stepniewski J, Dulak J. Human iPSCs-derived endothelial cells with mutation in HNF1A as a model of maturity-onset diabetes of the young. Cells. 2019;8(11):1440
69. Ma H et al. Metabolic rescue in pluripotent cells from patients with mtDNA disease. Nature. 2015;524(7564):234-238
70. Lorenz C et al. Human iPSC-derived neural progenitors are an effective drug discovery model for neurological mtDNA disorders. Cell Stem Cell. 2017;20(5):659-674.e9
71. Lee NS et al. A novel dual-color reporter for identifying insulin-producing beta-cells and classifying heterogeneity of insulinoma cell lines. PLoS One. 2012;7(4):e35521
72. Bayly CL et al. An INSULIN and IAPP dual reporter enables tracking of functional maturation of stem cell-derived insulin producing cells. Molecular Metabolism. 2024;89:102017
73. Fishman JA. Infection in organ transplantation. American Journal of Transplantation. 2017;17(4):856-879
74. Wang X et al. Advancements and challenges in immune protection strategies for islet transplantation. Journal of Diabetes. 2025;17(1):e70048
75. Deuse T et al. Hypoimmunogenic derivatives of induced pluripotent stem cells evade immune rejection in fully immunocompetent allogeneic recipients. Nature Biotechnology. 2019;37(3):252-258
76. Han X et al. Generation of hypoimmunogenic human pluripotent stem cells. Proceedings of the National Academy of Sciences of the United States of America. 2019;116(21):10441-10446
77. Scharp DW, Marchetti P. Encapsulated islets for diabetes therapy: History, current progress, and critical issues requiring solution. Advanced Drug Delivery Reviews. 2014;67-68:35-73
78. Purpura KA et al. Systematic engineering of 3D pluripotent stem cell niches to guide blood development. Biomaterials. 2012;33(5):1271-1280
79. Kirk K et al. Human embryonic stem cell derived islet progenitors mature inside an encapsulation device without evidence of increased biomass or cell escape. Stem Cell Research. 2014;12(3):807-814
80. D'Amour KA et al. Production of pancreatic hormone-expressing endocrine cells from human embryonic stem cells. Nature Biotechnology. 2006;24(11):1392-1401
81. Marfil-Garza BA, Shapiro AMJ, Kin T. Clinical islet transplantation: Current progress and new frontiers. Journal of Hepato-Biliary-Pancreatic Sciences. 2021;28(3):243-254
82. Shapiro AM et al. Islet transplantation in seven patients with type 1 diabetes mellitus using a glucocorticoid-free immunosuppressive regimen. The New England Journal of Medicine. 2000;343(4):230-238
83. Tomei AA et al. Device design and materials optimization of conformal coating for islets of Langerhans. Proceedings of the National Academy of Sciences of the United States of America. 2014;111(29):10514-10519
84. Lo B, Parham L. Ethical issues in stem cell research. Endocrine Reviews. 2009;30(3):204-213
85. Hyun I. The bioethics of stem cell research and therapy. The Journal of Clinical Investigation. 2010;120(1):71-75
86. Sugarman J. Human stem cell ethics: Beyond the embryo. Cell Stem Cell. 2008;2(6):529-533
87. Volarevic V et al. Ethical and safety issues of stem cell-based therapy. International Journal of Medical Sciences. 2018;15(1):36-45
88. Sipp D et al. Marketing of unproven stem cell-based interventions: A call to action. Science Translational Medicine. 2017;9(397):eaag0426
89. Veres A et al. Charting cellular identity during human in vitro β-cell differentiation. Nature. 2019;569(7756):368-373
90. Angermueller C et al. Deep learning for computational biology. Molecular Systems Biology. 2016;12(7):878
91. Nosrati H, Nosrati M. Artificial intelligence in regenerative medicine: Applications and implications. Biomimetics (Basel). 2023;8(5):442
92. Grassi L et al. Organoids as a new model for improving regenerative medicine and cancer personalized therapy in renal diseases. Cell Death & Disease. 2019;10(3):201
93. Templer S. Closed-loop insulin delivery systems: Past, present, and future directions. Frontiers in Endocrinology (Lausanne). 2022;13:919942
94. Millman JR, Pagliuca FW. Autologous pluripotent stem cell-derived β-like cells for diabetes cellular therapy. Diabetes. 2017;66(5):1111-1120

[1] 1. Campbell JE, Newgard CB. Mechanisms controlling pancreatic islet cell function in insulin secretion. Nature Reviews. Molecular Cell Biology. 2021;22(2):142-158

[2] 2. Röder PV et al. Pancreatic regulation of glucose homeostasis. Experimental & Molecular Medicine. 2016;48(3):e219

[3] 3. Pisania A et al. Quantitative analysis of cell composition and purity of human pancreatic islet preparations. Laboratory Investigation. 2010;90(11):1661-1675

[4] 4. Bosco D et al. Unique arrangement of alpha- and beta-cells in human islets of Langerhans. Diabetes. 2010;59(5):1202-1210

[5] 5. Segerstolpe Å et al. Single-cell transcriptome profiling of human pancreatic islets in health and type 2 diabetes. Cell Metabolism. 2016;24(4):593-607

[6] 6. Hogrebe NJ, Ishahak M, Millman JR. Developments in stem cell-derived islet replacement therapy for treating type 1 diabetes. Cell Stem Cell. 2023;30(5):530-548

[7] 7. Wang S et al. Transplantation of chemically induced pluripotent stem-cell-derived islets under abdominal anterior rectus sheath in a type 1 diabetes patient. Cell. 2024;187(22):6152-6164.e18

[8] 8. Pagliuca FW et al. Generation of functional human pancreatic β cells in vitro. Cell. 2014;159(2):428-439

[9] 9. Ricordi C et al. Automated method for isolation of human pancreatic islets. Diabetes. 1988;37(4):413-420

[10] 10. Lehmann R et al. Superiority of small islets in human islet transplantation. Diabetes. 2007;56(3):594-603

[11] 11. Lakey JR, Mirbolooki M, Shapiro AM. Current status of clinical islet cell transplantation. Methods in Molecular Biology. 2006;333:47-104

[12] 12. Kin T et al. Enhancing the success of human islet isolation through optimization and characterization of pancreas dissociation enzyme. American Journal of Transplantation. 2007;7(5):1233-1241

[13] 13. Ichii H et al. Rescue purification maximizes the use of human islet preparations for transplantation. American Journal of Transplantation. 2005;5(1):21-30

[14] 14. Toso C et al. Factors affecting human islet of Langerhans isolation yields. Transplantation Proceedings. 2002;34(3):826-827

[15] 15. Shapiro AM, Pokrywczynska M, Ricordi C. Clinical pancreatic islet transplantation. Nature Reviews. Endocrinology. 2017;13(5):268-277

[16] 16. Lemos JRN, Skyler JS. Challenges in beta cell replacement for type 1 diabetes. Hormone Research in Pædiatrics. 2025;98:435-449

[17] 17. Matsumoto S. Clinical allogeneic and autologous islet cell transplantation: Update. Diabetes and Metabolism Journal. 2011;35(3):199-206

[18] 18. Rezania A et al. Reversal of diabetes with insulin-producing cells derived in vitro from human pluripotent stem cells. Nature Biotechnology. 2014;32(11):1121-1133

[19] 19. Nair GG et al. Recapitulating endocrine cell clustering in culture promotes maturation of human stem-cell-derived β cells. Nature Cell Biology. 2019;21(2):263-274

[20] 20. Jin W, Jiang W. Stepwise differentiation of functional pancreatic β cells from human pluripotent stem cells. Cell Regeneration. 2022;11(1):24

[21] 21. Thomson JA et al. Embryonic stem cell lines derived from human blastocysts. Science. 1998;282(5391):1145-1147

[22] 22. Rossant J. Stem cells and early lineage development. Cell. 2008;132(4):527-531

[23] 23. Murry CE, Keller G. Differentiation of embryonic stem cells to clinically relevant populations: Lessons from embryonic development. Cell. 2008;132(4):661-680

[24] 24. Evans MJ, Kaufman MH. Establishment in culture of pluripotential cells from mouse embryos. Nature. 1981;292(5819):154-156

[25] 25. Takahashi K, Yamanaka S. Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell. 2006;126(4):663-676

[26] 26. Takahashi K et al. Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell. 2007;131(5):861-872

[27] 27. Maehr R et al. Generation of pluripotent stem cells from patients with type 1 diabetes. Proceedings of the National Academy of Sciences of the United States of America. 2009;106(37):15768-15773

[28] 28. Millman JR et al. Generation of stem cell-derived β-cells from patients with type 1 diabetes. Nature Communications. 2016;7:11463

[29] 29. Yamada M et al. Human oocytes reprogram adult somatic nuclei of a type 1 diabetic to diploid pluripotent stem cells. Nature. 2014;510(7506):533-536

[30] 30. Schwank G et al. Functional repair of CFTR by CRISPR/Cas9 in intestinal stem cell organoids of cystic fibrosis patients. Cell Stem Cell. 2013;13(6):653-658

[31] 31. Lian Q et al. Functional mesenchymal stem cells derived from human induced pluripotent stem cells attenuate limb ischemia in mice. Circulation. 2010;121(9):1113-1123

[32] 32. Yu J et al. Induced pluripotent stem cell lines derived from human somatic cells. Science. 2007;318(5858):1917-1920

[33] 33. Kumar SS et al. Recent developments in β-cell differentiation of pluripotent stem cells induced by small and large molecules. International Journal of Molecular Sciences. 2014;15(12):23418-23447

[34] 34. Jiang W et al. In vitro derivation of functional insulin-producing cells from human embryonic stem cells. Cell Research. 2007;17(4):333-344

[35] 35. Loh KM et al. Efficient endoderm induction from human pluripotent stem cells by logically directing signals controlling lineage bifurcations. Cell Stem Cell. 2014;14(2):237-252

[36] 36. D'Amour KA et al. Efficient differentiation of human embryonic stem cells to definitive endoderm. Nature Biotechnology. 2005;23(12):1534-1541

[37] 37. Zorn AM, Wells JM. Vertebrate endoderm development and organ formation. Annual Review of Cell and Developmental Biology. 2009;25:221-251

[38] 38. Arroyave F, Uscátegui Y, Lizcano F. From iPSCs to pancreatic β cells: Unveiling molecular pathways and enhancements with vitamin C and retinoic acid in diabetes research. International Journal of Molecular Sciences. 2024;25(17):9654

[39] 39. Johannesson M et al. FGF4 and retinoic acid direct differentiation of hESCs into PDX1-expressing foregut endoderm in a time- and concentration-dependent manner. PLoS One. 2009;4(3):e4794

[40] 40. Gu G, Dubauskaite J, Melton DA. Direct evidence for the pancreatic lineage: NGN3+ cells are islet progenitors and are distinct from duct progenitors. Development. 2002;129(10):2447-2457

[41] 41. Jennings RE et al. Human pancreas development. Development. 2015;142(18):3126-3137

[42] 42. Shih HP et al. A Notch-dependent molecular circuitry initiates pancreatic endocrine and ductal cell differentiation. Development. 2012;139(14):2488-2499

[43] 43. Scavuzzo MA et al. Endocrine lineage biases arise in temporally distinct endocrine progenitors during pancreatic morphogenesis. Nature Communications. 2018;9(1):3356

[44] 44. Cai Q et al. Prospectively isolated NGN3-expressing progenitors from human embryonic stem cells give rise to pancreatic endocrine cells. Stem Cells Translational Medicine. 2014;3(4):489-499

[45] 45. Murtaugh LC et al. Notch signaling controls multiple steps of pancreatic differentiation. Proceedings of the National Academy of Sciences of the United States of America. 2003;100(25):14920-14925

[46] 46. Silva IBB et al. Stem cells differentiation into insulin-producing cells (IPCs): Recent advances and current challenges. Stem Cell Research & Therapy. 2022;13(1):309

[47] 47. Memon B et al. Enhanced differentiation of human pluripotent stem cells into pancreatic progenitors co-expressing PDX1 and NKX6.1. Stem Cell Research & Therapy. 2018;9(1):15

[48] 48. Sali S et al. A perfect islet: Reviewing recent protocol developments and proposing strategies for stem cell derived functional pancreatic islets. Stem Cell Research & Therapy. 2025;16(1):160

[49] 49. Velazco-Cruz L et al. Acquisition of dynamic function in human stem cell-derived β cells. Stem Cell Reports. 2019;12(2):351-365

[50] 50. Talavera-Adame D et al. Endothelial cells in co-culture enhance embryonic stem cell differentiation to pancreatic progenitors and insulin-producing cells through BMP signaling. Stem Cell Reviews and Reports. 2011;7(3):532-543

[51] 51. Barsby T, Otonkoski T. Maturation of beta cells: Lessons from in vivo and in vitro models. Diabetologia. 2022;65(6):917-930

[52] 52. Feyen DAM et al. Metabolic maturation media improve physiological function of human iPSC-derived cardiomyocytes. Cell Reports. 2020;32(3):107925

[53] 53. Aguayo-Mazzucato C et al. Thyroid hormone promotes postnatal rat pancreatic β-cell development and glucose-responsive insulin secretion through MAFA. Diabetes. 2013;62(5):1569-1580

[54] 54. Molakandov K et al. Selection for CD26(−) and CD49A(+) cells from pluripotent stem cells-derived islet-like clusters improves therapeutic activity in diabetic mice. Frontiers in Endocrinology (Lausanne). 2021;12:635405

[55] 55. Parent AV et al. Development of a scalable method to isolate subsets of stem cell-derived pancreatic islet cells. Stem Cell Reports. 2022;17(4):979-992

[56] 56. Davis JC et al. Glucose response by stem cell-derived β cells in vitro is inhibited by a bottleneck in glycolysis. Cell Reports. 2020;31(6):107623

[57] 57. Jang D et al. Single cell glucose-stimulated insulin secretion assay using nanowell-in-microwell plates. Lab on a Chip. 2024;24(18):4232-4241

[58] 58. Zanfrini E et al. Generation and application of novel hES cell reporter lines for the differentiation and maturation of hPS cell-derived islet-like clusters. Scientific Reports. 2024;14(1):19863

[59] 59. Shilleh AH, Beard S, Russ HA. Enrichment of stem cell-derived pancreatic beta-like cells and controlled graft size through pharmacological removal of proliferating cells. Stem Cell Reports. 2023;18(6):1284-1294

[60] 60. Barra JM et al. Cryopreservation of stem cell-derived β-like cells enriches for insulin-producing cells with improved function. Diabetes. 2024;73(10):1687-1696

[61] 61. King AJ et al. Normal relationship of beta- and non-beta-cells not needed for successful islet transplantation. Diabetes. 2007;56(9):2312-2318

[62] 62. Peterson QP et al. A method for the generation of human stem cell-derived alpha cells. Nature Communications. 2020;11(1):2241

[63] 63. Jun Y et al. Engineered vasculature induces functional maturation of pluripotent stem cell-derived islet organoids. Developmental Cell. 20 May 2025:S1534-5807(25)00262-X. DOI: 10.1016/j.devcel.2025.04.024

[64] 64. Vegas AJ et al. Long-term glycemic control using polymer-encapsulated human stem cell-derived beta cells in immune-competent mice. Nature Medicine. 2016;22(3):306-311

[65] 65. Balboa D et al. Insulin mutations impair beta-cell development in a patient-derived iPSC model of neonatal diabetes. eLife. 2018;7:e38519

[66] 66. Hua H et al. iPSC-derived β cells model diabetes due to glucokinase deficiency. The Journal of Clinical Investigation. 2017;127(3):1115

[67] 67. Cujba AM et al. An HNF1α truncation associated with maturity-onset diabetes of the young impairs pancreatic progenitor differentiation by antagonizing HNF1β function. Cell Reports. 2022;38(9):110425

[68] 68. Kachamakova-Trojanowska N, Stepniewski J, Dulak J. Human iPSCs-derived endothelial cells with mutation in HNF1A as a model of maturity-onset diabetes of the young. Cells. 2019;8(11):1440

[69] 69. Ma H et al. Metabolic rescue in pluripotent cells from patients with mtDNA disease. Nature. 2015;524(7564):234-238

[70] 70. Lorenz C et al. Human iPSC-derived neural progenitors are an effective drug discovery model for neurological mtDNA disorders. Cell Stem Cell. 2017;20(5):659-674.e9

[71] 71. Lee NS et al. A novel dual-color reporter for identifying insulin-producing beta-cells and classifying heterogeneity of insulinoma cell lines. PLoS One. 2012;7(4):e35521

[72] 72. Bayly CL et al. An INSULIN and IAPP dual reporter enables tracking of functional maturation of stem cell-derived insulin producing cells. Molecular Metabolism. 2024;89:102017

[73] 73. Fishman JA. Infection in organ transplantation. American Journal of Transplantation. 2017;17(4):856-879

[74] 74. Wang X et al. Advancements and challenges in immune protection strategies for islet transplantation. Journal of Diabetes. 2025;17(1):e70048

[75] 75. Deuse T et al. Hypoimmunogenic derivatives of induced pluripotent stem cells evade immune rejection in fully immunocompetent allogeneic recipients. Nature Biotechnology. 2019;37(3):252-258

[76] 76. Han X et al. Generation of hypoimmunogenic human pluripotent stem cells. Proceedings of the National Academy of Sciences of the United States of America. 2019;116(21):10441-10446

[77] 77. Scharp DW, Marchetti P. Encapsulated islets for diabetes therapy: History, current progress, and critical issues requiring solution. Advanced Drug Delivery Reviews. 2014;67-68:35-73

[78] 78. Purpura KA et al. Systematic engineering of 3D pluripotent stem cell niches to guide blood development. Biomaterials. 2012;33(5):1271-1280

[79] 79. Kirk K et al. Human embryonic stem cell derived islet progenitors mature inside an encapsulation device without evidence of increased biomass or cell escape. Stem Cell Research. 2014;12(3):807-814

[80] 80. D'Amour KA et al. Production of pancreatic hormone-expressing endocrine cells from human embryonic stem cells. Nature Biotechnology. 2006;24(11):1392-1401

[81] 81. Marfil-Garza BA, Shapiro AMJ, Kin T. Clinical islet transplantation: Current progress and new frontiers. Journal of Hepato-Biliary-Pancreatic Sciences. 2021;28(3):243-254

[82] 82. Shapiro AM et al. Islet transplantation in seven patients with type 1 diabetes mellitus using a glucocorticoid-free immunosuppressive regimen. The New England Journal of Medicine. 2000;343(4):230-238

[83] 83. Tomei AA et al. Device design and materials optimization of conformal coating for islets of Langerhans. Proceedings of the National Academy of Sciences of the United States of America. 2014;111(29):10514-10519

[84] 84. Lo B, Parham L. Ethical issues in stem cell research. Endocrine Reviews. 2009;30(3):204-213

[85] 85. Hyun I. The bioethics of stem cell research and therapy. The Journal of Clinical Investigation. 2010;120(1):71-75

[86] 86. Sugarman J. Human stem cell ethics: Beyond the embryo. Cell Stem Cell. 2008;2(6):529-533

[87] 87. Volarevic V et al. Ethical and safety issues of stem cell-based therapy. International Journal of Medical Sciences. 2018;15(1):36-45

[88] 88. Sipp D et al. Marketing of unproven stem cell-based interventions: A call to action. Science Translational Medicine. 2017;9(397):eaag0426

[89] 89. Veres A et al. Charting cellular identity during human in vitro β-cell differentiation. Nature. 2019;569(7756):368-373

[90] 90. Angermueller C et al. Deep learning for computational biology. Molecular Systems Biology. 2016;12(7):878

[91] 91. Nosrati H, Nosrati M. Artificial intelligence in regenerative medicine: Applications and implications. Biomimetics (Basel). 2023;8(5):442

[92] 92. Grassi L et al. Organoids as a new model for improving regenerative medicine and cancer personalized therapy in renal diseases. Cell Death & Disease. 2019;10(3):201

[93] 93. Templer S. Closed-loop insulin delivery systems: Past, present, and future directions. Frontiers in Endocrinology (Lausanne). 2022;13:919942

[94] 94. Millman JR, Pagliuca FW. Autologous pluripotent stem cell-derived β-like cells for diabetes cellular therapy. Diabetes. 2017;66(5):1111-1120