Acoustic virtual 3D scaffold for direct-interacting tumor organoid–immune cell coculture systems

Abstract

Three-dimensional (3D) cell culture has revolutionized life sciences, particularly in organoid technologies. Traditional bioscaffold materials, however, complicate the detachment of tumor organoids and hamper the routine use of organoid–immune cell cocultures. Here, we show an acoustic virtual 3D scaffold (AV-Scaf) method to achieve 3D tumor organoid culture, enabling a direct-interacting tumor organoid–immune cell coculture system. The self-organization process of tumor cells is facilitated by a vortex acoustic field, which enables the cell bioassembly and ion channel activation. This approach can significantly enhance the influx of calcium ions, thereby accelerating intercellular interactions of cellular assemblies. We established scaffold-free melanoma and breast cancer organoids using AV-Scaf and cocultured melanoma organoids with T cells. We found that our coculture system resulted in a high activation state of T cells, characterized by notable up-regulation of granzyme B (2.82 to 17.5%) and interferon-γ (1.36 to 16%). AV-Scaf offers an efficient method for tumor organoid–immune cell studies, advancing cancer research and immunotherapy development.

An acoustically scaffold-free approach has been used to culture tumor organoids.

INTRODUCTION

Three-dimensional (3D) cell culture has significantly advanced the fields of life sciences and tissue engineering (1–5). Tumor organoids, which are self-organizing 3D cultures (6), serve as powerful preclinical models due to their preservation of the morphological, genetic, and functional characteristics of the original tissues (7–9). To replicate the tumor microenvironment more accurately, a coculture system involving organoids and other cellular components, such as immune cells, has been developed (8, 10, 11). This system facilitates preclinical testing of chemotherapies, targeted therapies, and immunotherapies (8), offering a robust platform for drug screening and tailoring individualized treatments. Notably, the activation of T cells in the coculture system plays a pivotal role in simulating and studying immune responses within the tumor microenvironment (11, 12). Activated T cells can recognize and attack tumor cells, thereby mimicking the natural immune response to tumors in vitro. However, traditional organoid culture methods, including Matrigel (12), droplets (13, 14), and microchambers (7, 15), provide a 3D structural support yet limit the direct interaction of tumor cells with cocultured cells, hindering the T cell activation efficiency of coculture systems.

Cell responses to mechanical stimuli are crucial determinants of cell fate decisions (4, 16). For instance, the stiffness of matrix materials influences cell proliferation and differentiation in 3D organoid cultures through mechanosensitive transcriptional regulators (4, 16–18). Ultrasound (US) is a mechanical wave that can exert forces on cells and has emerged as a promising tool in organoid technologies, providing a contact-free method to manipulate and stimulate cells (17–22). The US-induced physiological processes make it an appealing alternative to physical outputs of 3D bioscaffolds.

In this study, we developed an acoustic virtual 3D scaffold (AV-Scaf) method to achieve 3D tumor organoid culture, which enabled a direct-interacting tumor organoid–immune cell coculture system. Specifically, AV-Scaf involves a designed vortex acoustic field generated by a 20-MHz US transducer and a lens, achieving contact-free clustering and mechanical stimulation of tumor cells. The ion channel activation and calcium ion influx were found to be critical factors for improving intercellular interactions and facilitating the self-organization process of cell assemblies. To demonstrate the utility of AV-Scaf, we established melanoma and breast cancer organoids and cocultured melanoma organoids with T cells. Compared to the Matrigel-based method, T cells in the direct-interacting coculture system by AV-Scaf showed a high activation state, characterized by notable up-regulation of granzyme B (GZMB) (2.82% to 17.5%) and interferon-γ (IFN-γ) (1.36% to 16%). Our AV-Scaf enables a direct-interacting tumor organoid–immune cell coculture system, providing a more effective tumor-immune microenvironment in drug development and precision personalized therapies.

RESULTS

AV-Scaf for scaffold-free tumor organoids

Acoustic technologies have emerged as a cutting-edge strategy to manipulate and structure cells in 3D (19, 20). Using a contact-free acoustic field to organize cellular components offers a significant advantage by eliminating the biophysical cues from solid scaffolds that may influence cellular behavior (17). US can be used to trap, manipulate, or stimulate cells for tissue-engineering applications. To foster the formation of 3D organoids, we applied AV-Scaf to achieve cell assembly and cell stimulation. Figure 1A provides a comprehensive depiction of AV-Scaf used in this study. AV-Scaf involves the generation of a focused acoustic vortex by a US transducer and a lens, and this configuration is intended to achieve the clustering of tumor cells within the focal plane (Fig. 1B). The designed vortex-focused sound field clusters tumor cells at optimal locations and aggregates them into appropriately sized clusters while also applying noncontact mechanical stimulation. This fosters intercellular communication and induces further self-organization into organoids without reducing cell viability. Acoustic radiation force and streaming are used to manipulate tumor cells into clusters without direct contact. In addition to cell bioassembly, US can trigger cell reprogramming by mechanical stimuli that activate ion channels (17, 18, 23–26). For example, US can activate different ion channels, including the TRP, TREK, TRAAK, and PIEZO families, thereby changing the behaviors of cells (17). In our RNA sequencing (RNA-seq) analysis, US stimulation can significantly enhance the influx of calcium ions, thereby accelerating the process of intercellular interactions based on cellular assemblies. Figure 1C demonstrates the formation process of scaffold-free organoid systems. Notably, the traditional tumor organoid models have several limitations. The most widely used scaffold materials for organoid culture are animal-derived basement membrane matrices, such as Matrigel; they are poorly tunable, exhibit substantial batch-to-batch variations, and can cause unexpected stimulation of cells (27). More problematically, the establishment of a coculture system involves the removal of these matrix materials, unavoidably inflicting mechanical damage to the organoids. To solve this issue, we applied the focused vortex sound field as a virtual 3D scaffold to accelerate the self-organization of tumor cells. Because of the matrix-free nature, the 3D tumor organoid models obtained by AV-Scaf are formed in a 2D environment. Therefore, our scaffold-free tumor organoids are highly scalable and are easier to establish coculture systems that more accurately represent the tumor microenvironment.

Fig. 1. Schematic of AV-Scaf for scaffold-free tumor organoids.

(A) Schematic illustration of the AV-Scaf strategy. (B) Schematics of cell movement and clustering within the US field (left) and corresponding microscopic images before and after melanoma cell clustering (right). Scale bars, 500 μm. Created using Figdraw. (C) Schematic illustration of the formation process of scaffold-free organoid systems by AV-Scaf. Scale bars, 100 μm. (D) Photograph and exploded-view schematic illustration of the transducer. Scale bar, 5 mm. (E) Electrical impedance magnitude and phase of the transducer as a function of frequency, and the measured pulse-echo waveform and normalized frequency spectrum. (F) Design parameters and photograph of the vortex lens. Scale bar, 5 mm. (G) Simulated amplitudes (top) and phases (bottom) on the xy plane in different z-axis planes. (H) Simulated 3D shape of the acoustic fields and the force in the horizontal direction. (I) Top view of simulated intensity (left) and phase (right) on the xy plane in the focal plane.

To design US-based systems for achieving the above targets, consideration of the basic physical principles is essential. Ultrasonic transducers used for acoustic assembly applications often have frequencies higher than 1 MHz (17). Ion channel activation can occur across a broad frequency range from tens of kilohertz to tens of megahertz (24, 28, 29). For efficient US transmission into the culture medium, the plates must closely match the acoustic impedance of water. In addition, interfaces can be shaped to focus sound waves to precise locations, using methods such as lenses or more complex patterns like holograms (30). The resolution of the focused plane is determined by the wavelength, where higher frequencies provide higher resolution for focusing. Figure 1D shows the photograph of our fabricated 20-MHz transducer, and the detailed structure is shown on the right. The design considerations for ultrasonic transducers include frequency for sound field precision and size for stimulation efficiency. Basically, a transducer stack consists of a square, Au-sputtered LiNbO₃ single crystal and an E-solder backing layer connected to a coaxial wire and is secured in a brass housing using epoxy resin. A thin film of parylene C is then deposited on the transducer. Figure 1E shows the transducer frequency and echo characterization. Acoustic vortex beams have recently attracted considerable attention. When an acoustic vortex beam interacts with an object, angular momentum is transferred between the vortex beam and the object. Focusing on a vortex beam can greatly enhance the interaction between the vortex beam and cells, and thus, the cells can be trapped and rotated simultaneously. Figure 1F shows the design parameters and photograph of the vortex lens. To better characterize the vortex property of the focused beam, we show the simulated amplitudes (top) and phases (bottom) on the xy plane in different z-axis planes (Fig. 1G). We further present the 3D shape of the acoustic fields in the numerical simulation and the direction of the radiation force (Fig. 1H). Figure 1I shows the top view of simulated intensity (left) and phase (right) in the focal plane, indicating that the intensity is highly focused in the center and a phase vortex around it. We intend to use these tunable sound fields to develop scaffold-free 3D culture strategies.

Cell self-organization induced by ion channel activation

To validate the capability of AV-Scaf in establishing scaffold-free tumor organoids, we first designed the corresponding culture system (Fig. 2A). A translucent and sonolucent polyolefin (PO) film was adhered to the bottom of the polystyrene (PS) chamber to achieve the lossless acoustic propagation. Given the requirement for tumor organoids to culture for an extended period, it is critical that the culture environment does not adversely affect the viability of the organoids. Therefore, PS with good biocompatibility was chosen for chamber fabrication and an acoustically transparent PO membrane was used to ensure efficient US propagation. To evaluate the performance of the devices, we conducted acoustic vortex and cell clustering experiments (fig. S1). We found that the tumor cells can be assembled as cell clusters after being treated with AV-Scaf for 2 min. US is a commonly used method for cell manipulation due to its excellent biocompatibility (31). However, long-time exposure to US and high US intensity can cause damage to cells. To ensure that the AV-Scaf method does not adversely affect cell viability, we have investigated the process parameters of AV-Scaf (Fig. 2, B to D). To determine the efficiency of organoid formation, we assessed the morphology of organoids formed after 5 days of culture treated with AV-Scaf for 2 min and different driving voltages (Fig. 2B). For melanoma and breast cancer groups, we found that a small applied voltage of 60 mV may not have sufficient mechanical stimuli to activate ion channels because no obvious cell self-organization was observed. Notably, the 140-mV group would generate too large cell clusters and fail to reach adequate growth due to enhanced cell assembly volumes. We estimated the cell viability of organoids treated with AV-Scaf for different time periods and voltages (Fig. 2C). We found that the cell viability was significantly reduced when exposure time crossed the critical value of 240 s. In addition, an applied voltage of 180 mV and an exposure time of 180 s also affect the cell viability. These results verified our conjecture that AV-Scaf needs to have suitable process parameters. Therefore, we chose an applied voltage of 100 mV as a trade-off. We measured the organoid diameter treated with a voltage of 100 mV for 2 min (Fig. 2D). Figure 2 (E and F) shows the breast cancer and melanoma organoid growth images, respectively. As we supposed, cells treated with AV-Scaf in culture planes showed obvious self-organization behaviors 1 day later. Matrigel has been widely used as a matric material for 3D organoid culture (12). We further compared the morphological characteristics of tumor organoids obtained by the AV-Scaf and the Matrigel-based method. As shown in Fig. 2G, the size and morphology of breast cancer and melanoma organoids by AV-Scaf appeared similar to those formed in a Matrigel reference culture. To further compare the differences between the classical Matrigel method and our AV-Scaf approach, we conducted immunofluorescence (IF) staining on tumor organoids derived from both methods (Fig. 2, H and I). The results demonstrated that organoids generated by both techniques could express the specific markers associated with their origin. This indicates that regardless of their morphology or specific markers, the organoids produced by both methods exhibit consistency in their characteristics. To verify that the tumor organoids produced by the AV-Scaf method retain the structural integrity consistent with patient tissues, we performed hematoxylin and eosin (H&E) and immunohistochemistry (IHC) staining on tumor tissues from patients with melanoma and on melanoma organoids generated by AV-Scaf (Fig. 2J). The results indicated that the organoids produced by AV-Scaf have tissue architecture identical to that of the patient’s tissues and expressed the same markers.

Fig. 2. Breast cancer and melanoma organoids via the developed AV-Scaf.

(A) Design of AV-Scaf platform for culturing organoids. (B) Representative bright-field images of organoids after 5 days of culture treated with AV-Scaf for 2 min and different voltages. Scale bars, 100 μm. (C) Cell viability of organoids treated with AV-Scaf for different time periods and voltages. Data are presented as means ± SD (n = 3). (D) Organoid diameter treated with a voltage of 100 mV for 2 min. Data are presented as means ± SD (n = 3). (E and F) Time-course images of breast cancer and melanoma organoids generated by AV-Scaf. Scale bars, 100 μm. (G) Representative microscopy images of breast cancer and melanoma organoids generated by AV-Scaf compared with Matrigel. Scale bars, 100 μm. (H and I) IF staining for HER2 in breast cancer organoids and for Melan-A in melanoma organoids, respectively. Scale bars, 100 μm. (J) H&E and IHC staining of AV-Scaf–based melanoma organoids and the corresponding tissues. Scale bars, 100 μm.

We explored potential mechanisms behind AV-Scaf for organoid formation. Melanoma is a highly representative tumor suitable for studying tumor-related mechanisms. To explore the mechanisms behind the AV-Scaf method, we conducted RNA-seq analysis on melanoma organoids produced by AV-Scaf. Compared with the control (patient-derived tumor cells untreated with AV-Scaf), Fig. 3A shows differentially expressed gene (DEG) statistics, with 464 significantly up-regulated genes and 186 significantly down-regulated genes. Figure 3B shows a correlation heatmap that demonstrates high consistency among biological replicates and significant differences between control and AV-Scaf groups. Principal components analysis clearly distinguishes control from stimulated samples (Fig. 3C). As shown in Fig. 3D, gene set enrichment analysis (GSEA) highlights significant enrichment in calcium-mediated signaling, tissue morphogenesis, and epithelial-to-mesenchymal transition pathways. Gene ontology (GO) enrichment analyses reveal significant enrichment in processes such as cell adhesion, calcium ion transport, and signal transduction (Fig. 3, E and F). GO enrichment analysis elucidates the biological processes and molecular functions predominantly affected by US stimulation. Figure 3E demonstrates GO terms enriched in organoid versus control, highlighting processes such as cell-substrate adhesion, cellular response to oxygen levels, and positive regulation of cell adhesion, all pivotal for tissue morphogenesis and cellular differentiation. The enrichment of calcium-mediated signaling (Fig. 3D, top) further corroborates the role of calcium ions as crucial secondary messengers in these processes. Figure 3F focuses on up-regulated genes, underscoring enriched terms related to tissue development, regulation of cell differentiation, and calcium ion transport. The enrichment of signal transduction pathways, particularly those involving calcium ions, aligns with the hypothesized mechanotransductive role of US stimulation, promoting calcium influx and subsequent downstream signaling cascades. Heatmap analysis of genes related to calcium and adhesion shows distinct expression patterns, indicating diverse regulatory responses to US stimulation (Fig. 3, G and H). The AV-Scaf method, though involving only brief US stimulation, has shown RNA-seq results to promote intracellular calcium influx and enhance cellular adhesion behaviors. This significantly accelerates interactions among cells within tumor clusters, thereby facilitating the self-organization process of tumor cells.

Fig. 3. Transcriptomic comparison of AV-Scaf–assisted tumor organoids and tumor cells.

(A) DEG statistics, with 464 significantly up-regulated genes and 186 significantly down-regulated genes. (B and C) Correlation heatmap and principal components analysis (PCA) between control and stimulated groups. (D) GSEA in calcium-mediated signaling, tissue morphogenesis, and epithelial-to-mesenchymal transition pathways. (E and F) GO enrichment analyses reveal significant enrichment in processes such as cell adhesion, calcium ion transport, and signal transduction. (G and H) Heatmap analysis of genes related to calcium and adhesion demonstrates unique expression profiles, suggesting varied regulatory responses to US stimulation. The gene set depicted in each heatmap is enriched from those genes that are most significantly up-regulated, closely aligning with the observed phenomena.

Figure 4A is a schematic illustration of the potential mechanism of AV-Scaf, showing that AV-Scaf significantly activates ion channels and enhances calcium ion flow, which may facilitate the self-organization process of cells. The sequencing results emphasize a close relationship between calcium ion influx and cell adhesion behaviors following US stimulation. The Venn diagram in Fig. 4B clearly shows that although a significant number of genes are unique to either calcium ion channels or cell adhesion, there is also a substantial overlap. This overlap suggests that several genes are co-regulated or potentially interact under US stimulation, affecting both calcium signaling and cellular adhesion mechanisms. In Fig. 4C, the volcano plot underscores the interconnectedness by showing significant changes in gene expression between organoids and controls. Key genes such as CDH1, essential for cell adhesion, and CXCR4, involved in signaling, are emphasized, indicating enhanced roles after US treatment. To validate the RNA-seq results, we conducted calcium ion imaging (Fig. 4, D, G, and H) and confocal observation of extracellular matrix (ECM) generation in two tumor organoids formed by AV-Scaf (Fig. 4, E and F). Figure 4D shows representative fluorescence microscopy images of cells stained with Fluo-4, with the highest fluorescence observed at 1 hour, indicating a transient spike in intracellular calcium levels immediately following US stimulation. The calcium ion imaging results align with gene sequencing data, which indicated the up-regulation of genes involved in calcium signaling pathways. The transient increase in calcium ion levels observed 1 hour after stimulation suggests that US induces a rapid influx of calcium, likely through mechanosensitive channels, as previously hypothesized. This influx acts as a secondary messenger, initiating various downstream signaling cascades that ultimately affect gene expression. Figure 4G displays the flow cytometry analysis using Fluo-4 AM. The histograms reveal a substantial increase in calcium ion fluorescence intensity 1 hour after stimulation, followed by a decrease at 24 hours, compared to the control group. This temporal change is quantified in Fig. 4H, where fluorescence intensity significantly peaks at 1 hour and then diminishes by 24 hours. Figure 4 (E and F) presents confocal microscopy images of breast cancer and melanoma organoids, respectively, stained for 4′,6-diamidino-2-phenylindole (DAPI; nuclei), fibronectin, and laminin. Cell clusters captured via US do not contain ECM; in contrast, self-organized tumor organoids generate ECM between the tumor cells. These images reveal the ECM composition in the organoids with AV-Scaf. In both organoid types, substantial ECM deposition is evident, marked by strong fibronectin (red) and laminin (green) signals, which merge to produce a yellow overlay in the composite images. The confocal microscopy results further validate the gene sequencing findings, particularly the enrichment of genes associated with cell adhesion, ECM organization, and cellular interactions. The substantial ECM generation observed in both breast cancer and melanoma organoids upon US stimulation confirms the involvement of calcium-mediated pathways in modulating the tumor microenvironment. The enhanced deposition of fibronectin and laminin, key components of the ECM, highlights the remodeling of the extracellular landscape, potentially influencing tumor progression and metastasis. To further demonstrate the significant impact of calcium ion influx on the formation of tumor organoids using the AV-Scaf method, we conducted calcium channel blockade (CCB) experiments (Fig. 4, I to K). Cells from the AV-Scaf method, with and without CCB, were collected for enzyme-linked immunosorbent assay (ELISA) analysis of three proteins: fibronectin, laminin, and collagen IV. The results indicated that the blockade of calcium channels significantly reduced the content of cell adhesion–related proteins. In addition, we observed that treating tumor cells with CCB significantly inhibited the formation of tumor organoids (fig. S2). This suggests a close link between calcium ion influx and cell adhesion and that blocking calcium ion entry further affects the self-organizing capabilities of the cells. By modulating calcium influx and cell adhesion, AV-Scaf could potentially be leveraged as a culturing strategy to alter the bioscaffold, thereby promoting cell self-organization and growth.

Fig. 4. The calcium ion imaging and confocal observation of ECM generation in tumor organoids with AV-Scaf.

(A) Enhancement of calcium ion influx through mechanosensitive ion channels upon US stimulation. (B) Venn diagram of DEGs gained after comparing calcium ion channel to cell adhesion. The intersection area represents specific characteristics of the calcium channel and cell adhesion process. (C) Volcano plot showing DEGs about up-regulated genes (yellow) and down-regulated genes (blue). All the enriched overlapped genes about calcium ion channel and cell adhesion process were significantly up-regulated. (B) and (C) analyze up-regulated genes to align closely with the underlying biological phenomena. (D) Fluorescence microscopy images of cells stained with Fluo-4 illustrate calcium ion levels at three time points: control (left), 1 hour (middle), and 24 hours (right). Scale bar, 100 μm. (E and F) Confocal microscopy images of breast cancer and melanoma organoids stained for DAPI (blue, nuclei), fibronectin (red), and laminin (green). The merged image shows the colocalization of fibronectin and laminin in the ECM, indicating significant ECM production with AV-Scaf. All images were taken in z-axis stacks. Scale bars, 100 μm. (G and H) Comparison of fluorescence intensity of control cells with cells at 1 and 24 hours after US stimulation via flow cytometry analysis. Data are presented as means ± SD (n = 3). (I to K) Quantitative analysis of fibronectin, laminin, and collagen IV in AV-Scaf–mediated cells with CCB treatment. Data are presented as means ± SD (n = 5).

Direct-interacting coculture system enables higher T cell activation efficiency

Figure 5A illustrates the establishment and analysis of a direct-interacting tumor organoid–T cell coculture system based on our AV-Scaf method. Our coculture design is aligned with clinical cancer treatments. Since patients with melanoma typically receive immunotherapy as a first-line treatment, we conducted cocultures of melanoma organoids with T cells to demonstrate the superiority of the AV-Scaf method. Initially, single-cell suspensions are subjected to AV-Scaf, leading to the formation of tumor cell clusters. These clusters are then cultivated into scaffold-free tumor organoids. To establish a tumor organoid–T cell coculture model, we obtained peripheral blood mononuclear cells (PBMCs) from the same patient. Subsequently, T cells are introduced to create a direct-interacting tumor organoid coculture system. Figure 5 (B to E) illustrates the activation profiles of T cells cocultured with tumor organoids prepared using Matrigel and AV-Scaf methods. Figure 5 (B and D) depicts representative flow cytometry plots showing the expression of GZMB (2.82% vs. 17.5%) and IFN-γ (1.36% vs. 16.0%) in CD8⁺ T cells, respectively. A substantial enhancement in T cell activation is observed when using the AV-Scaf method compared to Matrigel. As quantified in Fig. 5C, the percentage of CD45⁺CD8⁺GZMB⁺ cells was significantly higher in the AV-Scaf group than in the Matrigel group. Similarly, Fig. 5E shows that CD45⁺CD8⁺IFN-γ⁺ cells were also significantly more prevalent in the AV-Scaf group versus the Matrigel group. These findings suggest that the AV-Scaf method potentially provides a more effective microenvironment for T cell activation within the organoid coculture system. The absence of Matrigel in the tumor organoids produced by the AV-Scaf method facilitates direct contact between tumor cells and T cells, thereby enhancing T cell activation, which is crucial for immune coculture drug testing. This enhancement likely facilitates more robust interactions between T cells and tumor cells, thereby potentially increasing the efficacy of immunotherapeutic strategies. To validate the efficacy of the coculture system, we established coculture models with two ratios of T cells to tumor cells and explored the cytotoxic effects of different T cell ratios on tumor organoids. Figure 5F shows live/dead staining of melanoma organoids cocultured with T cells at 24 and 48 hours. Initially, a high number of live cells are visible; however, as time progresses to 48 hours, a significant increase in dead cells is observed. Figure 5 (G and H) shows the viability of organoids when cocultured with T cells at ratios of 2:1 and 5:1, respectively, measured at 24 and 48 hours. The results suggest a decrease in viability over time, more pronounced at the higher T cell ratio. Figure 5I depicts a transition from organoids encircled by T cells to disrupted structures, indicating effective T cell activity. Figure 5 (J and L) illustrates cytotoxicity percentages for the 2:1 and 5:1 T cell–to–tumor cell ratios. Increased T cell ratios lead to higher cytotoxicity, particularly at 48 hours, confirming T cell effectiveness in inducing organoid cell death. Figure 5 (K and M) shows the volume of organoids over time under different T cell ratios. There is a notable reduction in organoid volume, again more significant at a higher ratio of T cells, which correlates with the increased cytotoxicity observed. These results provide important insights into the dynamics of T cell–tumor interactions within a scaffold-free organoid model. The incorporation of programmed cell death protein 1 (PD-1) antibodies into our organoid-T cell coculture model underscores the promising applicability in the domain of immunotherapy. The scaffold-free nature of the organoid model, enabled by AV-Scaf, offers a more physiologically relevant context compared to traditional scaffold-based methods. This direct-interacting approach enables the examination of interactions between tumors and the immune system, providing more accurate insights into tumor biology and immunotherapy responses. In addition, applying this coculture model to different types of tumors and T cell subpopulations would help generalize these findings and identify specific conditions that maximize therapeutic efficacy. Furthermore, integrating this coculture system with high-throughput screening could facilitate the discovery of immunotherapeutic agents or combinations that enhance T cell–mediated cytotoxicity.

Fig. 5. The establishment and analysis of a direct-interacting tumor organoid–T cell coculture system facilitated by AV-Scaf.

(A) Schematic diagram outlines the process of creating the coculture system. (B and D) Representative flow cytometry plots for GZMB and IFN-γ expression in CD8⁺ T cells, respectively. (C and E) Percentages of CD45⁺CD8⁺GZMB⁺ T cells and CD45⁺CD8⁺IFN-γ⁺ T cells in the Matrigel and AV-Scaf methods. Data are presented as means ± SD (n = 3). (F) Fluorescence microscopy images show the viability of tumor organoids when cocultured with T cells across different time points (T cell-to-tumor cell ratio 2:1). Scale bars, 100 μm. (G and H) Viability of tumor organoids cocultured with T cells at ratios of 2:1 (G) and 5:1 (H), measured at 24 and 48 hours. Data are presented as means ± SD (n = 3). (I) Bright-field microscopy images show the effects of T cell–mediated cytotoxicity on AV-Scaf–based organoids (T cell-to-tumor cell ratio 2:1). Scale bars, 100 μm. (J and L) Cytotoxic effects of T cells on tumor organoids at different T cell–to–tumor cell ratios [2:1 in (J) and 5:1 in (L)] over time. Data are presented as means ± SD (n = 5). (K and M) Spheroid volume reduction of tumor organoids over time at different T cell–to–tumor cell ratios [2:1 in (K) and 5:1 in (M)]. Data are presented as means ± SD (n = 5).

DISCUSSION

Our study presents the AV-Scaf method, which uses a designed vortex acoustic field as a virtual 3D scaffold for the direct 3D culture of cells within a 2D environment. This method addresses critical limitations of traditional scaffold-based organoid culture systems by eliminating the need for bioscaffold materials, such as Matrigel, that can introduce biophysical cues influencing cellular behavior and complicate the detachment of organoids. By leveraging the mechanical properties of US, our AV-Scaf method facilitates the formation of scaffold-free tumor organoids and enables direct-interacting coculture systems, thereby providing a more efficient model for studying tumor-immune interactions. The application of a focused acoustic vortex facilitated the clustering of tumor cells, enabling their self-organization into 3D structures within a 2D environment. The virtual 3D scaffold created by the acoustic field effectively mimicked the support provided by traditional scaffold materials without the associated drawbacks. The traditional Matrigel-based method has long been recognized for its importance in organoid culture, effectively maintaining the morphology and viability of tumor cells. Our findings highlight the potential of AV-Scaf as an alternative to Matrigel, offering similar outcomes in organoid formation. A core feature of the AV-Scaf method lies in its ability to activate ion channels and enhance calcium ion flow, thereby promoting cell self-organization. Our RNA-seq analysis and calcium ion imaging experiments confirmed the significant up-regulation of genes involved in calcium-mediated signaling pathways and the transient increase in intracellular calcium levels following US stimulation. These molecular and cellular changes are consistent with the hypothesized mechanotransductive role of US, which facilitates the rapid influx of calcium ions through mechanosensitive channels, triggering downstream signaling cascades that drive cell self-organization and differentiation. The enrichment of genes associated with cell adhesion, ECM organization, and cellular interactions further supports the notion that AV-Scaf–induced calcium signaling plays a pivotal role in modulating the tumor microenvironment. Our coculture experiments with T cells demonstrated the potential of AV-Scaf–based organoids to provide a more accurate representation of the tumor microenvironment. The observed T cell activation efficiency in the organoid-immune coculture highlights the relevance of this model for immunotherapy research. In addition, the cytotoxic experiments with PD-1 antibodies underscores the considerable potential of our coculture model for immunotherapy applications. These findings suggest that the AV-Scaf method can effectively support the study of T cell–tumor interactions and the evaluation of immunotherapeutic strategies.

Our study underscores the importance of developing scalable and physiologically relevant organoid culture methods for advancing cancer research and therapeutic development. The AV-Scaf method, by circumventing the limitations of traditional scaffold materials, offers a robust and versatile platform for generating tumor organoids and direct-interacting coculture systems. The ability to modulate calcium signaling and ECM generation through US stimulation provides valuable insights into the mechanistic underpinnings of cell self-organization and tumor microenvironment remodeling. Furthermore, the scalability and simplicity of the AV-Scaf method make it an attractive option for high-throughput screening and personalized medicine applications. We will explore the application of AV-Scaf to a broader range of tumor types and immune cell subpopulations, as well as integrate this method with high-throughput screening technologies to accelerate the discovery of effective therapeutic agents. By providing a more reliable and scalable platform for organoid culture, the AV-Scaf method has the potential to significantly affect the field of tissue engineering and regenerative medicine, ultimately contributing to improved clinical outcomes for patients with cancer.

MATERIALS AND METHODS

Fabrication of a 20-MHz ultrasonic transducer

The 20-MHz transducer features a cylindrical copper housing with a 2-mm aperture drilled into the sidewall for wire egress, allowing the device to rest horizontally. Lithium niobate is chosen as the core piezoelectric material due to its pronounced piezoelectric effect and low dielectric constant, which are optimal for large-aperture sensors requiring impedance matching (50 ohms). The design of the transducer was optimized using PiezoCAD software, which relies on the Krimholtz Leedom Matthaei equivalent circuit model specifically for piezoelectric transducers. This optimization yielded a transducer dimension of 8 mm by 8 mm. Subsequently, a slightly larger lithium niobate plate was precision ground to achieve a thickness resonating at the desired frequency. An Au electrode was then sputtered onto one face of this adjusted plate via magnetron sputtering. The next step involved applying a layer of E-solder 3022 (with an acoustic impedance of approximately 5.9 MRayl) to the electrode-coated side of the lithium niobate plate. Following the curing process, the backing material was further reduced to a thickness of 1 mm. The lithium niobate and its backing layer were then cut to the simulated dimensions using a precision cutter. A connection was established by soldering a wire to the E-solder side and integrating it into the copper housing, which was also equipped with a soldered ground wire. The assembly was encapsulated within epoxy resin to ensure stability and insulation. Another Au electrode was subsequently sputtered onto the opposite side of the lithium niobate and onto the brass enclosure to establish a common ground. Last, a protective coating of parylene C film was deposited over the entire surface of the transducer, enhancing its durability and biocompatibility.

Impedance and phase measurement

Figure S3A illustrates the electrical testing setup for the ultrasonic transducer. The electrical characteristics of the transducer were assessed using an impedance analyzer (WK6500B, Wayne Kerr Electronics, UK). Impedance and phase measurements were performed on the 20-MHz ultrasonic transducer, with the findings presented in fig. S3B. Given the operational requirements of the transducer in conjunction with external circuits, it is imperative that the transducer’s impedance matches the internal resistance of these circuits, which is typically 50 ohms for most instrumentation. The optimal matching impedance value is derived from the resonance frequency impedance measurements.

Pulse-echo testing

The acoustic performance of an ultrasonic transducer is typically evaluated using the pulse-echo method. This method involves situating a quartz plate at the transducer’s focal point within a liquid medium and initiating transducer excitation. The emitted sound waves propagate to the quartz surface, and the transducer subsequently captures the reflected waves. This setup facilitates the measurement of the transducer’s center frequency (f_c) and bandwidth (BW). Figure S4A displays the setup for the acoustic testing of the ultrasonic transducer. The JSR pulse-echo receiver (DPR500, JSR, USA) is used both to excite the transducer and to capture the returning electrical signals. The echo waveform is visualized and analyzed using an oscilloscope (DSOX3024A, Keysight, USA), while further signal processing is conducted using a computer. Results from the pulse-echo test of the fabricated 20-MHz ultrasonic transducer are presented in fig. S4B. The center frequency of the ultrasonic transducer is calculated as follows

$$f_{\mathit{c}}=(f_{\mathit{1}}+f_{\mathit{2}})/2=(15.96+24.63)/2=20.3$$ (1)

The bandwidth is determined using the equation

$$\mathit{\text{BW}}=(f_{\mathit{2}}-f_{\mathit{1}})/f_{\mathit{c}}=(24.63+15.96)/20.3=42.7$$ (2)

where f₁ and f₂ represent the frequency points at which the echo spectrum is reduced by −6 dB, delineating the lower and upper frequency limits, respectively.

Design and fabrication of a high-frequency vortex sound lens

Vortex sound beams, characterized by their helical wavefront structures and annular intensity distributions, not only have spin angular momentum but also demonstrate orbital angular momentum. The design of a focusing vortex sound lens uses a Fresnel spiral diffraction grating, which involves alternating acoustically transparent and nontransparent spiral arms. The geometry of the mth arm of the spiral is mathematically dictated by a formula incorporating the focal length (F), the topological charge of the acoustic vortex (M), the wavelength (λ), and the number of arms (m)

$$r_m{(\mathrm{\theta })}^2={[\sqrt{r_0^2+F^2}+(\frac{M\mathrm{\theta }}{2\mathrm{\pi }}-m)\mathrm{\lambda }]}^2-F^2$$ (3)

For the practical application discussed here, a Fresnel spiral diffraction grating was crafted for operation at a frequency of 20 MHz with a focal length of 8 mm and a single spiral arm (m = 1). Figure S5A illustrates the theoretical design, while fig. S5B displays the corresponding mask designed for this purpose. The mask was fabricated using precision laser cutting techniques, with the resultant physical product depicted in fig. S5C. The operational principle of the designed grating relies on diffracting waves from opposing angles to converge at the focal point with opposite phases. This mechanism effectively creates a focused vortex sound beam, leveraging the unique properties of the Fresnel spiral structure to manipulate the acoustic waves’ angular momentum components.

Numerical simulation

In the design of the Fresnel spiral diffraction gratings, two adjacent spiral curves were delineated. These spirals were extended to render regions acoustically transparent, assigned a value of 1 (cyan regions in fig. S6A), and acoustically opaque, assigned a value of 0 (gray regions in fig. S6A). An incident plane wave pressure field, with an amplitude of 1 Pa, was introduced to the transparent region. All subsequent simulations were uniformly normalized, and the plane wave propagated along the z axis. Figure S6B presents the overall 3D simulation model, depicting the Fresnel spiral diffraction grating with the incident pressure field at the bottom and the water region above. The simulation was conducted within the pressure acoustics frequency domain. Figure S6C shows the mesh division of the model; the bottom part was divided using a free triangular mesh, and the entire model was then meshed by sweeping based on this initial division. The maximum element size of the mesh was maintained at one-fifth of the wavelength. Figure S7 shows the simulation results of various vortex acoustic fields based on Fresnel spiral diffraction grating.

Design and fabrication of the AV-Scaf culture system

The PS culture chambers, with an inner diameter of 5 mm and an outer diameter of 7 mm, were fabricated using a laser cutting process. A transparent and sonolucent PO film (3M) was integrated into the base of a PS chamber, optimizing for lossless acoustic wave propagation essential for the process. The chamber holder was prepared by using a high-resolution PμSL 3D printer (microArch S140, BMF Precision Technology Inc., Shenzhen, China). To drive transducers for acoustic vortex, the sinusoidal signal from a signal generator (SMB100A, Rohde & Schwarz, Germany) was amplified by a power amplifier (525LA, Electronics & Innovation Ltd., USA). To assess the performance of the system, PS microspheres and tumor cells were used in US capture tests. Their size was evaluated using a laser particle sizer (BeNano 90 Zeta, Dandong Bettersize Instruments Ltd., China).

Tumor tissue processing

Melanoma and breast cancer samples were obtained from patients diagnosed with malignant melanoma and HER2-positive breast cancer, respectively. All samples were collected with the consent of patients, and the experiments were approved by the Medical Ethics Committee of Xiangya Hospital, Central South University. Following excision, the melanoma tissues were placed into 50-ml centrifuge tubes, each containing 10 ml of collection medium. An enzyme mixture of 0.2% collagenase IV (Sigma-Aldrich) and 0.1% dispase II (Sigma-Aldrich) was found to be most effective for digesting melanoma tissues. The tissues were incubated for approximately 30 min at 37°C in this enzymatic solution. Subsequently, the cell suspensions were filtered through a 100-μm sterile cell strainer and then centrifuged at 1000 rpm for 10 min at room temperature. The breast cancer tissues were collected with collection medium and cut into small pieces of 1 mm³. Another enzyme mixture of 0.2% collagenase IV (Sigma-Aldrich) with 0.2% hyaluronidase (Sigma-Aldrich) was used to digest the breast cancer tissue for 90 min at 37°C. Subsequently, the cell suspensions were filtered through the same cell strainer and then centrifuged at room temperature.

Matrigel-based patient-derived tumor organoid culture

The resulting cell pellets were seeded into growth factor–reduced Matrigel, with each well receiving 100 μl containing no more than 1 × 10⁵ cells. The cultures were maintained in tumor organoid medium [Dulbecco’s modified Eagle’s medium (DMEM)/F-12; Gibco] enriched with N-2 (Gibco) and B-27 supplements (Gibco), 10% R-spondin– conditioned medium (PeproTech), epidermal growth factor (EGF; 50 ng/ml; R&D Systems), fibroblast growth factor–10 (FGF-10; 100 ng/ml; R&D Systems), N-acetylcysteine (1.25 mM; Sigma-Aldrich), Rho-kinase inhibitor Y-27632 (10 μM; Abmole), A83-01 (5 μM; Sigma-Aldrich), 1× GlutaMAX, 10 mM nicotinamide, and 1 mM N-acetylcysteine. Organoids were passaged using mechanical dissociation or TrypLE Express (Invitrogen), supplemented with 10 μM Y-27632 every 1 to 3 weeks. The medium was refreshed every 3 or 4 days based on the organoids’ growth dynamics. After passaging, cells were reseeded in BME and overlaid with tumor organoid medium following centrifugation with 5 to 10 ml of DMEM/F12 at 500g.

Microscopy

Imaging was conducted using an inverted Nikon ECLIPSE Ti fluorescence microscope system equipped with either a Plan Apochromat Lambda 10×/1.40 objective or a Plan Fluor 4×/0.13 objective. The system included a CSU-W1 confocal spinning disk unit, an iXon Ultra 888 camera (Andor Technology), and an MLC 400B laser unit (Agilent Technologies) and was operated using NIS-Elements software (Nikon). The volume values of organoids were calculated as follows: V = 0.5 × length × width².

Optimization of AV-Scaf parameters

Different voltages were applied to assess the mechanical stimuli necessary for ion channel activation. Notably, a voltage of 60 mV was insufficient to induce significant cell self-organization, while 140 mV led to excessively large cell clusters, hindering optimal growth. Furthermore, we assessed the cell viability across various voltages and exposure times, identifying a critical exposure threshold at 240 s, beyond which cell viability significantly decreased. Consequently, a driving voltage of 100 mV for a duration of 2 min was selected as an optimal trade-off for promoting adequate organoid growth without compromising cell viability.

AV-Scaf–based tumor PDO culture

For the study of AV-Scaf, tumor cells were obtained by digesting tumor organoids cultured using the Matrigel method. Using the optimized AV-Scaf settings, patient-derived melanoma and breast cancer samples were cultured to form scaffold-free tumor organoids. The organoid formation process was initiated by treating the tumor cells with AV-Scaf for 2 min, resulting in the assembly of cells into clusters. The morphology of these organoids was monitored over a 5-day culture period under the optimized conditions.

ELISA analysis and CCB study

After the samples were collected, the protein levels of ECM laminin, fibronectin, and collagen IV in the organoid were measured using laminin, fibronectin, and collagen IV ELISA kits according to the manufacturer’s instructions (human laminin, fibronectin, and collagen IV ELISA kits: ab219046, ab119599, and CSB-EL005742HU). In the experiments, the selective and potent inhibitor of calcium ion channel YM-58483 (5 nM; 223499-30-7, MedChemExpress) was added before US stimulation.

PBMC culture

PBMCs were isolated from peripheral blood using Lympholyte-H Cell Separation Media (Cedarlane) and subsequently cryopreserved. The PBMC culture medium consisted of RPMI 1640 (Corning) supplemented with 2 mM UltraGlutamine I, 1% penicillin-streptomycin solution, 25 mM Hepes (pH 7.2), 5.5 × 10⁻⁵ M β-mercaptoethanol, interleukin-2 (6000 IU/ml; Sigma-Aldrich and SL Pharm), and 10% inactivated serum (Gibco) (herein referred to as T cell expansion medium).

Coculture of lymphocytes and organoids

To assess the inhibitory effects of anti–PD-1 antibody on T cells, we used two organoid culture methods in coculture assays with CD45⁺ PBMCs. These PBMCs were isolated using CD45 MicroBeads. On the day of coculture, we prepared traditional organoids by disaggregating them into small cell clumps, which were then combined with expanded T cells from PBMCs and embedded in fresh Matrigel. For the AV-Scaf–based organoids, we collected the cell clumps using pipette tips and directly mixed them with the expanded T cells from PBMCs. The mixture of stimulated PBMCs with either dissociated or scaffold-free organoids was set up at effector-to-target ratios of 2:1 or 5:1. In the cytotoxic experimental setups, we introduced anti–PD-1 antibody at a concentration of 80 μg/ml. The coculture was maintained for approximately 48 hours to allow for sufficient interaction and observation of the antibody’s effects.

Flow cytometry

To assess tumor reactivity, lymphatic cells were washed with phosphate-buffered saline (PBS) and stained with anti-CD45–peridinin chlorophyll protein–cyanine5.5 (PerCP-Cy5.5), anti-CD3–Alexa Fluor 700, and anti-CD8–fluorescein isothiocyanate antibodies (BD Biosciences) for 60 min at 4°C. Cell membranes were subsequently permeabilized using the eBioscience intracellular fixation and permeabilization buffer set according to the manufacturer’s instructions. Intracellular antibodies, including anti–IFN-γ and anti-GZMB, were then applied for 60 min at 4°C. Intracellular calcium ion concentration in tumor cells was evaluated by washing the cells with PBS, adding 1 ml of Fluo-4 staining solution, and incubating for 30 min at 37°C. Mean fluorescence intensity at various time points after US stimulation was measured using the BD FACSymphony A3 cell analyzer system, with data analysis conducted via FlowJo v.10.6.0 software.

IF staining and microscopy

Organoids were analyzed using whole-mount staining without sectioning. For IF staining, organoids were fixed with 4% paraformaldehyde (PFA) for 1 hour, permeabilized with 0.3% Triton X-100 (Sigma-Aldrich) for 15 min, followed by three PBS washes, and blocked with 3% bovine serum albumin overnight at 4°C. Primary antibodies were incubated with the organoids overnight at 4°C, followed by the application of fluorescence-conjugated secondary antibodies for 1 hour at room temperature in the dark. Last, nuclei were stained with DAPI for 5 min. Images were captured using the Agilent BioTek Cytation C10 confocal microscope. To detect intracellular calcium ion concentration using fluorescence, single tumor cells were extracted from organoids via digestion and subsequently stained with Fluo-4 staining solution for 30 min at 37°C. Images were captured using a fluorescence microscope at various time points before or after the tumor cells were stimulated and cohered by US.

Histological analysis and IHC study

For H&E and IHC staining, AV-Scaf–based organoids were fixed overnight at room temperature in 4% PFA. The fixed samples were then processed using standard protocols, including dehydration, clearing, and embedding in paraffin, and sectioned into 35 μm. Then, the sections were used to conduct IHC and H&E staining.

Cell viability

Cell viability was quantified using the Cell Counting Kit-8 (Bimake, B34302). The live or dead staining cells were measured by ViaStain AOPI staining solution, which was dual-labeled acridine orange (AO; live cells, green) and propidium iodide (PI; dead cells, red). The images were captured using an inverted Nikon ECLIPSE Ti fluorescence microscope system. The live/dead ratios of the tumor cells were analyzed by a Countstar MiraBF/FL Plus automatic cell (fluorescence) analyzer.

RNA-seq analysis

In the RNA-seq experiment, samples consisted of tumor cells treated with the AV-Scaf method for 24 hours within the culture chambers and control tumor cells that were merely placed in the culture chambers for 24 hours without any treatment. Total RNA was isolated from tumor cells and quantified using the NanoDrop One Microvolume UV-Vis Spectrophotometer (Thermo Fisher Scientific). RNA integrity was assessed by agarose gel electrophoresis and the Agilent 2100 Bioanalyzer (Agilent Technologies). The samples exhibited a 260/280 ratio of approximately 2.0, and cDNA libraries were prepared and sequenced by Majorbio Biotech. Specifically, 200 ng of RNA from each group was used for library construction with the TruSeq RNA Sample Prep Kit (Illumina). The resulting DNA was amplified by polymerase chain reaction and subsequently purified through gel electrophoresis using Certified Low Range Ultra Agarose (Bio-Rad). Clone clusters were generated on the Illumina cBot using the TruSeq PE Cluster Kit v3-cBot-HS, and high-throughput sequencing was performed on an Illumina MiSeq sequencer using the TruSeq SBS Kit v3-HS (200 cycles). Aligned reads were analyzed using featureCounts (v2.0.0) based on the GENCODE vM19 annotation. Differential expression analysis was conducted using the R package (v.4.0.3) DESeq2 (v1.30.0) between samples maintained at 30° and 4°C. GSEA was performed using the GSEA Preranked tool of GSEA software (v4.1.0), where genes were preranked on the basis of their P values and fold change.

Statistical analysis

Data analysis was performed in GraphPad Prism 10.2.1 software. All measured values in graphs represented means ± SD. The statistical significance of the differences between groups was determined by an unpaired Student’s t test or one-way analysis of variance (ANOVA) test. Differences between groups were considered significant at P < 0.05 (*P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001).

Correction (23 December 2024): The original version of Fig. 5, G and H, was missing legends describing the colors of the bar graphs, and this error was only recently brought to the attention of the Editorial Office. Legends have been added to these panels. The XML and PDF versions of the article have been updated.

Supplementary Materials

This PDF file includes:

Supplementary Text

Figs. S1 to S7