3D Platform Research Articles

Engineered hsa-miR-455-3p-Abundant Extracellular Vesicles Derived from 3D-Cultured Adipose Mesenchymal Stem Cells for Tissue-Engineering Hyaline Cartilage Regeneration.

Efforts are made to enhance the inherent potential of extracellular vesicles (EVs) by utilizing 3D culture platforms and engineered strategies for functional cargo-loading. Three distinct types of adipose mesenchymal stem cells-derived EVs (ADSCs-EVs) are successfully isolated utilizing 3D culture platforms consisting of porous gelatin methacryloyl (PG), PG combined with sericin methacryloyl (PG/SerMA), or PG combined with chondroitin sulfate methacryloyl (PG/ChSMA). These correspond to PG-EVs, PG/SerMA-EVs, and PG/ChSMA-EVs, respectively. Unique microRNA (miRNA) profiles are observed in each type of ADSCs-EVs. Notably, PG-EVs encapsulate higher levels of hsa-miR-455-3p and deliver more hsa-miR-455-3p to chondrocytes, which results in the activation of the hsa-miR-455-3p/PAK2/Smad2/3 axis and the subsequent hyaline cartilage regeneration. Furthermore, the functionality of PG-EVs is optimized through engineered strategies, including agomir/lentivirus transfection, electroporation, and Exo-Fect transfection. These strategies, referred to as Agomir-EVs, Lentivirus-EVs, Electroporation-EVs, and Exo-Fect-EVs, respectively, are ranked based on their efficacy in encapsulating hsa-miR-455-3p, delivering hsa-miR-455-3p to chondrocytes, and promoting cartilage formation via the hsa-miR-455-3p/PAK2/Smad2/3 axis. Notably, Exo-Fect-EVs exhibit the highest efficiency. Collectively, the 3D culture conditions and engineered strategies have an impact on the miRNA profiles and cartilage regeneration capabilities of ADSCs-EVs. The findings provide valuable insights into the mechanisms underlying the promotion of cartilage regeneration by ADSCs-EVs.

Conceptual Design of a 3D Visualization Platform for Ships Based on Digital Twin Technology

Addressing the challenges in the current ship’s lifecycle design process, such as high difficulty in information sharing and complex installation of design environments, this study proposes a concept design of a ship 3D visualization platform based on digital twin technology. It constructs a web-based ship 3D visualization platform with an interactive interface of realism. The aim is to avoid cumbersome client-side programs and provide a method to showcase and interact with ship 3D models on web pages. This method not only reduces the threshold for ordinary users but also significantly enhances the work efficiency of professional designers. Following the model construction theory of digital twin platforms, it utilizes WebGL technology and the Three.js library to build ship 3D scenes, achieving ship 3D visualization. Functional interaction among modules is implemented using JavaScript, establishing the digital twin of the ship. Test results indicate that the proposed concept design of the ship 3D visualization platform can preliminarily fulfill the basic requirements of achieving ship 3D display, rendering, and interaction on web platforms. The proposed method can support the development of ship online collaborative design systems based on front-end internet technologies.

Augmented reality: a new perspective in dental education

INTRODUCTION The Microsoft HoloLens is a mixed reality device with the capability to provide a real-time 3D platform using multiple sensors and holographic processing to display information, and even to simulate a virtual world. With rapidly evolving technology and virtual learning on the increase, the HoloLens can be used as a vital tool for education and surgical planning. The aim of this pilot study was to ascertain its benefit in dental education and in the surgical planning of complex oral surgery procedures. METHODS A cohort of postgraduate dentists working at the Eastman Dental Hospital in London were shown two holographic videos. Participation was voluntary and an email invitation was sent to all non-consultant grade dental staff across multiple dental specialties. The cases demonstrated were a mandibular third molar in close association with the inferior alveolar nerve and an impacted tooth. Each video had a narration and explanation by a consultant oral surgeon. After having watched the videos, participants were asked to rate seven statements using a Likert scale. RESULTS Eighty-two per cent of participants reported improved comprehension of orientating anatomical structures. All participants (100%) noted improved confidence in surgical planning. Ninety-four per cent believed that the technology was an invaluable surgical tool in postgraduate training. CONCLUSIONS Augmented reality has the potential to change the face of surgery in the 21st century. This technology can be used to improve surgical training, especially in an environment where hands-on training is limited and virtual learning is promoted.

Hydrogel-fiber-mesh-based 3D cell cultures: A new method for studying pituitary tumors

Acromegaly is a challenging medical condition that arises from the excessive production of growth hormones and the insulin-like growth factor 1 in the pituitary gland. While surgery is the primary treatment for acromegaly, medication is increasingly being used in patients who are unsuitable for surgery or have experienced treatment failure. Despite advancements in medical and surgical therapies, the treatment of acromegaly remains challenging. In this research, a three-dimensional (3D) in-vitro cell culture model for pituitary adenoma research was developed using hydrogel fiber meshes (HFMs) and GH3 cells. Electrospun nanofibers based on polyvinyl alcohol and polyacrylic acid were converted into HFMs by hydrogelification with the leaching of electrosprayed cellulose acetate beads for porosity enhancement. GH3 cells grown in the 3D model exhibited increased dispersion and upregulation of the somatostatin receptor subtypes 2 and 5 compared to those grown in traditional 2D cultures, as well as high sensitivity to somatostatin analogs and tumor-like profiles (as indicated by functional assays and transcriptome analysis, respectively). Therefore, the proposed 3D model accurately represents the physiological response to pituitary-adenoma therapeutic agents. This study highlights the potential of HFMs as a versatile platform for 3D in-vitro cell culture models that can be employed for pituitary adenoma research. Moreover, the proposed 3D cell culture model may contribute to a deeper understanding of tumor biology and facilitate the development of effective therapeutic strategies for acromegaly.

Development of a 3D Vascular Network Visualization Platform for One-Dimensional Hemodynamic Simulation.

Recent advancements in computational performance and medical simulation technology have made significant strides, particularly in predictive diagnosis. This study focuses on the blood flow simulation reduced-order models, which provide swift and cost-effective solutions for complex vascular systems, positioning them as practical alternatives to 3D simulations in resource-limited medical settings. The paper introduces a visualization platform for patient-specific and image-based 1D-0D simulations. This platform covers the entire workflow, from modeling to dynamic 3D visualization of simulation results. Two case studies on, respectively, carotid stenosis and arterial remodeling demonstrate its utility in blood flow simulation applications.

Abstract 512: Cell-cycle inhibition may influence differences in 2D vs 3D tumor sensitivity profiles

Abstract Background: Traditional cell culture methods involve growing cells on flat surfaces, which do not fully replicate the human physiological conditions. In contrast, 3D cell cultures accurately reproduce aspects of the in-vitro malignant and non-malignant cell behavior. However, differences in tumor sensitivity platforms between 2D vs. 3D models might be relevant for some, but not for other drugs. Methods: The colorectal cancer cell line HCT-116 was cultured and plated in flat bottom well plates for the 2D condition and in Ultra Low Attachment round-bottom plates for the 3D condition. After plating, cells were treated with chemotherapies and targeted therapies for four days; cellular sensitivity was assessed through a viability assay. Four-parameter logistic (4PL) dose response curves were generated and IC50s were quantified to understand the differences in responses between 2D and 3D cellular environments. Results: HCT-116 exhibited similar responses to platinum drugs, taxanes, and several other tested drugs in both platforms, with the exception of gemcitabine (2D IC50 0.04 mcM; 3D IC50 12.8 mcM), lapatinib (2D IC50 23; 3D IC50 418), tucatinib (2D IC50 23.3; 3D IC50 79.3), and palbociclib (2D IC50 7.0; 3D IC50 24.0). Interestingly, these drugs share a common mechanism of action, which is the inhibition of cell cycle progression from G1 to S phase. Hence, we hypothesize that this shared mechanism may account for the observed differences in drug efficacy between the two environments. Conclusions: Similar dose responses have been observed with various drugs on both platforms, yet drugs that inhibit cell cycle progression from G1 to S phase, revealed higher sensitivity in 2D and more resistance in the 3D platform. Confirmatory cell-cycle results analyses are in progress. Further research is needed to understand if this applies to patient samples. Citation Format: Jahanvi Kumar, Chiara Maestri, Rajeshwar Nitiyanandan, Ivan Trus, Ricardo J. Parker, Brigitte Apfel, Christian Apfel. Cell-cycle inhibition may influence differences in 2D vs 3D tumor sensitivity profiles [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 512.

Abstract 4258: An innovative PDX and patient-derived 3D platform for improved translatability of new medical entities

Abstract The preclinical platform landscape in oncology has radically changed in the last 15 years, mainly due to an increased ability to generate patient-derived models. Multiple 3D tumor cell cultures methods, either from established cell lines or from primary cultures, have been developed to assess the activity of therapeutic agents in vitro. These methods are strongly influenced by the experimental conditions, such as cell culture conditions, the presence of 3D supports like Matrigel, and the experimental design of the assay, such as the choice of the dose and the duration of the assay. The ability of these methods to predict drug efficacy in the patient relies not only in the optimization of the experimental settings, but also on the representativeness of the patient population, and on the prevention of model drifts due to clonal selection and/or tumor cell adaptation to culture conditions with passages. In this project, we aimed to develop an innovative 3D cell model platform that addresses all these experimental challenges. To do so, we took advantage of our low passage Tumorgraft platform, a bank of more than 1500 patient-derived xenografts (PDXs) well characterized at molecular and pharmacological level and highly representative of the patient population, to generate the Tumorgraft3D platform. We derived TumorGraft3D models from low passage PDXs, by using proprietary, indication-specific culture conditions. By keeping these models at low passage, we were able to avoid clonal drifts. Moreover, the use of indication specific media allowed the preservation of patient’s and PDX’s tumor histology, molecular traits at genetic, gene expression and proteomic level, and displayed proliferation rates that recapitulate those observed in the parental PDXs. So far, we have successfully developed over 100 models from breast, ovarian, prostate, NSCLC, colorectal and gastric indications, with success rates up to 90%. Ex-vivo testing of standard of care highlighted different response profiles in accordance with the molecular feature of these models. The tumor dissociation process and culture conditions optimized with PDXs were also used for the development of 3D cultures derived from patients’ samples. These data demonstrated that our 3D platform can integrate the complementarity of our PDX and patient-derived 3D platform, which lies in the possibility of evaluating test agent activity in the repeatable and reproducible setting provided by the patient-derived 3D models, as well as in models directly derived from patients with more heterogeneous and indication-specific establishment success rate, and throughput dependent on the amount of primary tumor material. Citation Format: Samaneh Kamali, Stefano Cairo, Fu-Ju Chou, Taylor Light, Mara Gilardi, Brandon Walling, Christine Baer, Hsiu-Wen Tsai, Abhay Andar, Karin Abarca-Heidemann, Maria Mancini. An innovative PDX and patient-derived 3D platform for improved translatability of new medical entities [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4258.

Abstract 6778: New microplate platform with cryopreserved 3D tumor spheroids for faster and convenient pre-clinical testing

Abstract Drug discovery and safety testing depend on predictive in vitro models, including multicellular tissues with organotypic functions. While traditional 2D tumor cell cultures have been extensively used in early drug screening due to their user-friendly nature, automation compatibility, and high throughput, they fall short in representing the intricate 3-dimensional structure, physiology, and complex multicellular nature of actual tumors. However, generating such 3D tissues for each test campaign is labor intensive. In addition, not all researchers have the resources to establish these 3D models. To pave the way, we developed a new platform that offers a range of cryopreserved 3D tumor models in micro plate format allowing for high-content screening. It enables users to start testing compounds within a 3-to-5 days simply by thawing an ARCTis™ plate (Always Ready Cryo Tissues) and following clear instructions. Another advantage of these cryopreserved 3D models derives from the fact that they are made in larger batches which means the start point for compound testing is always the same. This improves data quality, maximizes the test window length, and makes the data comparable across work groups. Currently, our growing portfolio consists of 25 tumor cell lines from ATCC representing the most common solid tumors. Their functionality has been determined based on efficacy tests for each cell line with the apoptotic agent Staurosporine. Various cell lines exhibited compact spheroids with a round morphology, less compact aggregates with non-spherical morphology, or loose cell-cell interaction aggregates, which can correlate with their tumor site of origin. Upon treatment with Staurosporine the dose-response profiles indicated growth inhibition, tumor shrinkage, or tumor cell killing effects based on size assessment and cell metabolic analysis (ATP). Moreover, we demonstrated the robust performance of these assays from plates stored for up to 6 months at -80°C.In conclusion, this groundbreaking approach addresses the limitations of traditional 2D cell cultures by providing a high-throughput, in-plate frozen, 3D cell culture platform. By offering a combination of a more physiologically relevant representation of tumors with a robust frozen-storage and time flexible assay platform our method holds great promise for advancing cancer drug discovery by easing the exploration of complex drug testing screens in vitro. Citation Format: Nils Goedecke, Simon Stroebel, Simon Hutter, Tala Issa, Irina Agarkova, Laure-Anne Ligeon, Olivier Frey. New microplate platform with cryopreserved 3D tumor spheroids for faster and convenient pre-clinical testing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6778.

Abstract 224: Combining functional precision medicine and radiotherapy with bio-printed organoids in head and neck squamous cell carcinoma

Abstract The study aims to establish a high throughput ex vivo organoid-based drug screening platform for head and neck squamous cell carcinoma (HNSCC) to investigate interactions between radiotherapy and different chemotherapies or targeted therapy agents and ultimately provide functional precision medicine therapeutic suggestions. HNSCC is the sixth most common cancer worldwide. Both HPV+ and HPV- cancers can be treated with surgery, radiotherapy, chemotherapy, or a combination of these. Cetuximab is currently the only FDA-approved targeted agent for HNSCC. Few clinical trials to date have shown an improved clinical outcome when combining targeted agents with radiotherapy, thus there is a need to identify new therapeutic combinations to improve outcomes. In order to characterize HNSCC tumor behavior and sensitivity to therapy, we have leveraged our high throughput 3D tumor organoid screening platform. Our approach entails seeding tumor cells in extracellular matrix around the perimeter of tissue culture wells in ring-like structures, which we have successfully deployed in other cancer types (Phan et al, 2019; Al Shihabi et al, 2022; Nguyen et al, 2022; Al Shihabi et al 2023). To optimize a chemoradiation platform, we used the HN30, HN31, and SCC154 cell lines representing HPV- primary, HPV- metastatic, and HPV+ head and neck tumors. The cell-line-derived 3D models are exposed to both radiotherapy and various chemotherapy or targeted therapy drugs. We measured cell responses by ATP-release assays and by applying our machine learning-based brightfield image analysis pipeline (Al Shihabi et al, 2022). Our results showed that the HPV+ SCC154 was the most sensitive line to radiotherapy while HPV- metastatic HN31 was the most resistant. HN31 was resistant to most drug treatments except for gemcitabine, docetaxel, and mitomycin c, while HN30 and SCC154 were sensitive to a broader set of agents. We have investigated combinatorial efficacy of radiation and chemotherapy as well as targeted agents and extended this platform to HNSCC patient-derived tumor organoids. Our proof-of-concept study highlights how our organoid-based drug screening platform can be used to test chemoradiation approaches that are more effective and personalized. Citation Format: Luda Lin, Krishna K. Bommakanti, Andreanne V. Sannajust, Yazeed Alhiyari, Brandon Mo, Lauran Evans, Peyton Tebon, Maie St. John, Alice Soragni. Combining functional precision medicine and radiotherapy with bio-printed organoids in head and neck squamous cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 224.

Abstract 4703: Automated 42 PDX 3D in vitro tumor models of the TME screen immuno-oncology and targeted compounds and biologics for antitumor effects and MOA

Abstract High throughput screening has been widely utilized for its efficiency in testing novel therapeutic agents. However, the conventional screening using 2D culture of cancer cell lines lacks the biological complexity of the tumor microenvironment or the immune compartment which limits their application in testing immune-oncology therapies. Particularly with the passing of the FDA Modernization Act 2.0, it is critical to create more biologically relevant 3D in vitro models that can be used to reduce, refine and ultimately replace preclinical animal models. Here we have developed a highly automated 3D high throughput screening platform comprised of 42 patient-derived xenograft models in coculture with fibroblasts in engineered extracellular matrix hydrogels that resemble tumor stromal microenvironment. The PDX models cover a diverse range of tumor and histological types including NSCLC, CRC, gastric, TNBC, RCC, bladder, ovarian, melanoma, pancreatic, and others. Moreover, PBMCs or other immune cells can be incorporated into the system for evaluating immuno-oncology drugs. The panel has been tested against chemotherapy drug cisplatin and the immunotherapy biologic, Solitomab, an EpCAM/CD3 bispecific antibody. The endpoint analyses for antitumor effects include the dose response of tumor size and tumor cell death percentage based on high content imaging analysis. In addition, immune cells and supernatant in the IO assay can be recovered from the wells and used for flow cytometry profiling and cytokine assays. In summary, the novel 42-PDX panel described here offers a unique and powerful tool for rapidly generating preclinical data and a better understanding the drug activity at the pharmacology stages, opening the door for faster and more human relevant drug discovery for cancer patients. Citation Format: Bin Xue, Christopher Harrod, Long Le, Julia Schüler, Kolin C. Hribar. Automated 42 PDX 3D in vitro tumor models of the TME screen immuno-oncology and targeted compounds and biologics for antitumor effects and MOA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4703.

Abstract 4200: A novel 3D culture platform, E-slice, retains intact tumor microenvironment and tumor infiltrating immune cells

Abstract Human cancer tissue is a complex ecosystem with heterogeneous cell types that communicate with each other dynamically to promote tumor progression and immune evasion. Hence, experimental systems that destroy or select for cancer cells in culture have often failed to accurately predict clinical responses of new drugs. Therefore, a technology that can retain the intact tumor microenvironment (TME) and accurately predict cancer patient’s response to anti-cancer treatments, including immunotherapies, will greatly benefit patients and dramatically reduce the cost of new drug development. E-slice is a proprietary 3D human tumor culture platform that maintains individual patient tumor’s unique ecosystem and the TME ex vivo for up to 30 days. It is generated by making thin sections of intact, fresh tumor tissues and culturing them in serum-free, defined media. As such, immune components and the TME in E-slices faithfully recapitulate human tumors ex vivo. We demonstrate that E-slices can be used to: 1) measure viability changes upon anti-cancer agent treatment longitudinally; 2) retain the native TME and tissue architecture since E-slices are never dissociated or artificially reconstituted; 3) culture any solid tumor types from patient needle biopsy cores or surgical samples, PDX, or mouse models; 4) perform high content drug screening on human tissues; 5) discover secreted biomarkers and to 6) discover or validate molecular mechanisms of action or therapy resistance; and 7) measure immunotherapy responses ex vivo from human tissues. Importantly, it has been shown to accurately predict individual patient treatment responses to chemotherapies and targeted therapies in 4-8 days, paving the way for evidence-based personalized treatment selections in a clinically actionable time frame. Furthermore, single cell RNA-sequencing analysis demonstrates that E-slices can retain the viability and molecular phenotypes of tumor infiltrating immune cells for up to 8 days ex vivo, providing a unique platform to study human tumor-immune interactions and evaluate efficacy of immune modulators on human tumor tissues ex vivo. Citation Format: Viridiana Leyva-Aranda, Thomas Gallup, Jose Maldonado, Corina Margain, Sang Yun, David Gallup, Min Kim, Kyuson Yun. A novel 3D culture platform, E-slice, retains intact tumor microenvironment and tumor infiltrating immune cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4200.

Abstract 4268: Engineered hydrogel elucidates contributions of matrix mechanics to pathobiology of adenocarcinoma and identify matrix-activated therapeutic targets

Abstract Dysregulation of the extracellular matrix (ECM) properties disturbs tissue homeostasis and contributes to pathological conditions, such as cancer. Recent studies have demonstrated that ECM stiffening is associated with metaplasia-dysplasia-adenocarcinoma sequence in the esophagus. This underscores a compelling need to develop a physiologically-relevant 3D culture model to enable the study of the independent contribution of matrix stiffness to the initiation and progression of esophageal adenocarcinoma (EAC). Such a model will then serve as a platform for pre-clinical drug screening in the context of matrix properties. In this context, we have engineered a hyaluronic acid-based 3D hydrogel platform that supports the growth and differentiation of patient-derived Barrett’s esophagus (BE) organoids, a precursor to EAC, as well as patient-derived EAC organoids. The engineered biomaterial 3D platform allows control over matrix stiffness to better recapitulate the mechanically dynamic esophageal cancer microenvironment and help identify therapeutic targets in EAC.Our data demonstrates that BE and EAC organoid density, growth and proliferation can be controlled by matrix stiffness. RNA sequencing data show that increased matrix stiffness promotes changes in the transcriptional profiles of BE and EAC organoids, revealing enrichment of pathways associated with tumorigenesis and disease progression. Furthermore, we demonstrate through molecular and functional assays that increased matrix stiffness endows stem-like properties to the EAC organoids via Yap-Sox9 mechano-activation. Finally, targeted therapy studies in our in vitro and in vivo engineered environments revealed that Yap inhibition regressed the effects of increased matrix stiffness in EAC organoids. In summary, our data suggest that matrix mechanics have a significant role in activation of EAC-associated signaling pathways in patient-derived BE and EAC organoids. We also demonstrate that the engineered hydrogel serves as a platform to identify potential therapeutic targets to disrupt the contribution of pro-tumorigenic matrix mechanics in EAC. Together, these studies establish an engineered patient-derived organoid culture platform that can be used to elucidate underlying matrix-mediated mechanisms of the metaplasia-dysplasia-adenocarcinoma sequence and inform the development of novel therapeutics that target ECM stiffness in EAC. FUNDING SOURCES: NCI P01CA098101, U54 CA163004 and NIDDK K01 DK133620. Citation Format: Ricardo Cruz-Acuna, Secunda W. Kariuki, Kensuke Sugiura, Spyros Karaiskos, Eleanor M. Plaster, Claudia Loebel, Gizem Efe, Tatiana Karakasheva, Joel T. Gabre, Jianhua Hu, Jason A. Burdick, Anil K. Rustgi. Engineered hydrogel elucidates contributions of matrix mechanics to pathobiology of adenocarcinoma and identify matrix-activated therapeutic targets [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4268.

Abstract 651: 3D-bioprinted cancer models for target discovery, drug development, and personalized therapy

Abstract Many drugs show promising results in laboratory research, but eventually fail in clinical trials. We hypothesize that one main reason for this translational gap is that the cancer models used are inadequate. Most models lack the complex tumor-stromal cell interactions with their microenvironment which are required for tumor progression. Conventional 2D cultures, where cells grow on rigid plastic plates mainly as mono-cultures of a single type of cells, are not able to recapitulate the complex settings of such interactions. Therefore, there is a need to develop a 3D model that better mimics the tumor microenvironment. Hence, we developed a vascularized, hydrogel-based 3D-bioprinted tumor model consisting of patient-derived tumor and microenvironmental cells. Our 3D-bioprinted models are based on a library of hydrogels that we developed as scaffolds for different tumor types, designed according to the mechanical properties of the tissue/organ of origin. The patient-derived models consist of cells from a biopsy, constructed based on CT/MRI scans, and include functional vessels that allow serum and peripheral blood mononuclear cells (PBMC) to flow when connected to a pump. Using this unique model platform, we identified P-selectin as a novel immune checkpoint in the brain regulating cancer-microglia-tumor-associated macrophages (TAMs) interactions. Moreover, we are currently validating our 3D platform for its ability to mimic patient-specific tumors and their microenvironment in order to predict patient response to different treatments (such as chemotherapy, immunotherapy, and targeted therapies). Hence, we are currently conducting an 80-patient “basket” clinical trial testing different treatments on patient samples to validate the ability of our model to predict patient outcomes covering 7 different cancer types. These unique 3D-bioprinted models have the potential to facilitate target discovery and drug development, as well as to serve as a reliable system for precision medicine. Citation Format: Ronit Satchi-Fainaro, Anne Krinsky, Anshika Katyal, Opal Avramoff, Eilam Yeini, Lena Neufeld, Sharon Halparin, Ronnie Frommer-Shapira. 3D-bioprinted cancer models for target discovery, drug development, and personalized therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 651.

Risk prediction and function evaluation by T-cell epitope model and expression model of HLA-DPB1 mismatching in unrelated-donor hematopoietic stem cell transplantations

Objective: To evaluate the risk prediction and assessment function of HLA-DPB1 T-cell epitope (TCE) model and expression model in human leukocyte antigen (HLA)-matched unrelated hematopoietic stem cell transplantation (MUD-HSCT) with HLA-DPB1 mismatching. Methods: A total of 364 (182 pairs) potential MUD-HSCT donors and recipients confirmed by HLA high-resolution typing in Shaanxi Blood Center from 2016 to 2019 were analyzed retrospectively. Of the 182 recipients, there were 121 males and 61 females with an average age of (26.3±14.2) years. Of the 182 donors, there were 148 males and 34 females with an average age of (33.7±7.5) years. Polymerase chain reaction-sequence-based typing (PCR-SBT), next-generation sequencing (NGS) and polymerase chain reaction-sequence specific oligonucleotide probe (PCR-SSO) based on LABScan®3D platform were used for high-resolution typing of HLA-A, B, C, DRB1, DQB1, DPB1 gene, and PCR-SBT was used for single nucleotide polymorphism (SNP) typing. TCE model and expression model were used to predict and evaluate the HLA-DPB1 mismatch pattern and acute graft-versus-host-disease (aGVHD) risk. Results: A total of 26 HLA-DPB1 alleles and their 3'-UTR rs9277534 SNP genotypes were detected in this study population, and two new alleles HLA-DPB1*1052∶01 and HLA-DPB1*1119∶01 were found and officially named. The overall mismatch rate of HLA-DPB1 in MUD-HSCT donors and recipients was 90.66% (165/182). In TCE model, the HLA-DPB1 mismatch rates of permissible mismatch (PM) and non-permissible mismatch (non-PM) were 47.80% (87/182) and 42.86% (78/182), respectively. The non-PM in GvH direction was 13.73% (25/182), and which in HvG direction was 29.12% (53/182). A total of 73 pairs of donors and recipients in TCE model met the evaluation criteria of expression model. Among of TCE PM group, recipient DP5 mismatches accounted for 34.25% (25/73) were predicted as aGVHD high risk according to expression model. For the TCE non-PM group, both the recipient DP2 mismatches of 6.85% (5/73) and recipient DP5 mismatches of 10.86% (8/73) were predicted to be at high risk for aGVHD. Risk prediction by TCE model and expression model was 27.27% concordant and 16.97% unconcordant. Conclusions: TCE model and expression model are effective tools to predict aGVHD risk of MUD-HSCT. Comprehensive application of the two models is helpful to the hierarchical assessment of HSCT risk.

BEHAV3D: a 3D live imaging platform for comprehensive analysis of engineered T cell behavior and tumor response.

Modeling immuno-oncology by using patient-derived material and immune cell co-cultures can advance our understanding of immune cell tumor targeting in a patient-specific manner, offering leads to improve cellular immunotherapy. However, fully exploiting these living cultures requires analysis of the dynamic cellular features modeled, for which protocols are currently limited. Here, we describe the application of BEHAV3D, a platform that implements multi-color live 3D imaging and computational tools for: (i) analyzing tumor death dynamics at both single-organoid or cell and population levels, (ii) classifying T cell behavior and (iii) producing data-informed 3D images and videos for visual inspection and further insight into obtained results. Together, this enables a refined assessment of how solid and liquid tumors respond to cellular immunotherapy, critically capturing both inter- and intratumoral heterogeneity in treatment response. In addition, BEHAV3D uncovers T cell behavior involved in tumor targeting, offering insight into their mode of action. Our pipeline thereby has strong implications for comparing, prioritizing and improving immunotherapy products by highlighting the behavioral differences between individual tumor donors, distinct T cell therapy concepts or subpopulations. The protocol describes critical wet lab steps, including co-culture preparations and fast 3D imaging with live cell dyes, a segmentation-based image processing tool to track individual organoids, tumor and immune cells and an analytical pipeline for behavioral profiling. This 1-week protocol, accessible to users with basic cell culture, imaging and programming expertise, can easily be adapted to any type of co-culture to visualize and exploit cell behavior, having far-reaching implications for the immuno-oncology field and beyond.

Enantioanalysis of Cysteine Using an Enantioselective Stochastic Platform: A Key Factor on Early Diagnosis of Breast Cancer

Proteomics and metabolomics have identified novel biomarkers, such as enantiomers of amino acids, that can be used for the early detection of cancer. This paper proposed a 3D enantioselective stochastic platform that contains a mixture of powder (diamond powder and TiO2) modified with calix [6] arene and has been used for the enantioanalysis of L- and D-Cysteine in biological samples. The results demonstrated an extended linear concentration range (up to 10−18mol l−1) and sensitivities of 1.00 × 107 s mol l−1 magnitude order. The recoveries of the enantiomers in biological samples were higher than 98.00%.

Dual-Sensitive Fluorescent Nanoprobes for Simultaneously Monitoring In Situ Changes in pH and Matrix Metalloproteinase Expression in Stiffness-Tunable Three-Dimensional In Vitro Scaffolds.

A tumor microenvironment often presents altered physicochemical characteristics of the extracellular matrix (ECM) including changes in matrix composition, stiffness, protein expression, pH, temperature, or the presence of certain stromal and immune cells. Of these, overexpression of matrix metalloproteinases (MMPs) and extracellular acidosis are the two major hallmarks of cancer that can be exploited for tumor detection. The change in matrix stiffness and the release of certain cytokines (TNF-α) in the tumor microenvironment play major roles in inducing MMP-9 expression in cancerous cells. This study highlights the role of mechanical cues in upregulating MMP-9 expression in cancerous cells using stiffness-tunable matrix compositions and dual-sensitive fluorescent nanoprobes. Ionically cross-linked 3D alginate/gelatin (AG) scaffolds with three stiffnesses were chosen to reflect the ECM stiffnesses corresponding to healthy and pathological tissues. Moreover, a dual-sensitive nanoprobe, an MMP-sensitive peptide conjugated to carbon nanoparticles with intrinsic pH fluorescence properties, was utilized for in situ monitoring of the two cancer hallmarks in the 3D scaffolds. This platform was further utilized for designing a 3D core-shell platform for spatially mapping tumor margins and for visualizing TNF-α-induced MMP-9 expression in cancerous cells.

Laser-directed energy deposition to achieve high-aspect-ratio micropillar arrays for 3D interdigitated microsupercapacitors

Microsupercapacitors (MSCs) are promising micropower sources. High-performance active electrode materials have been extensively developed for them because MSC capacitances are critically determined by the electrochemical features of active materials. However, the limited two-dimensional spaces of conventional MSCs pose a substantial challenge in rational electrode design for fully exploiting the active material performances. Therefore, the development of three-dimensional (3D) MSCs has garnered considerable research interest. Herein, 3D interdigitated metal current collectors for 3D MSCs are successfully microfabricated using laser-directed energy deposition (LDED) of Inconel 625 powder. High-aspect-ratio (∼14) micropillars (diameter, 110 µm) are printed on a stainless-steel substrate, thus significantly increasing the surface area for active material deposition. Finally, reduced graphene oxide and polyaniline are electrodeposited as active materials on this 3D platform to boost MSC capacitance. The resulting 3D MSC exhibits substantially high electrochemical performance, with an energy and power densities of 18.76 μWh/cm2 and 0.395 mW/cm2, respectively, and high areal capacitances of 120.7–216.2 mF/cm2 at 1 mA/cm2 depending on the thickness of polyaniline. These inspiring results not only suggest a new route for using high-throughput LDED for high-performance MSCs but also suggest a new 3D fabrication strategy for next-generation micropower sources.

Fully automated structured light scanning for high-fidelity 3D reconstruction via graph optimization.

Convenient and high-fidelity 3D model reconstruction is crucial for industries like manufacturing, medicine and archaeology. Current scanning approaches struggle with high manual costs and the accumulation of errors in large-scale modeling. This paper is dedicated to achieving industrial-grade seamless and high-fidelity 3D reconstruction with minimal manual intervention. The innovative method proposed transforms the multi-frame registration into a graph optimization problem, addressing the issue of error accumulation encountered in frame-by-frame registration. Initially, a global consistency cost is established based on point cloud cross-multipath registration, followed by using the geometric and color differences of corresponding points as dynamic nonlinear weights. Finally, the iteratively reweighted least squares (IRLS) method is adopted to perform the bundle adjustment (BA) optimization of all poses. Significantly enhances registration accuracy and robustness under the premise of maintaining near real-time efficiency. Additionally, for generating watertight, seamless surface models, a local-to-global transitioning strategy for multiframe fusion is introduced. This method facilitates efficient correction of normal vector consistency, addressing mesh discontinuities in surface reconstruction resulting from normal flips. To validate our algorithm, we designed a 3D reconstruction platform enabling spatial viewpoint transformations. We collected extensive real and simulated model data. These datasets were rigorously evaluated against advanced methods, roving the effectiveness of our approach. Our data and implementation is made available on GitHub for community development.

AIoT-enabled digital twin system for smart tunnel fire safety management

High traffic flow in a confined tunnel makes fire safety a critical issue. This paper proposed a digital twin framework for tunnel fire safety management in real-time, driven by dynamic sensor data and AIoT technologies. A deep learning model trained by the Transformer network and simulation dataset is used to predict real-time fire location and size. Then, the AI model is integrated into a 3D digital twin platform developed by the game engine Unity 3D. The performance of the proposed digital twin framework is demonstrated using numerical experiments and large-scale tunnel fire tests. Results show that the established AI model achieved promising accuracy in predicting fire location and power for both numerical and experimental data. The digital twin platform can also visualize the 3D fire scene that supports evacuation, firefighting, and emergency rescue. This research demonstrates the feasibility of using a 3D environment and digital twin in real-time fire safety management.