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Glioblastoma (GBM) presents a significant therapeutic challenge due to the limited efficacy of existing treatments. Chimeric antigen receptor (CAR) T-cell therapy offers promise, but its potential in solid tumors like GBM is undermined by the physical barrier posed by the extracellular matrix (ECM). To address the inadequacies of traditional 2D cell culture, animal models, and Matrigel-based 3D culture in mimicking the mechanical characteristics of tumor tissues, we employed biomaterials and digital light processing-based 3D bioprinting to fabricate biomimetic tumor models with finely tunable ECM stiffness independent of ECM composition. Our results demonstrated that increased material stiffness markedly impeded CAR-T cell penetration and tumor cell cytotoxicity in GBM models. The 3D bioprinted models enabled us to examine the influence of ECM stiffness on CAR-T cell therapy effectiveness, providing a clinically pertinent evaluation tool for CAR-T cell development in stiff solid tumors. Furthermore, we developed an innovative heat-inducible CAR-T cell therapy, effectively overcoming the challenges posed by the stiff tumor microenvironment.
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Glioma, with its heterogeneous microenvironments and genetic subtypes, presents substantial challenges for treatment prediction and development. We integrated 3D bioprinting and multi-algorithm machine learning as a novel approach to enhance the assessment and understanding of glioma treatment responses and microenvironment characteristics. The bioprinted patient-derived glioma tissues successfully recapitulated molecular properties and drug responses of native tumors. We then developed GlioML, a machine learning workflow incorporating nine distinct algorithms and a weighted ensemble model that generated robust gene expression-based predictors, each reflecting the diverse action mechanisms of various compounds and drugs. The ensemble model superseded the performance of all individual algorithms across diverse in vitro systems, including sphere cultures, complex 3D bioprinted multicellular models, and 3D patient-derived tissues. By integrating bioprinting, the evaluative scope of the treatment expanded to T cell-related therapy and anti-angiogenesis targeted therapy. We identified promising compounds and drugs for glioma treatment and revealed distinct immunosuppressive or angiogenic myeloid-infiltrated tumor microenvironments. These insights pave the way for enhanced therapeutic development for glioma and potentially for other cancers, highlighting the broad application potential of this integrative and translational approach.
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Astronauts experience significant and rapid bone loss as a result of an extended stay in space, making the International Space Station (ISS) the perfect laboratory for studying osteoporosis due to the accelerated nature of bone loss on the ISS. This prompts the question, how does the lack of load due to zero-gravity propagate to bone-forming cells, human fetal osteoblasts (hFOBs), altering their maturation to mineralization? Here, we aim to study the mechanotransduction mechanisms by which bone loss occurs in microgravity. Two automated experiments, 4 microfluidic chips capable of measuring single-cell mechanics of hFOBs via aspiration and cell spheroids incubated in pressure-controlled chambers, were each integrated into a CubeLab deployed to the ISS National Laboratory. For the first experiment, we report protrusion measurements of aspirated cells after exposure to microgravity at the ISS and compare these results to ground control conducted inside the CubeLab. Our analysis revealed slightly elongated protrusions for space samples compared to ground samples indicating softening of hFOB cells in microgravity. In the second experiment, we encapsulated osteoblast spheroids in collagen gel and incubated the samples in pressure-controlled chambers. We found that microgravity significantly reduced filamentous actin levels in the hFOB spheroids. When subjected to pressure, the spheroids exhibited increased pSMAD1/5/9 expression, regardless of the microgravity condition. Moreover, microgravity reduced YAP expression, while pressure increased YAP levels, thus restoring YAP expression for spheroids in microgravity. Our study provides insights into the influence of microgravity on the mechanical properties of bone cells and the impact of compressive pressure on cell behavior and signaling in space.
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Astronauts experience significant and rapid bone loss as a result of an extended stay in space, making the International Space Station (ISS) the perfect laboratory for studying osteoporosis due to the accelerated nature of bone loss on the ISS. This prompts the question, how does the lack of load due to zero-gravity propagate to bone-forming cells, human fetal osteoblasts (hFOBs), altering their maturation to mineralization? Here, we aim to study the mechanotransduction mechanisms by which bone loss occurs in microgravity. Two automated experiments, microfluidic chips capable of measuring single-cell mechanics via aspiration and cell spheroids incubated in pressure-controlled chambers, were each integrated into a CubeLab deployed to the ISS National Laboratory. For the first experiment, we report protrusion measurements of aspirated cells after exposure to microgravity at the ISS and compare these results to ground control conducted inside the CubeLab. We found slightly elongated protrusions for space samples compared to ground samples indicating softening of hFOB cells in microgravity. In the second experiment, we encapsulated osteoblast spheroids in collagen gel and incubated the samples in pressure-controlled chambers. We found that microgravity significantly reduced filamentous actin levels in the hFOB spheroids. When subjected to pressure, the spheroids exhibited increased pSMAD1/5/9 expression, regardless of the microgravity condition. Moreover, microgravity reduced YAP expression, while pressure increased YAP levels, thus restoring YAP expression for spheroids in microgravity. Our study provides insights into the influence of microgravity on the mechanical properties of bone cells and the impact of compressive pressure on cell signaling in space.
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Chimeric Antigen Receptor T cell (CAR-T) therapy has emerged as a transformative therapeutic strategy for hematological malignancies. However, its efficacy in treating solid tumors remains limited. An in-depth and comprehensive understanding of CAR-T cell signaling pathways and the ability to track CAR-T cell biodistribution and activation in real-time within the tumor microenvironment will be instrumental in designing the next generation of CAR-T cells for solid tumor therapy. This review summarizes the signaling network and the cellular and molecular imaging tools and platforms that are utilized in CAR-T cell-based immune therapies, covering both in vitro and in vivo studies. Firstly, we provide an overview of the existing understanding of the activation and cytotoxic mechanisms of CAR-T cells, compared to the mechanism of T cell receptor (TCR) signaling pathways. We further describe the commonly employed tools for live cell imaging, coupled with recent research progress, with a focus on genetically encoded fluorescent proteins (FPs) and biosensors. We then discuss the utility of diverse in vivo imaging modalities, including fluorescence and bioluminescence imaging, Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), and photoacoustic (PA) imaging, for noninvasive monitoring of CAR-T cell dynamics within tumor tissues, thereby providing critical insights into therapy's strengths and weaknesses. Lastly, we discuss the current challenges and future directions of CAR-T cell therapy from the imaging perspective. We foresee that a comprehensive and integrative approach to CAR-T cell imaging will enable the development of more effective treatments for solid tumors in the future.
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Neoplasias , Receptores Quiméricos de Antígenos , Humanos , Distribución Tisular , Neoplasias/diagnóstico por imagen , Neoplasias/terapia , Inmunoterapia , Linfocitos T , Imagen Molecular , Microambiente TumoralRESUMEN
A primary challenge of high-throughput imaging flow cytometry (IFC) is to analyze the vast amount of imaging data, especially in applications where ground truth labels are unavailable or hard to obtain. We present an unsupervised deep embedding algorithm, the Deep Convolutional Autoencoder-based Clustering (DCAEC) model, to cluster label-free IFC images without any prior knowledge of input labels. The DCAEC model first encodes the input images into the latent representations and then clusters based on the latent representations. Using the DCAEC model, we achieve a balanced accuracy of 91.9% for human white blood cell (WBC) clustering and 97.9% for WBC/leukemia clustering using the 3D IFC images and 3D DCAEC model. Above all, although no human recognizable features can separate the clusters of cells with protein localization, we demonstrate the fused DCAEC model can achieve a cluster balanced accuracy of 85.3% from the label-free 2D transmission and 3D side scattering images. To reveal how the neural network recognizes features beyond human ability, we use the gradient-weighted class activation mapping method to discover the cluster-specific visual patterns automatically. Evaluation results show that the automatically identified salient image regions have strong cluster-specific visual patterns for different clusters, which we believe is a stride for the interpretable neural network for cell analysis with high-throughput IFCs.
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Algoritmos , Aprendizaje Automático no Supervisado , Humanos , Citometría de Flujo/métodos , Redes Neurales de la Computación , Análisis por ConglomeradosRESUMEN
Cell-based immunotherapy, for example, chimeric antigen receptor T (CAR-T) cell immunotherapy, has revolutionized cancer treatment, particularly for blood cancers. However, factors such as insufficient T cell tracking, tumour heterogeneity, inhibitory tumour microenvironment (TME) and T cell exhaustion limit the broad application of CAR-based immunotherapy for solid tumours. In particular, the TME is a complex and evolving entity, which is composed of cells of different types (e.g., cancer cells, immune cells and stromal cells), vasculature, soluble factors and extracellular matrix (ECM), with each component playing a critical role in CAR-T immunotherapy. Thus, developing approaches to mitigate the inhibitory TME factors is critical for future success in applying CAR-T cells for solid tumour treatment. Accordingly, understanding the bilateral interaction of CAR-T cells with the TME is in pressing need to pave the way for more efficient therapeutics. In the following review, we will discuss TME-associated aspects with an emphasis on T cell trafficking, ECM barriers, abnormal vasculature, solid tumour heterogenicity and immune suppressive microenvironment. We will then summarize current engineering strategies to overcome the challenges posed by the TME-associated factors. Lastly, the future directions for engineering efficient CAR-T cells for solid tumour therapy will be discussed.