Huu Tuan Nguyen

Blood vessel embolization is a well-established treatment modality for liver cancer. Novel shear-thinning hydrogels (STH) have been developed to address the need for safer and more effective local delivery of embolic agents and therapeutics. However, embolization therapies are currently optimized in animal models, which often differ from humans at the cellular, tissue, and organ levels. We aim to evaluate the efficacy of novel embolic agents such as STH using a human-relevant in vitro model that recapitulates human hepatocellular carcinoma capillary networks. A vascularized human liver-tumor-on-a-chip model was developed to assess embolic agent performance. The effects of drug-eluting STH (DESTH) on tumor cell viability, surface marker expression, vasculature morphology, and cytokine responses were evaluated. To study the effects of embolization on microvasculature morphology independent of the chemotherapy compound, we evaluated the effect of different drug-free embolic agents on the vascular tumor microenvironment under flow conditions. DESTH treatment induced tumor cell death, downregulated the expression of epithelial cell adhesion molecules in HepG2, increased levels of cytokines such as interleukin-4 (IL-4), granulocyte-macrophage colony-stimulating factor, and vascular endothelial growth factor, and decreased albumin secretion. Furthermore, different embolic agents exert distinct effects on microvascular morphology, with STH causing complete regression of the microvascular networks. This vascularized liver tumor-on-a-chip model enables human-relevant, real-time assessment of embolic agent efficacy and vascular response and can be applied for the development of innovative and effective embolization therapies for liver cancer.

Background: Embolization is a well-established treatment modality for liver cancer. However, traditional embolization agents are limited by inefficient delivery and aggregation in blood vessels. Novel shear-thinning hydrogels (STH) have been developed to address the need for safer and more effective local delivery of embolic agents and therapeutics. Objective: We aim to evaluate the efficacy of novel embolic agents such as STH using a human-relevant in vitro model that recapitulates human hepatocellular carcinoma capillary networks. Methods: A vascularized human liver-tumor-on-a-chip model was developed to assess embolic agent performance. The effects of drug-eluting STH (DESTH) on tumor cell viability, surface marker expression, vasculature morphology, and cytokine responses were evaluated. To study the effects of embolization on microvasculature morphology independent of the chemotherapy compound, we assessed the effect of different drug-free embolic agents on the vascular tumor microenvironment under flow conditions. Results: DESTH treatment induced tumor cell death, downregulated the expression of Epithelial Cell Adhesion Molecules (EpCAM) in HepG2, increased levels of cytokines such as Interleukin-4 (IL-4), Granulocyte-macrophage colony-stimulating factor (GM-CSF), and Vascular Endothelial Growth Factor (VEGF), and decreased albumin secretion. Furthermore, different embolic agents exert distinct effects on microvascular morphology, with STH causing complete regression of the microvascular networks. Conclusion: This vascularized liver tumor-on-a-chip model enables human-relevant, real-time assessment of embolic agent efficacy and vascular response, paving the way for the development of innovative and effective embolization therapies for liver cancer.

Glioblastoma (GBM) is an aggressive form of cancer, comprising ≈80% of malignant brain tumors. However, there are no effective treatments for GBM due to its heterogeneity and the presence of the blood‐brain barrier (BBB), which restricts the delivery of therapeutics to the brain. Despite in vitro models contributing to the understanding of GBM, conventional 2D models oversimplify the complex tumor microenvironment. Organ‐on‐a‐chip (OoC) models have emerged as promising platforms that recapitulate human tissue physiology, enabling disease modeling, drug screening, and personalized medicine. There is a sudden increase in GBM‐on‐a‐chip models that can significantly advance the knowledge of GBM etiology and revolutionize drug development by reducing animal testing and enhancing translation to the clinic. In this review, an overview of GBM‐on‐a‐chip models and their applications is reported for drug screening and discussed current challenges and potential future directions for GBM‐on‐a‐chip models.

SignificanceAccurate cell segmentation and classification in three-dimensional (3D) images are vital for studying live cell behavior and drug responses in 3D tissue culture. Evaluating diverse cell populations in 3D cell culture over time necessitates non-toxic staining methods, as specific fluorescent tags may not be suitable, and immunofluorescence staining can be cytotoxic for prolonged live cell cultures.AimWe aim to perform machine learning-based cell classification within a live heterogeneous cell culture population grown in a 3D tissue culture relying only on reflectance, transmittance, and nuclei counterstained images obtained by confocal microscopy.ApproachIn this study, we employed a supervised convolutional neural network (CNN) to classify tumor cells and fibroblasts within 3D-grown spheroids. These cells are first segmented using the marker-controlled watershed image processing method. Training data included nuclei counterstaining, reflectance, and transmitted light images, with stained fibroblast and tumor cells as ground-truth labels.ResultsOur results demonstrate the successful marker-controlled watershed segmentation of 84% of spheroid cells into single cells. We achieved a median accuracy of 67% (95% confidence interval of the median is 65-71%) in identifying cell types. We also recapitulate the original 3D images using the CNN-classified cells to visualize the original 3D-stained image’s cell distribution.ConclusionThis study introduces a non-invasive toxicity-free approach to 3D cell culture evaluation, combining machine learning with confocal microscopy, opening avenues for advanced cell studies.

Tumor-associated inflammation drives cancer progression and therapy resistance, with the infiltration of monocyte-derived tumor-associated macrophages (TAMs) associated with poor prognosis in diverse cancers. Targeting TAMs holds potential against solid tumors, but effective immunotherapies require testing on immunocompetent human models prior to clinical trials. Here, we develop an in vitro model of microvascular networks that incorporates tumor spheroids or patient tissues. By perfusing the vasculature with human monocytes, we investigate monocyte trafficking into the tumor and evaluate immunotherapies targeting the human tumor microenvironment. Our findings demonstrate that macrophages in vascularized breast and lung tumor models can enhance monocyte recruitment via TAM-produced CCL7 and CCL2, mediated by CSF-1R. Additionally, we assess a novel multispecific antibody targeting CCR2, CSF-1R, and neutralizing TGF-β, referred to as CSF1R/CCR2/TGF-β Ab, on monocytes and macrophages using our 3D models. This antibody repolarizes TAMs towards an anti-tumoral M1-like phenotype, reduces monocyte chemoattractant protein secretion, and effectively blocks monocyte migration. Finally, we show that the CSF1R/CCR2/TGF-β Ab inhibits monocyte recruitment in patient-specific vascularized tumor models. Overall, this vascularized tumor model offers valuable insights into monocyte recruitment and enables functional testing of innovative therapeutic antibodies targeting TAMs in the tumor microenvironment (TME).