Bridging the gap between tumor-on-chip and clinics: a systematic review of 15 years of studies.

Over the past 15 years, the field of oncology research has witnessed significant progress in the development of new cell culture models, such as tumor-on-chip (ToC) systems. In this comprehensive overview, we present a multidisciplinary perspective by bringing together physicists, biologists, clinicians, and experts from pharmaceutical companies to highlight the current state of ToC research, its unique features, and the challenges it faces. To offer readers a clear and quantitative understanding of the ToC field, we conducted an extensive systematic analysis of more than 300 publications related to ToC from 2005 to 2022. ToC offer key advantages over other in vitro models by enabling precise control over various parameters. These parameters include the properties of the extracellular matrix, mechanical forces exerted on cells, the physico-chemical environment, cell composition, and the architecture of the tumor microenvironment. Such fine control allows ToC to closely replicate the complex microenvironment and interactions within tumors, facilitating the study of cancer progression and therapeutic responses in a highly representative manner. Importantly, by incorporating patient-derived cells or tumor xenografts, ToC models have demonstrated promising results in terms of clinical validation. We also examined the potential of ToC for pharmaceutical industries in which ToC adoption is expected to occur gradually. Looking ahead, given the high failure rate of clinical trials and the increasing emphasis on the 3Rs principles (replacement, reduction, refinement of animal experimentation), ToC models hold immense potential for cancer research. In the next decade, data generated from ToC models could potentially be employed for discovering new therapeutic targets, contributing to regulatory purposes, refining preclinical drug testing and reducing reliance on animal models.

Protocol for in vitro assessment of human monocyte transendothelial migration using a high-throughput live cell imaging system.

In vitro modeling of the different steps of immune cell recruitment is essential to decipher the role of endothelial cells in this process. Here, we present a protocol for the assessment of human monocyte transendothelial migration using a live cell imaging system. We describe steps for culture of fluorescent monocytic THP-1 cells and chemotaxis plate preparation with HUVEC monolayers. We then detail real-time analysis using the IncuCyte® S3 live-cell imaging system, image analysis, and assessment of transendothelial migration rates. For complete details on the use and execution of this protocol, please refer to Ladaigue et al.1.

A role for endothelial alpha-mannosidase MAN1C1 in radiation-induced immune cell recruitment.

Radiation therapy damages tumors and normal tissues, probably in part through the recruitment of immune cells. Endothelial high-mannose N-glycans are, in particular, involved in monocyte-endothelium interactions. Trimmed by the class I α-mannosidases, these structures are quite rare in normal conditions. Here, we show that the expression of the endothelial α-mannosidase MAN1C1 protein decreases after irradiation. We modeled two crucial steps in monocyte recruitment by developing in vitro real-time imaging models. Inhibition of MAN1C1 expression by siRNA gene silencing increases the abundance of high-mannose N-glycans, improves the adhesion of monocytes on endothelial cells in flow conditions and, in contrast, decreases radiation-induced transendothelial migration of monocytes. Consistently, overexpression of MAN1C1 in endothelial cells using lentiviral vectors decreases the abundance of high-mannose N-glycans and monocyte adhesion and enhances transendothelial migration of monocytes. Hence, we propose a role for endothelial MAN1C1 in the recruitment of monocytes, particularly in the adhesion step to the endothelium.

Deep models of integrated multiscale molecular data decipher the endothelial cell response to ionizing radiation.

The vascular endothelium is a hot spot in the response to radiation therapy for both tumors and normal tissues. To improve patient outcomes, interpretable systemic hypotheses are needed to help radiobiologists and radiation oncologists propose endothelial targets that could protect normal tissues from the adverse effects of radiation therapy and/or enhance its antitumor potential. To this end, we captured the kinetics of multi-omics layers-i.e. miRNome, targeted transcriptome, proteome, and metabolome-in irradiated primary human endothelial cells cultured in vitro. We then designed a strategy of deep learning as in convolutional graph networks that facilitates unsupervised high-level feature extraction of important omics data to learn how ionizing radiation-induced endothelial dysfunction may evolve over time. Last, we present experimental data showing that some of the features identified using our approach are involved in the alteration of angiogenesis by ionizing radiation.