3D multicellular systems in disease modelling: From organoids to organ-on-chip.

Cell-cell interactions underlay organ formation and function during homeostasis. Changes in communication between cells and their surrounding microenvironment are a feature of numerous human diseases, including metabolic disease and neurological disorders. In the past decade, cross-disciplinary research has been conducted to engineer novel synthetic multicellular organ systems in 3D, including organoids, assembloids, and organ-on-chip models. These model systems, composed of distinct cell types, satisfy the need for a better understanding of complex biological interactions and mechanisms underpinning diseases. In this review, we discuss the emerging field of building 3D multicellular systems and their application for modelling the cellular interactions at play in diseases. We report recent experimental and computational approaches for capturing cell-cell interactions as well as progress in bioengineering approaches for recapitulating these complexities ex vivo. Finally, we explore the value of developing such multicellular systems for modelling metabolic, intestinal, and neurological disorders as major examples of multisystemic diseases, we discuss the advantages and disadvantages of the different approaches and provide some recommendations for further advancing the field.

High-content image analysis to study phenotypic heterogeneity in endothelial cell monolayers.

Endothelial cells (ECs) are heterogeneous across and within tissues, reflecting distinct, specialised functions. EC heterogeneity has been proposed to underpin EC plasticity independently from vessel microenvironments. However, heterogeneity driven by contact-dependent or short-range cell-cell crosstalk cannot be evaluated with single cell transcriptomic approaches, as spatial and contextual information is lost. Nonetheless, quantification of EC heterogeneity and understanding of its molecular drivers is key to developing novel therapeutics for cancer, cardiovascular diseases and for revascularisation in regenerative medicine. Here, we developed an EC profiling tool (ECPT) to examine individual cells within intact monolayers. We used ECPT to characterise different phenotypes in arterial, venous and microvascular EC populations. In line with other studies, we measured heterogeneity in terms of cell cycle, proliferation, and junction organisation. ECPT uncovered a previously under-appreciated single-cell heterogeneity in NOTCH activation. We correlated cell proliferation with different NOTCH activation states at the single-cell and population levels. The positional and relational information extracted with our novel approach is key to elucidating the molecular mechanisms underpinning EC heterogeneity.

Therapeutic vulnerability to PARP1,2 inhibition in RB1-mutant osteosarcoma.

Loss-of-function mutations in the RB1 tumour suppressor are key drivers in cancer, including osteosarcoma. RB1 loss-of-function compromises genome-maintenance and hence could yield vulnerability to therapeutics targeting such processes. Here we demonstrate selective hypersensitivity to clinically-approved inhibitors of Poly-ADP-Polymerase1,2 inhibitors (PARPi) in RB1-defective cancer cells, including an extended panel of osteosarcoma-derived lines. PARPi treatment results in extensive cell death in RB1-defective backgrounds and prolongs survival of mice carrying human RB1-defective osteosarcoma grafts. PARPi sensitivity is not associated with canonical homologous recombination defect (HRd) signatures that predict PARPi sensitivity in cancers with BRCA1,2 loss, but is accompanied by rapid activation of DNA replication checkpoint signalling, and active DNA replication is a prerequisite for sensitivity. Importantly, sensitivity in backgrounds with natural or engineered RB1 loss surpasses that seen in BRCA-mutated backgrounds where PARPi have established clinical benefit. Our work provides evidence that PARPi sensitivity extends beyond cancers identifiable by HRd and advocates PARP1,2 inhibition as a personalised strategy for RB1-mutated osteosarcoma and other cancers.