Resistance to cancer therapy arises from heterogeneous cellular responses within tumours grown in complex 3D environments but this cell-to-cell variability is rarely addressed in standard in vitro drug screens, which typically measure the average response of cell populations in highly artificial contexts, often confusing real biological variance with noise and failing to capture the behaviour of outliers that may drive drug resistance. While some progress has been made to study phenotypic heterogeneity by single cell-resolved assays of 2D cell cultures using current high content analysis (HCA) technologies, the failure to account for heterogeneous therapeutic responses in complex 3D tumour environments, including interactions with other cells such as fibroblasts and immune cells, contributes to the inefficiency of cancer drug discovery programmes and poor outcomes for many cancer patients.

Developing new cancer therapies requires improved understanding of heterogeneity in cell behaviour. Assays for new potential cancer therapies must therefore address single-cell responses, rather than the average responses of cell populations that fail to account for outlier cells that can be responsible for drug resistance. This will require single-cell-resolved imaging capabilities that can be employed at reasonable throughput. Since individual cancer cell behaviour will depend on the local tumour microenvironment (TME), it is also necessary to progress from assays of homogeneous monolayers of cells (typically using immortal cell lines) to more complex 3D cancer models, such as patient-derived organoids (PDO), that may better recapitulate the complexity of the in vivo context. However, increasing the physiological complexity of cancer models also increases their opacity and scale – limiting opportunities for high throughput (phenotypic) screening. Current high throughput assays involving these complex 3D models are typically limited to relatively simple endpoints since the HCA instrumentation and expertise to image diverse responses with single cell resolution in extended 3D cell cultures are not yet commercially available. Furthermore, the reproducibility of (heterogeneous) responses to drugs in 3D cancer models, and therefore the reliability of such assays, are not yet established.

This project aims to accelerate the development and deployment of 3D HCA capabilities to enable single-cell resolved assays of complex 3D cancer models to enhance cancer drug discovery.