A Single Site Study Accessing the Acceptability and Feasibility of Patient-specific 'Tumouroids' as Personalised Treatment Screening Tools

In England, more than three hundred thousand people are diagnosed with cancer each year. The diagnostic and treatment pathways for multiple cancers have greatly developed over the past decade. However, novel treatments are expensive and currently discrimination between responders and non-responders is still suboptimal. There is a pressing need to develop tools that allow for better disease characterisation and stratification. Personalised medicine, whereby prevention, diagnosis, and treatment of diseases is aimed at the individual level, is a growing field. Predicting patient-specific treatment response is challenging as response depends not only on the characteristics of cancer cells but also on how these cells interact with their immediate surrounding environment and on how the tumour interacts with the host. A simplistic model is therefore insufficient to predict treatment response. Complex, patient-derived animal models have been used to this effect but are expensive, may take up to 6 months to provide clinically relevant answers, and pose ethical issues. In the past in vitro models lacked complexity as they were based solely on the two-dimensional (2D) growth of cancer cells. Nowadays the use of 3D tumour models has provided an extra level of complexity to in vitro studies. With these models it is possible to recreate tumour characteristics that were lost in 2D, such as cell-cell interaction between cancer cells and between cancer and stromal cells, cell-matrix interaction, or hypoxia.

The investigators have developed a 3D complex tumour model - named tumouroid. Using this model, preliminary work has been undertaken which allows the growth of patient-derived tumouroids using primary cancer cells from patients.

This personalised platform can be challenged by therapeutics used in clinical practice and response to treatment can be assessed via appropriate assays.

The study goals are twofold:

To assess patient acceptability to the use of patient derived tumour models for future decision-making, and To assess the feasibility of generating patient derived renal cancer tumouroids and using them as platforms to test drug response.