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NCT number NCT03300102
Study type Observational
Source University College, London
Contact Chris Brew-Graves
Phone 02076799280
Status Not yet recruiting
Phase N/A
Start date October 31, 2017
Completion date March 31, 2018

Clinical Trial Summary

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.

Clinical Trial Description

This trial is a prospective tissue collection of renal cell carcinoma samples, including collection of data using both structured Likert 12 item questionnaires and semi structured interviews to assess acceptability. With the development of patient-derived tumouroids the investigators would like to overcome the current over-simplified strategies that focus on genetic markers as predictors of response. In the future, the investigators hope to establish tumouroids as a personalised platform to predict patient response to treatment that is more cost-efficient and poses less ethical issues than animal platforms.

This project will assess if patient-derived tumouroids can be therapeutically challenged and if patients would be willing to accept that such platform to guide clinical treatment decision making.

This study is designed to assess primarily patient acceptability. Acceptability will be elicited using Likert scale non-validated questionnaires and in a semi-structured interview in which the views and preferences relating the acceptability or otherwise of the patient derived tumour models and their impact on future decision making will be explored.

The study will also assess feasibility of building tumouroids and challenging them. Feasibility will address the successful transition between the critical phases of generating a viable and responsive tumour model. This begins with the extraction of cancer cells from the explanted tumour and ends with the determination of a response or otherwise to a therapeutic challenge of the viable tumour model at a range of in vitro concentrations.

The findings of this study will be presented at conference(s) and manuscripts will be submitted to appropriate journals for publication.

Study Design

Related Conditions & MeSH terms

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