NCT04060537

Identification of Novel Biomarkers of Response to Systemic Treatments in Renal Cell Cancer

A Retrospective Translational Study to Identify Novel Biomarkers of Response to Systemic Treatments in Renal Cell Cancer

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 12 (estimated)
• Sponsor: CCTU- Cancer Theme · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

This research study aims to investigate changes inside kidney cancers (also known as Renal Cell Carcinoma or RCC), and in normal kidney surrounding the tumour, when patients are treated with systemic therapy. Samples, radiological images and data from a previous trial (NeoSUN) will be analysed and/or reanalysed, in accordance with the consent of NeoSUN participants.

Detailed description

This research study aims to investigate changes inside kidney cancers, and in normal kidney surrounding the tumour, when patients are treated with systemic therapy. Systemic treatment is widely used as routine treatment for patients who have kidney cancer that has spread to other organs. It is also used sometimes before surgery to try to shrink kidney cancers to make surgery easier and less risky. Recent research has shown that kidney cancers consist of many different cells in addition to the cancer cells (including immune, structural and blood vessel cells). However, doctors know very little about what changes systemic therapy causes to cells other than cancer cells. Researchers now think that these other cells may influence how the tumour cells behave during cancer treatment and how well the cancer responds to treatment. The NeoSUN clinical trial was run at Cambridge University Hospitals between 2006 and 2015.18 patients were treated with a TKI called sunitinib for 12 days before they had their kidney surgically removed. MRI and CT scans were performed before and after the treatment. Samples of tumour and normal kidney were also taken before and after treatment. All patients consented to use of their tissue and data for future research projects. The investigators would like to analyse the effects that sunitinib had on the tumour and other cells using techniques called immunohistochemistry, immunofluorescence, and CyTOF. These mark the different cells so they can easily be identified and the effects on each one analysed. The investigators would also like to re-analyse the scans performed and use artificial intelligence (AI) to see try to detect new trends. The information may help to guide which drugs might be best used in future to treat kidney cancer more effectively whilst keeping side effects low.

Conditions

• Carcinoma, Renal Cell

Interventions

Type	Name	Description
OTHER	Laboratory analysis of samples	RNA sequencing, immunohistochemistry, immunofluorescence, and cytometry of tumour tissues
OTHER	Application of machine learning	Using machine learning to interrogate data generated from analysis of Renal Cell Cancer tumours using RNA sequencing, immunohistochemistry, immunofluorescence, cytometry, and MRI imaging of tumours.

Timeline

• Start date: 2020-01-01
• Primary completion: 2022-01-01
• Completion: 2022-01-01
• First posted: 2019-08-19
• Last updated: 2019-08-19