An observational study in Carcinoma, Renal Cell, sponsored by CCTU- Cancer Theme. Status unknown. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2019-08-19.
Sponsored by CCTU- Cancer Theme · Observational
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.
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.
1,964 studies on the registry are indexed under Carcinoma, Renal Cell; 377 are open to participants now.
This study's planned enrollment of 12 is below the median of 146 across 360 observational studies indexed under Carcinoma, Renal Cell.
Browse Carcinoma, Renal Cell studies →CCTU- Cancer Theme is the lead sponsor of 19 studies on the registry; 5 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Participants with renal cell cancer who have given prior consent under NeoSUN for their samples and data to be used, and who have adequate samples and data available.
Patients must have consent in place, for the use of tissue and imaging to be used for the purposes of clinical research;
Participants must also meet at least one of the following criteria to be eligible:
Exclusion Criteria:
None
Patients with Renal Cell Carcinoma who have had previous systemic treatment, with adequate tissue samples and radiological data
Other: Laboratory analysis of samples · Other: Application of machine learning
RNA sequencing, immunohistochemistry, immunofluorescence, and cytometry of tumour tissues
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.
Biological identification of biomarkers of response to systemic treatment in Renal Cell Cancer.
Using data from RNA sequencing of tumour tissues, the outcome is to identify novel biomarkers of response.
Time frame: 2 years
Radiological identification of biomarkers of response to systemic treatment in Renal Cell Cancer.
Using data from MRI imaging by analysis of the tumour microenvironment and machine learning interrogation of output data, the outcome is to identify novel biomarkers of response.
Time frame: 2 years
Biological identification of biomarkers of response to systemic treatment in Renal Cell Cancer.
Using data from immunohistochemistry, the outcome is to identify novel biomarkers of response.
Time frame: 2 years
Biological identification of biomarkers of response to systemic treatment in Renal Cell Cancer.
Using data from immunofluorescence, the outcome is to identify novel biomarkers of response.
Time frame: 2 years
Biological identification of biomarkers of response to systemic treatment in Renal Cell Cancer.
Using data from CyTOF (mass cytometry), the outcome is to identify novel biomarkers of response.
Time frame: 2 years
No study locations are listed for this record.
Plan to share: Undecided
No publications or documents are linked to this record.
This study is status unknown, as verified in Aug 2019. You cannot join it, but the record below documents what was studied.
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