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Brief Title: Renal Cell Carcinoma Microenvironment Discovery Project
Official Title: Molecular Dissection of the Renal Cell Carcinoma Tumor Microenvironment for the Discovery of Novel Therapeutic Targets
Study ID: NCT04005183
Brief Summary: This study will obtain tumor samples from nephrectomy specimens in a multi-regional fashion and subject them to integrated genomics, proteomics, pathological, and radiological assessment. The goal is to better understand the the molecular basis for how various cells within the tumor microenvironment act in a coordinated manner to facilitate tumor progression and therapy resistance. Our ultimate aim is to leverage this data resource to identify novel therapeutic targets and biomarkers to improve the clinical management of this disease.
Detailed Description: This study is an observational prospective trial where renal cell carcinoma samples are isolated from nephrectomy specimens in a multi-regional manner and subjected to an integrated genomic, proteomic, pathological, radiological assessment to provide a detailed morphological and molecular view of the RCC microenvironment. The major genomics technologies used to examine tumour specimens include single cell RNA sequencing including nuclear (NUCseq) and epitope sequencing (CITEseq). Additionally, bulk RNA/DNA sequencing, targeted mutational profiling, and imaging mass cytometry will be performed. These technologies will determine mutational and gene/protein expression profiles of various heterogeneous cell populations within the tumour microenvironment, including cancer, immune, and supporting cells. This will allow identification of mutations and abnormal expression patterns within individual cells, that will be used to infer targetable vulnerabilities and biomarker signatures.
Minimum Age: 18 Years
Eligible Ages: ADULT, OLDER_ADULT
Sex: ALL
Healthy Volunteers: No
University Health Network, Princess Margaret Hospital, Toronto, Ontario, Canada
Name: Antonio Finelli, MD
Affiliation: University Health Network, Toronto
Role: PRINCIPAL_INVESTIGATOR