Clinical trial · Observational
Renal Cell Carcinoma Microenvironment Discovery Project
Molecular Dissection of the Renal Cell Carcinoma Tumor Microenvironment for the Discovery of Novel Therapeutic Targets
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
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.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Renal Cell Carcinoma | Renal Cell Carcinoma | CURATED_BROADER | 0.80 |
Interventions
Interventions (0)
Data not yet available
Design
Arms and outcomes
Arms (1)
- label
- All patients
- description
- Patients undergoing nephrectomy at the University Health Network are eligible for enrolment. All renal cell carcinoma histological subtypes and stages are eligible. Tumor, blood and urine samples are acquired at the time of nephrectomy.
Primary outcomes (2)
- measure
- Molecular profiling of various cell populations within tumour by using single cell RNAseq.
- timeFrame
- 10 years
- description
- The RNA transcripts of tumour cells will be sequenced and subjected to informatics and descriptive statistical methods to generate comprehensive data sets that aid in better understanding of the tumour microenvironment in various patients and disease types. These data sets will provide insights into drug target discovery, and used as hypothesis-generating guidance for future study aims.
- measure
- Determination of the radiological and pathological features associated with the derived tumor microenvironment molecular data
- timeFrame
- 10 years
- description
- The radiological and pathological assessment on each tumour case will be paired with the gene- and protein-level data to provide a comprehensive picture of the disease. These datasets will be used as training sets to guide machine learning technologies with the intention of aiding diagnosis, prognosis prediction, and treatment plans in the future.
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * Nephrectomy * Primary or metastatic disease * Any histology of renal cell carcinoma Exclusion Criteria: * NA
References
Publications (0)
Data not yet available