Developing a Prognostic Algorithm for clear cell Renal Cell Carcinoma Using Preclinical Biomarkers for Two Distinct Subtypes

 

Trainee:

Samira Brooks

Samira Brooks

Research Mentor:

Dr. Kimryn Rathmell,

MD, PhD

Rathmel

Clinical Co-Mentor:

Dr. Matt Neilson

unavailable
Department Toxicology
Project Description:

The majority of patients with renal tumors have the clear cell Renal Cell Carcinoma (ccRCC) subtype, a tumor associated with VHL mutations and a poor prognosis in the metastatic state. Recently, the lab elucidated two subtypes of clear cell RCC, ccA and ccB, that convey a prognostic value, with tumors displaying the ccA signature associated with an 8.6 year survival as compared to only 2 years for ccB. Originally, 120 genes were identified to assign ccA and ccB classification to ccRCC tumors. Now, my project entails condensing this list into a biomarker gene set that could be used as a translational tool. The ccA/ccB definitive biomarker set will undergo validation and development as a diagnostic test. Classifying a large cohort of retrospectively collected non-metastatic ccRCC specimens and identifying correlations between the subtypes and risk assessments, including disease recurrence and cancer-specific survival, will accomplish this. Once the biomarkers are authenticated, I plan to further investigate if ccRCC subclassification can predict clinical response to anti-angiogenic therapies, as well as analyze whether epidemiological and demographic factors influence subtype. These results will all be used as preliminary data to develop a biomarker inclusive risk algorithm for integration into the clinical arena.