This proposal is motivated by the principle that systematic analysis of Renal Cell Carcinoma (RCC) metabolism will produce biomarkers predicting oncological behavior and tumor-specific vulnerabilities against which to direct novel therapies. RCC is diagnosed with increasing frequency in asymptomatic patients due to the proliferation of cross-sectional imaging techniques. Although most small renal masses (SRMs) diagnosed in this manner are indolent, there are no clear criteria by which to predict whether a given mass will behave aggressively and require escalation of care. We propose to capitalize on altered RCC metabolism to identify predictive biomarkers correlating with oncological behavior in SRMs undergoing active surveillance (AS), and to identify a key set of reprogrammed metabolic activities whose function is required for aggressive RCC growth. The rationale for the project is as follows: 1) most genes mutated in RCC regulate metabolism at the cellular level; 2) metabolism is dynamic, quantifiable and responsive to many processes relevant to RCC biology and disease progression; 3) many of these processes can be monitored non-invasively through multiparametric magnetic resonance (mpMR) imaging; and 4) blockade of these metabolic activities should prevent tumor progression. We therefore hypothesize that rigorous metabolomics and imaging can be used to identify quantitative features that predict tumor aggressiveness in SRMs, and that can be inhibited to suppress the growth of aggressive RCC. We will pursue three aims to test this hypothesis, each featuring an integrated, innovative array of techniques developed by the outstanding group of investigators involved in this Project.
Aims 1 and 2 will feature a prospective, observational study of 160 patients on AS for incidentally diagnosed SRMs. This cohort will be monitored longitudinally by mpMRI (Aim 1) and by metabolomics in the renal mass and urine (Aim 2). Patients who progress to surgical intervention because of accelerating tumor growth rates will have imaging and metabolomics repeated at the time of nephrectomy, and a subset of patients will receive intra-operative infusion of isotope-labeled nutrients to assess tumor metabolic flux in vivo (Aim 2). Data from the cohort will be analyzed to identify metabolomic and imaging features correlating with oncological aggression.
In Aim 3, we will use metabolomics, metabolic flux analysis and multi-modality imaging (PET, MR) to identify metabolic features of aggressive RCC growth in a set of genetically and histologically diverse orthotopic RCC tumors in mice. Enzymes from key pathways differentiating tumor from normal kidney will be inhibited to determine the effect on tumor growth. Altogether, work in this Project will produce a comprehensive and dynamic view of reprogrammed metabolism in human RCC and will identify new metabolic candidates for targeted therapy. A key, unique deliverable, satisfying an important unmet clinical need in kidney cancer management, will be the discovery of a set of biomarkers with the potential to guide AS in patients with incidentally diagnosed SRMs.

Public Health Relevance

Renal cell carcinoma (RCC) is a deadly and poorly understood form of cancer. A wealth of genetic and molecular information indicates that this disease is characterized by a dramatic reprogramming of metabolism in the tumor cells. Our work will use metabolomics and MR-based imaging of metabolic features in human and mouse RCC to identify biomarkers of aggressive tumor growth and new therapeutic targets.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center (P50)
Project #
5P50CA196516-05
Application #
9990734
Study Section
Special Emphasis Panel (ZCA1)
Project Start
2016-08-01
Project End
2021-07-31
Budget Start
2020-08-01
Budget End
2021-07-31
Support Year
5
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Texas Sw Medical Center Dallas
Department
Type
DUNS #
800771545
City
Dallas
State
TX
Country
United States
Zip Code
75390
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