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In Vivo Metabolic Profiling of CLL (Chronic Lymphocytic Leukemia)

University of Wisconsin, Madison · 2022
ClinicalTrials.gov · Datasets · License: Public Domain · 2022
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chronic-lymphocytic-leukemia
Metabolic reprogramming has been identified as a hallmark of cancer. Almost a century after Otto Warburg initially discovered increased glycolytic activity in tumor tissue ("Warburg effect"), therapeutic targeting of cancer metabolism has become a field of intense research effort in cancer biology. A growing appreciation of metabolic heterogeneity and complexity is currently reshaping investigators "simplistic" understanding of metabolic reprogramming in cancer. Discovering metabolic vulnerabilities as new treatment targets for cancer requires systematic dissection of metabolic dependencies, fuel preferences, and underlying mechanisms in the specific physiological context. However, today's data on cancer cell metabolic signatures and heterogeneity in their physiological habitat of the human organism is sparse to non-existent representing a critical knowledge gap in designing effective metabolic therapies. Here, the investigators propose a "top-down" approach studying cancer cell metabolism in patients followed by mechanistic in-depth studies in cell culture and animal models to define metabolic vulnerabilities. Investigators will develop a metabolic tracing method to quantitatively characterize metabolic signatures and fuel preferences of leukemic lymphocytes in patients with chronic lymphocytic leukemia (CLL). Isotopic metabolic tracers are nutrients that are chemically identical to the native nutrient. Incorporated stable, non-radioactive isotopes allow investigators to follow their metabolic fate by monitoring conversion of tracer nutrients into downstream metabolites using cutting-edge metabolomics analysis. Using this method, investigators propose to test the hypothesis that leukemic lymphocytes show tissue-specific metabolic preferences that differ from non-leukemic lymphocytes and that ex vivo in-plasma labeling represents a useful model for assaying metabolic activity in leukemic cells in a patient-specific manner.
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