Dr. Ameeta Kelekar

Lab Medicine & Pathology
Medical School
Twin Cities
Project Title: 
Alpha-Ketoglutarate Bioinformatics

These researchers are investigating ways to exploit the natural metabolite alpha ketoglutarate (aKG) as a tumor suppressor and novel cancer therapeutic and to use it for identifying new and targetable pathways in tumor initiation and progression. As a key intermediate in the energy-producing TCA cycle aKG sits at a crucial intersection that integrates carbon supply to the TCA from both glucose and glutamine. Importantly, aKG also acts as a cofactor for enzymes, such as dioxygenases and histone and DNA demethylases, involved in regulating cell growth and differentiation. Thus, this metabolite has evolved as a messenger molecule signaling nutrient supply and demand to the cell through co-factor activity in non-metabolic reactions.

The importance of aKG’s second-messaging capacity became apparent with the discovery that mutations in isocitrate dehydrogenase (IDH) were prominent in glioblastomas and acute myeloid leukemias. IDH catalyzes the reaction that generates aKG from isocitrate and mutations in IDH lead to an incomplete reaction causing accumulation of 2-hydroxyglutarate (2-HG), an "oncometabolite." Structural similarity of 2-HG to aKG underlies its ability to act as an aKG antagonist and competitively inhibit multiple aKG-dependent enzymes, including lysine histone demethylases and the Tet family of DNA hydroxylases. The numerous reports of the oncogenic role of 2-HG led this group to hypothesize that aKG could be therapeutically effective as a natural tumor suppressor metabolite and that identifying aKG influenced gene expression changes would be valuable in designing therapeutic strategies. The researchers have data showing the ability of cell permeable dimethyl (DM)-aKG to suppress growth in a variety of cancer cells including lung and colorectal cancer and an acute T-leukemia cell line. They designed a proteomics approach to help identify major critical pathways targeted by aKG using the Jurkat T-leukemia line as a model. A fully resistant aKG treated population of cells was generated and the protein signature of the aKG resistant cells was compared with that of the sensitive parental cells in an unbiased high-throughput proteomics screen based on iTRAQ technology. This experiment yielded several thousand differentially expressed proteins, some of which have been verified by Western blot. The researchers are using bioinformatics methods to further explore and probe this large and highly significant dataset to identify novel pathways and gene sets regulated by aKG treatment.

Project Investigators

Dr. Juan Abrahante Llorens
Dr. Ameeta Kelekar
Dr. Sarah Munro
Christine O'Connor
Yinjie Qiu
Tingyuan Yang
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