Metabolic profiling of cancer cells has recently been established as a promising tool for the development of therapies and identification of cancer biomarkers. Here we characterized the metabolomic profile of human breast tumors and uncovered intrinsic metabolite signatures in these tumors using an untargeted discovery approach and validation of key metabolites. The oncometabolite 2-hydroxyglutarate (2HG) accumulated at high levels in a subset of tumors and human breast cancer cell lines. We discovered an association between increased 2HG levels and MYC pathway activation in breast cancer, and further corroborated this relationship using MYC overexpression and knockdown in human mammary epithelial and breast cancer cells. Further analyses revealed globally increased DNA methylation in 2HG-high tumors and identified a tumor subtype with high tissue 2HG and a distinct DNA methylation pattern that was associated with poor prognosis and occurred with higher frequency in African-American patients. Tumors of this subtype had a stem cell–like transcriptional signature and tended to overexpress glutaminase, suggestive of a functional relationship between glutamine and 2HG metabolism in breast cancer. Accordingly, 13C-labeled glutamine was incorporated into 2HG in cells with aberrant 2HG accumulation, whereas pharmacologic and siRNA-mediated glutaminase inhibition reduced 2HG levels. Our findings implicate 2HG as a candidate breast cancer oncometabolite associated with MYC activation and poor prognosis.
Atsushi Terunuma, Nagireddy Putluri, Prachi Mishra, Ewy A. Mathé, Tiffany H. Dorsey, Ming Yi, Tiffany A. Wallace, Haleem J. Issaq, Ming Zhou, J. Keith Killian, Holly S. Stevenson, Edward D. Karoly, King Chan, Susmita Samanta, DaRue Prieto, Tiffany Y.T. Hsu, Sarah J. Kurley, Vasanta Putluri, Rajni Sonavane, Daniel C. Edelman, Jacob Wulff, Adrienne M. Starks, Yinmeng Yang, Rick A. Kittles, Harry G. Yfantis, Dong H. Lee, Olga B. Ioffe, Rachel Schiff, Robert M. Stephens, Paul S. Meltzer, Timothy D. Veenstra, Thomas F. Westbrook, Arun Sreekumar, Stefan Ambs
Usage data is cumulative from May 2024 through May 2025.
Usage | JCI | PMC |
---|---|---|
Text version | 1,398 | 304 |
158 | 77 | |
Figure | 587 | 9 |
Table | 54 | 0 |
Supplemental data | 253 | 60 |
Citation downloads | 90 | 0 |
Totals | 2,540 | 450 |
Total Views | 2,990 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.