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Oncotarget. 2015 Oct 20;6(32):33369-81. doi: 10.18632/oncotarget.5409.

Lowered circulating aspartate is a metabolic feature of human breast cancer.

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Center for Translational Medicine, and Shanghai Key Laboratory of Diabetes Mellitus, Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
University of Hawaii Cancer Center, Honolulu, HI, USA.
Department of Medical Oncology and Therapeutic Research, City of Hope National Medical Center, Duarte, CA, USA.
Albert Einstein College of Medicine, Yeshiva University, Bronx, NY, USA.
Nutrition Research Institute, University of North Carolina at Chapel Hill, North Carolina Research Campus, Kannapolis, NC, USA.
Taipei Medical University, Taipei, Taiwan.


Distinct metabolic transformation is essential for cancer cells to sustain a high rate of proliferation and resist cell death signals. Such a metabolic transformation results in unique cellular metabolic phenotypes that are often reflected by distinct metabolite signatures in tumor tissues as well as circulating blood. Using a metabolomics platform, we find that breast cancer is associated with significantly (p = 6.27E-13) lowered plasma aspartate levels in a training group comprising 35 breast cancer patients and 35 controls. The result was validated with 103 plasma samples and 183 serum samples of two groups of primary breast cancer patients. Such a lowered aspartate level is specific to breast cancer as it has shown 0% sensitivity in serum from gastric (n = 114) and colorectal (n = 101) cancer patients. There was a significantly higher level of aspartate in breast cancer tissues (n = 20) than in adjacent non-tumor tissues, and in MCF-7 breast cancer cell line than in MCF-10A cell lines, suggesting that the depleted level of aspartate in blood of breast cancer patients is due to increased tumor aspartate utilization. Together, these findings suggest that lowed circulating aspartate is a key metabolic feature of human breast cancer.


aspartate; breast cancer; diagnosis; metabolomics; multivariate analysis

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