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Global Metabolomics Reveals Urinary Biomarkers of Breast Cancer in a MCF-7 Xenograft Mouse Model
Global metabolomics analysis has the potential to uncover novel metabolic pathways that are differentially regulated during carcinogenesis, aiding in biomarker discovery for early diagnosis and remission monitoring. Metabolomics studies with human samples can be problematic due to high inter-individ...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3901288/ https://www.ncbi.nlm.nih.gov/pubmed/24958144 http://dx.doi.org/10.3390/metabo3030658 |
Sumario: | Global metabolomics analysis has the potential to uncover novel metabolic pathways that are differentially regulated during carcinogenesis, aiding in biomarker discovery for early diagnosis and remission monitoring. Metabolomics studies with human samples can be problematic due to high inter-individual variation; however xenografts of human cancers in mice offer a well-controlled model system. Urine was collected from a xenograft mouse model of MCF-7 breast cancer and analyzed by mass spectrometry-based metabolomics to identify metabolites associated with cancer progression. Over 10 weeks, 24 h urine was collected weekly from control mice, mice dosed with estradiol cypionate (1 mg/mL), mice inoculated with MCF-7 cells (1 × 10(7)) and estradiol cypionate (1 mg/mL), and mice dosed with MCF-7 cells (1 × 10(7)) only (n = 10/group). Mice that received both estradiol cypionate and MCF-7 cells developed tumors from four weeks after inoculation. Five urinary metabolites were identified that were associated with breast cancer; enterolactone glucuronide, coumaric acid sulfate, capric acid glucuronide, an unknown metabolite, and a novel mammalian metabolite, “taurosebacic acid”. These metabolites revealed a correlation between tumor growth, fatty acid synthesis, and potential anti-proliferative effects of gut microbiota-metabolized food derivatives. These biomarkers may be of value for early diagnosis of cancer, monitoring of cancer therapeutics, and may also lead to future mechanistic studies. |
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