Abstract | PURPOSE: Metabolomics is a discovery tool for novel associations of metabolites with disease. Here, we interrogated the metabolome of human breast tumors to describe metabolites whose accumulation affects tumor biology. EXPERIMENTAL DESIGN: We applied large-scale metabolomics followed by absolute quantification and machine learning-based feature selection using LASSO to identify metabolites that show a robust association with tumor biology and disease outcome. Key observations were validated with the analysis of an independent dataset and cell culture experiments. RESULTS: CONCLUSIONS: We describe the unexpected accumulation of liver- and microbiome-derived bile acids in breast tumors. Tumors with increased bile acids show decreased proliferation, thus fall into a good prognosis category, and exhibit significant changes in steroid metabolism.
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Authors | Wei Tang, Vasanta Putluri, Chandrashekar R Ambati, Tiffany H Dorsey, Nagireddy Putluri, Stefan Ambs |
Journal | Clinical cancer research : an official journal of the American Association for Cancer Research
(Clin Cancer Res)
Vol. 25
Issue 19
Pg. 5972-5983
(10 01 2019)
ISSN: 1557-3265 [Electronic] United States |
PMID | 31296531
(Publication Type: Journal Article, Research Support, N.I.H., Extramural, Research Support, N.I.H., Intramural, Research Support, Non-U.S. Gov't)
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Copyright | ©2019 American Association for Cancer Research. |
Chemical References |
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Topics |
- Bile Acids and Salts
(metabolism)
- Breast Neoplasms
(metabolism, mortality, pathology)
- Cell Proliferation
(physiology)
- Female
- Humans
- Liver
(metabolism)
- Metabolome
- Microbiota
- Prognosis
- Survival Rate
- Tumor Cells, Cultured
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