Abstract

Abstract Breast cancer is the most common cancer in women in the United States. Gene expression profiling studies of breast tumors led to the discovery of disease subtypes with different biologies. These studies also described novel biomarkers for therapy response and disease survival. However, it remains a challenge to define breast cancer biology solely based on gene expression. Recently, metabolomics emerged as a new discovery tool with the promise of identifying prognostic biomarkers and targetable metabolic dependencies of cancer cells. We previously measured the abundance of 536 metabolites in 67 breast tumor and their tumor adjacent noncancerous tissue by untargeted mass spectrometry. In the current study, we explored the prognostic power of the metabolome and conducted an integrated analysis comprising of the metabolome, transcriptome, and proteome to explore the association of metabolites with cell systems, tumor biology, and disease outcome. We built a predictive model based on multivariable Cox proportional hazards using the L1 penalized log partial likelihood (LASSO) method after pre-selecting prognostic metabolites following cross-validation with 1000 iterations. The median C-index was 0.73, indicating a certain robustness of metabolites as classifiers of breast cancer outcome. The models identified five metabolites including a bile acid-related metabolite, glycochenodeoxycholate (GCDC), as the most frequently selected features and outcome markers among these metabolites. An increased GCDC tumor content was associated with improved patient survival. We corroborated the presence of GCDC and three other bile acids in the human breast tissues using absolute measurements and confirmed their occurrence in breast tumors. Because additional large-scale transcriptome and proteome data were available for the same tissue samples, we further characterized the tumors based on their GCDC abundance, which showed that cell cycle-related pathways were enriched for differently expressed genes and tumors with a high GCDC content tended to have a low cell proliferation score, indicating that accumulation of GCDC leads to growth inhibition. We also conducted a correlation analysis for the relationship between GCDC abundance with other metabolites and identified 51 metabolites that were significantly correlated with GCDC. In this analysis, metabolite abundance in the sterol/steroid pathway associated most strongly with the GCDC tissue content. Lastly, we evaluated the effect of bile acids on breast cancer cell lines. The data showed a strong reduction of cancer cell proliferation under bile acid treatment, consistent with the tumor data, and distinct changes in gene expression. In conclusion, we propose that integrated metabolomics can provide powerful prognostic information with GCDC being a novel prognostic marker in breast cancer because accumulation of GCDC reduces cancer cell proliferation. Citation Format: Wei Tang, Tiffany Dorsey, Vasanta Putluri, Nagireddy Putluri, Stefan Ambs. Accumulation of a liver- and microbiome-derived metabolite in human breast tumors is associated with patient survival [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2518. doi:10.1158/1538-7445.AM2017-2518

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