2012-08-30
Localized hypoxia results in spatially heterogeneous metabolic signatures in breast tumor models
Publication
Publication
Neoplasia , Volume 14 - Issue 8 p. 732- 741
Tumor hypoxia triggers signaling cascades that significantly affect biologic outcomes such as resistance to radiotherapy and chemotherapy in breast cancer. Hypoxic regions in solid tumor are spatially heterogeneous. Therefore, delineating the origin and extent of hypoxia in tumors is critical. In this study, we have investigated the effect of hypoxia on different metabolic pathways, such as lipid and choline metabolism, in a human breast cancer model. Human MDA-MB-231 breast cancer cells and tumors, which were genetically engineered to express red fluorescent tdTomato protein under hypoxic conditions, were used to investigate hypoxia. Our data were obtained with a novel three-dimensional multimodal molecular imaging platform that combines magnetic resonance (MR) imaging, MR spectroscopic imaging (MRSI), and optical imaging of hypoxia and necrosis. A higher concentration of noninvasively detected total choline-containing metabolites (tCho) and lipid CH3 localized in the tdTomato-fluorescing hypoxic regions indicated that hypoxia can upregulate tCho and lipid CH3 levels in this breast tumor model. The increase in tCho under hypoxia was primarily due to elevated phosphocholine levels as shown by in vitro MR spectroscopy. Elevated lipid CH3 levels detected under hypoxia were caused by an increase in mobile MR-detectable lipid droplets, as demonstrated by Nile Red staining. Our findings demonstrate that noninvasive MRSI can help delineate hypoxic regions in solid tumors by means of detecting themetabolic outcome of tumor hypoxia, which is characterized by elevated tCho and lipid CH3.
Additional Metadata | |
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Elsevier B.V. | |
doi.org/10.1593/neo.12858 | |
Neoplasia | |
Jiang, L., Greenwood, T. R., Artemov, D., Raman, V., Winnard Jr., P. T., Heeren, R., … Glunde, K. (2012). Localized hypoxia results in spatially heterogeneous metabolic signatures in breast tumor models. Neoplasia, 14(8), 732–741. doi:10.1593/neo.12858 |