A Spectroscopic Technique to Simultaneously Characterize Fatty Acid Uptake, Mitochondrial Activity, Vascularity, and Oxygen Saturation for Longitudinal Studies In Vivo

Abstract

Aggressive breast cancer has been shown to shift its metabolism towards increased lipid catabolism as the primary carbon source for oxidative phosphorylation. In this study, we present a technique to longitudinally monitor lipid metabolism and oxidative phosphorylation in pre-clinical tumor models to investigate the metabolic changes with mammary tissue development and characterize metabolic differences between primary murine breast cancer and normal mammary tissue. We used optical spectroscopy to measure the signal of two simultaneously injected exogenous fluorescent metabolic reporters: TMRE (oxidative phosphorylation surrogate) and Bodipy FL C16 (lipid catabolism surrogate). We leverage an inverse Monte Carlo algorithm to correct for aberrations resulting from tissue optical properties and to extract vascular endpoints relevant to oxidative metabolism, specifically oxygen saturation (SO2) and hemoglobin concentration ([Hb]). We extensively validated our optical method to demonstrate that our two fluorescent metabolic endpoints can be measured without chemical or optical crosstalk and that dual measurements of both fluorophores in vivo faithfully recapitulate the measurements of each fluorophore independently. We then applied our method to track the metabolism of growing 4T1 and 67NR breast tumors and aging mammary tissue, all highly metabolic tissue types. Our results show the changes in metabolism as a function of mammary age and tumor growth, and these changes can be best distinguished through the combination of endpoints measured with our system. Clustering analysis incorporating both Bodipy FL C16 and TMRE endpoints combined with either SO2 or [Hb] proved to be the most effective in minimizing intra-group variance and maximizing inter-group differences. Our platform can be extended to applications in which long-term metabolic flexibility is important to study, for example in tumor regression, recurrence following dormancy, and responses to cancer treatment.

Imaging and Spectroscopic-Based Methods to Understand Cancer Metabolism and Biology

“…The present Special Issue contains four reviews [ 1 , 2 , 3 , 4 ] and four research articles [ 5 , 6 , 7 , 8 ] with the original work covering a wide range of methods that can be applied to assess and measure several characteristics of tumours.…”

“…Dr Deutsch et al presented a non-invasive method to simultaneously measure exogenous reporters of fatty acid uptake and metabolic membrane potential and endogenous contrast related to haemoglobin concentration and tissue oxygenation [ 5 ]. The authors demonstrated the feasibility of this method by showing that Bodipy FL C16 (lipid phosphorylation surrogate) and TMRE (oxidative phosphorylation surrogate) do not crosstalk chemically, optically or biologically, and that these probes are compatible with an inverse Monte Carlo algorithm to extract tissue optical properties and intrinsic fluorescent signals.…”

“…Deuterium metabolic imaging (DMI) has strong potential to become a dominant MR research tool and a viable clinical imaging modality to map metabolism with high temporal and/or spatial resolution in oncology. The present Special Issue contains four reviews [1][2][3][4] and four research articles [5][6][7][8] with the original work covering a wide range of methods that can be applied to assess and measure several characteristics of tumours.…”