Characterizing breast cancer invasive potential using combined label-free multiphoton metabolic imaging of cellular lipids and redox state
- Author(s): Hou, Jue
- Advisor(s): Tromberg, Bruce J
- Potma, Eric O
- et al.
Aerobic glycolysis (Warburg effect) is accompanied by significant alterations in cellular redox state and constitutes one of the hallmarks of cancer cell metabolism. Label-free multi-photon microscopy (MPM) methods based on two-photon excited fluorescence (TPEF) have been used extensively to form high-resolution images of redox state in cells and tissues based on intrinsic NADH and FAD+ fluorescence. However, changes in cellular redox alone are insufficient to fully characterize cancer metabolism and predict invasive potential. We demonstrate that label-free MPM measurements of TPEF-derived redox state (optical redox ratio, ORR = FAD+/(FAD + NADH)) combined with coherent Raman imaging of lipid formation can be used to quantitatively characterize cancer cells and their relative invasive potential. In addition, we confirm, using coherent Raman and deuterium labeling methods, that glucose is a significant source for the cellular synthesis of lipid biomass in glycolytic breast cancer cells. Live cell metabolism was imaged in 3D models of primary mammary epithelial cells (PME) and 2 cancer cell lines, T47D and MDA-MB-231. While we observed overlap in the distribution of the optical redox ratio between these different cell lines, the combination of ORR and lipid volume fraction derived from coherent Raman signals provided complementary independent measures and clear separation. Furthermore, we observed an increase in both lipid synthesis and consumption rates in E2-treated T47D cancer cells cultured in deuterated glucose by tracking the formation and disappearance of deuterated lipids. These results suggest that due to the relatively wide range of ORR values that reflect the natural diversity of breast cancer cellular redox states, the addition of lipid signatures obtained from coherent Raman imaging can improve our ability to characterize and understand key metabolic features that are hallmarks of the disease.