Quantitative mitochondrial redox imaging of breast cancer metastatic potential
Abstract
Predicting tumor metastatic potential remains a challenge in cancer research and clinical practice. Our goal was to identify novel biomarkers for differentiating human breast tumors with different metastatic potentials by imaging the in vivo mitochondrial redox states of tumor tissues. The more metastatic (aggressive) MDA-MB-231 and less metastatic (indolent) MCF-7 human breast cancer mouse xenografts were imaged with the low-temperature redox scanner to obtain multi-slice fluorescence images of reduced nicotinamide adenine dinucleotide (NADH) and oxidized flavoproteins (Fp). The nominal concentrations of NADH and Fp in tissue were measured using reference standards and used to calculate the Fp redox ratio, Fp∕(NADH+Fp). We observed significant core-rim differences, with the core being more oxidized than the rim in all aggressive tumors but not in the indolent tumors. These results are consistent with our previous observations on human melanoma mouse xenografts, indicating that mitochondrial redox imaging potentially provides sensitive markers for distinguishing aggressive from indolent breast tumor xenografts. Mitochondrial redox imaging can be clinically implemented utilizing cryogenic biopsy specimens and is useful for drug development and for clinical diagnosis of breast cancer.
Acknowledgments
This work was supported by the Susan G. Komen Foundation Grant No. {"type":"entrez-nucleotide","attrs":{"text":"KG081069","term_id":"515057132","term_text":"KG081069"}}KG081069 (PI: L. Z. Li), the Network of Translational Research in Optical Imaging (NTROI) at the University of Pennsylvania (U54 {"type":"entrez-nucleotide","attrs":{"text":"CA105008","term_id":"34958315","term_text":"CA105008"}}CA105008, PI: W. S. El-Deiry), the Center for Magnetic Resonance and Optical Imaging–an NIH-supported research resource (RR02305, PI: R. Reddy), SAIR Grant No. 2U24-{"type":"entrez-nucleotide","attrs":{"text":"CA083105","term_id":"34936416","term_text":"CA083105"}}CA083105 (PI: J. D. Glickson and L. A. Chodosh), and NIH Grant No. UO1-{"type":"entrez-nucleotide","attrs":{"text":"CA105490","term_id":"34958797","term_text":"CA105490"}}CA105490 (PI: L. A.Chodosh). We would like to thank Mr. Baohua Wu for his assistance, particularly in software development. We would also like to thank Mr. David Nelson for his technical laboratory assistance and Dr. Dennis Leeper for valuable discussions about human xenograft models.




