The Study of Metabolic Characteristics of Breast Cancer Metastases Using Fluorescence Lifetime Imaging Microscopy
Anton A Plekhanov1, Snezhana D Sinyushkina1, Dmitriy S Kozlov2
1Privolzhsky Research Medical University, Nizhny Novgorod, 603005, Russia.
Abstract:
The most critical problem in clinical oncology is the metastasis of malignant neoplasms. The survival and growth of metastases in a new microenvironment fundamentally depend on adaptations in the energy metabolism of metastasizing cells. However, these adaptations are far less studied compared to primary tumors. A promising method for assessing the metabolic status of cells is fluorescence lifetime imaging microscopy (FLIM), based on recording the decay parameters of cellular autofluorescence emitted by pyridine and flavin cofactors. This work aims to identify differences in the fluorescence decay kinetics of NAD(P)H between metastatic breast cancer cells and the primary tumor, as well as between metastatic cells and lymph node tissue in a 4T1 mouse model experiment. The study revealed a decrease in the relative fraction of the free form of NAD(P)H (a1, %), i.e., the form not bound to enzymes and associated with glycolysis, in metastases. This indicates a shift in the balance towards mitochondrial respiration. Furthermore, metastases were metabolically more heterogeneous at the cellular level than primary tumors, as evidenced by a higher dispersion of the mean NAD(P)H fluorescence lifetime τm. Additionally, it was found that metastatic cells have a higher contribution of the free NAD(P)H form a1 to the fluorescence decay and, consequently, a shorter mean lifetime τm compared to lymphoid tissue cells (p < 0.001). Thus, this study uses FLIM to demonstrate, for the first time, differences in the temporal characteristics of NAD(P)H autofluorescence between breast cancer metastases and the primary tumor, and between metastases and lymph node tissue. These findings align with existing concepts about the oxidative metabolism of breast cancer metastases. The obtained data are of interest for searching for therapeutic targets in the energy metabolism pathways of metastases and for developing new diagnostic approaches using autofluorescence.
