Monitoring metabolic responses to chemotherapy in single cells and tumors using nanostructure-initiator mass spectrometry (NIMS) imaging

NIMS analytical sensitivity and spatial resolution were examined in cultured Burkitt’s lymphoma cells treated briefly with Rapamycin or FLT. Sample aliquots were dispersed on NIMS surfaces for single cell imaging and metabolic profiling, or extracted in parallel for LC-MS/MS analysis. Docetaxel-induced changes in FLT metabolism were also monitored in tissues and tissue extracts from mice bearing drug-sensitive tumor xenografts. To correct for variations in FLT disposition, the ratio of FLT-MP to FLT was used as a measure of TK1 thymidine kinase activity in NIMS images. TK1 and tumor-specific luciferase were measured in adjacent tissue sections using immuno-fluorescence microscopy.NIMS and LC-MS/MS yielded consistent results. FLT, FLT-MP, and Rapamycin were readily detected at the single cell level using NIMS. Rapid changes in endogenous metabolism were detected in drug-treated cells, and rapid accumulation of FLT-MP was seen in most, but not all imaged cells. FLT-MP accumulation in xenograft tumors was shown to be sensitive to Docetaxel treatment, and TK1 immunoreactivity co-localized with tumor-specific antigens in xenograft tumors, supporting a role for xenograft-derived TK1 activity in tumor FLT metabolism.NIMS is suitable for monitoring drug exposure and metabolite biotransformation with essentially single cell resolution, and provides new spatial and functional dimensions to studies of cancer metabolism without the need for radiotracers or tissue extraction. These findings should prove useful for in vitro and pre-clinical studies of cancer metabolism, and aid the optimization of metabolism-based cancer therapies and diagnostics.Genetic and environmental cues, including stresses from anti-cancer treatments, can induce significant changes in cell and tissue metabolism. Understanding the relationships between drug exposure and tissue metabolism can improve diagnosis and treatment outcomes, and speed the identification of new drug targets and biomarkers [1]. Quanti