Cell heterogeneity in tumor microenvironment has been an issue for the variation of drug response between patients in cancer treatment. Instead of overviewing cancer as a generalized system, single cell analysis helps clarify the mechanism between drug and its targeted intracellular compartment. With the advantages of simple sample preparation and non-destructive detection, infrared (IR) spectroscopic imaging is an emerging technique that provides both qualitative and quantitative information in high throughput manner to observe cell dynamics. However, there is a difficulty in quantifying drug concentration within a single cell due to the overlapping of the intrinsic IR signature of the drug and the biological samples. To solve the issue, a doxorubicin derivative (DOX-IR Label), which showed two distinguishable peaks (1995 and 2050 cm-1) within the bio-silent region (1800-2000 cm-1) of IR spectra is developed by tagging doxorubicin with a metal-carbonyl moiety ((Cp)Fe(CO)2). The conjugation and properties of DOX-IR Label were confirmed by NMR, mass spectroscopy, ATR-IR, elemental analysis and UV-Vis spectroscopy. Furthermore, an initial biological evaluation of DOX-IR Label was performed on MCF10AT cell series, which comprise four cell lines, representing the breast cancer progression. The cellular uptake was quantified by the carbonyl peaks in IR spectra and correlated with the relative intracellular fluorescence intensity. To validate the localization of DOX-IR Label, nucleus or mitochondrial fluorescent staining was performed on the identical sample to support the IR chemical images. The ability to quantify drug compounds in a label-free and non-destructive manner using IR spectroscopic imaging can become a potential tool for fields such as pharmacology. Overall, the development of small molecules with endogenous signals for biological evaluation offers the ability to understand cell and drug interaction across multiple platforms and will accelerate future drug development.

Development of biotracker for studying drug localization and quantification in single cell via label-free ulti-modality imaging

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