Accelerator mass spectrometry allows for cellular quantification of doxorubicin at femtomolar concentrations

Abstract

Accelerator mass spectrometry (AMS) is a highly sensitive analytical methodology used to quantify the content of radioisotopes, such as (14)C, in a sample. The primary goals of this work were to demonstrate the utility of AMS in determining total cellular [(14)C]anthracycline concentrations following administration of doxorubicin (DOX) and to develop a sensitive assay that is superior to high performance liquid chromatography (HPLC) for the quantification of [(14)C]anthracycline at the tumor level. In order to validate the sensitivity of AMS versus HPLC with fluorescence detection, we performed three studies comparing the cellular accumulation of DOX: one in vitro cell line study, and two in vivo xenograft mouse studies. Using AMS, we quantified cellular [(14)C]anthracycline content up to 4 h following in vitro exposure at concentrations ranging from 0.2 pg/ml (345 fM) to 2 microg/ml (3.45 microM) [(14)C]DOX. The results of this study show that, compared to standard fluorescence-based HPLC, the AMS method was over five orders of magnitude more sensitive. Two in vivo studies compared the sensitivity of AMS to HPLC using a nude mouse xenograft model in which breast cancer cells were implanted subcutaneously. After sufficiently large tumors formed, [(14)C]DOX was administered intravenously at two dose levels. Additionally, we tested the AMS method in a nude mouse xenograft model of multidrug resistance (MDR) in which each mouse was implanted with both wild type and MDR+ cells on opposite flanks. The results of the second and third studies showed that [(14)C]anthracycline concentrations were significantly higher in the wild type tumors compared to the MDR+ tumors, consistent with the MDR model. Although this method does not discriminate between parent drug and metabolites, the extreme sensitivity of AMS should facilitate similar studies in humans to establish target site drug delivery and to potentially determine the optimal treatment dose and regimen.