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Computed Tomography-guided Time-domain Diffuse Fluorescence Tomography in Small Animals for Localization of Cancer Biomarkers
Published on: July 17, 2012
Detection of malignancies in mice using TXRF analysis and reaction-based optical fingerprinting of blood plasma
Alexander O Ustyuzhanin1, Evgenii V Skorobogatov1, Gulalek Babayeva2
1Lomonosov Moscow State University, Department of Chemistry, Moscow, Russia.
Abstract:
This study explores the potential of reaction-based optical fingerprinting and total X-ray fluorescence (TXRF) elemental analysis, both separately and in combination, as a rapid and inexpensive approach to preliminary cancer diagnostics. Plasma samples from BALB/c mice with transplanted mammary carcinoma (EMT-6) and BDF1 mice with Lewis lung carcinoma (LLC) or B16 melanoma were analyzed. The optical fingerprinting method relies on differences in the oxidation rate of a carbocyanine dye in the presence of blood plasma samples. Changes in fluorescence and absorption intensity were recorded photographically, enabling high-throughput analysis. The obtained images were digitized and the resulting dataset was processed using various statistical methods. Reaction-based optical fingerprinting achieved up to 100% observed accuracy in several classification tasks within the limited proof-of-concept dataset, distinguishing between healthy and diseased animals with transplanted tumors at different time points after tumor cell inoculation: 1 week for LLC, 2 weeks for B16, and 3 weeks for EMT-6. The same samples were simultaneously analyzed using TXRF, which also achieved 100% recognition accuracy when distinguishing between healthy animals and mice bearing LLC (after 1 and 2 weeks) or B16 melanoma (after 2 weeks). Although a direct combination of the reaction-based optical fingerprinting and TXRF analysis data into a single array did not consistently improve discrimination accuracy, the individual methods complement each other and enable effective screening of various cancer types. Overall, the kinetic-based fingerprint method demonstrated significant potential in distinguishing between different types and stages of malignancies in mice.

