Kai Xin Ooi, Christine Ricky, Nurul Ashikin MS, Audrey Fanty, Lai Yen Fong, Susan Ling Ling Hoe and Yang Mooi Lim

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IN VIVO BIOLUMINESCENCE IMAGING FOR LONGITUDINAL TUMORIGENICITY ASSESSMENT: CORRELATIONS WITH TUMOR VOLUME AND POST-D-LUCIFERIN INJECTION IMAGING TIMEPOINTS

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Abstract 

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Bioluminescence imaging (BLI) demonstrated superior sensitivity and specificity over the volumetric measurement for longitudinal tracking of tumor development. Luciferase activity is measured by determining the peak bioluminescence intensity, which serves as a quantitative indicator of tumor burden. The peak signal could only be acquired via a sequential imaging strategy. However, most researchers opted for a single timepoint imaging strategy to improve experimental throughput. The temporal dynamics of bioluminescence intensities driven by luciferin kinetics, which change over time, thus pose a challenge for accurate tumor growth estimation. The current study aims to evaluate the correlation between volumetric measurement and BLI of xenografted tumors for longitudinal assessment. Also, to address the variations in BLI intensity that arise from luciferin kinetics over days. Three NSG mice were inoculated subcutaneously with HT-29-GFP-Luc2 cells and assessed for tumorigenicity via volumetric measurements and sequential BLI. Both tumor volume and BLI signals demonstrated strong positive correlations with R2 > 0.90 when the mean volume remained below 1200 mm3. The study also demonstrated that temporal dynamics in bioluminescence kinetics can lead to varying degrees of under- or overestimation of tumor growth. The best imaging timepoint representing the peak time is eight minutes post-D-luciferin injection. This is due to its low luciferin kinetic variability and high exchangeability with peak time, which gives it the closest resemblance to the peak signal growth ratio. It is therefore suggested to image the tumors at eight minutes post-D-luciferin injection when practicing single-timepoint BLI in experiments using HT-29-GFP-Luc2 xenograft models.

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