Bioluminescent imaging (BLI) to improve and refine traditional murine models of tumor growth and metastasis.

Bioluminescent imaging (BLI) permits sensitive in vivo detection and quantification of cells specifically engineered to emit visible light. Three stable human tumor cell lines engineered to express luciferase were assessed for their tumorigenicity in subcutaneous, intravenous and spontaneous metastasis models. Bioluminescent PC-3M-luc-C6 human prostate cancer cells were implanted subcutaneously into SCID-beige mice and were monitored for tumor growth and response to 5-FU and mitomycin C treatments. Progressive tumor development and inhibition/regression following drug treatment were observed and quantified in vivo using BLI. Imaging data correlated to standard external caliper measurements of tumor volume, but bioluminescent data permitted earlier detection of tumor growth. In a lung colonization model, bioluminescent A549-luc-C8 human lung cancer cells were injected intravenously and lung metastases were monitored in vivo by whole animal imaging. Anesthetized mice were imaged weekly allowing a temporal assessment of in vivo lung tumor growth. This longitudinal study design permitted an accurate, real-time evaluation of tumor burden in the same animals over time. End-point bioluminescence measured in vivo correlated to total lung weight at necropsy. For a spontaneous metastatic tumor model, bioluminescent HT-29-luc-D6 human colon cancer cells implanted subcutaneously produced metastases to lung and lymph nodes in SCID-beige mice. Both primary tumors and micrometastases were detected by BLI in vivo. Ex vivo imaging of excised lung lobes and lymph nodes confirmed the in vivo signals and indicated a slightly higher frequency of metastasis in some mice. Levels of bioluminescence from in vivo and ex vivo images corresponded to the frequency and size of metastatic lesions in lungs and lymph nodes as subsequently confirmed by histology. In summary, BLI provided rapid, non-invasive monitoring of tumor growth and regression in animals. Its application to traditional oncology animal models offers quantitative and sensitive analysis of tumor growth and metastasis. The ability to temporally assess tumor development and responses to drug therapies in vivo also improves upon current standard animal models that are based on single end point data.