A spontaneously metastatic model of bladder cancer: imaging characterization.

Spontaneously metastatic xenograft models of cancer are infrequent and the few that exist are resource intensive. In xenografts, caliper measurements can be used to determine primary tumor burden and response to therapy but in metastatic disease models determination of the presence of metastatic disease, metastatic burden, and response to therapy are difficult, often requiring serial necropsy. In this study we characterized the development of visceral metastases in a patient derived xenograft model (PDXM) using in vivo imaging.

We identified and characterized the previously unreported development of spontaneous liver and bone metastasis in a known patient derived xenograft, bladder xenograft BL0293F, developed by Jackson Laboratories and the University of California at Davis and available from the National Cancer Institute Patient-Derived Models Repository [1]. Among FDG-PET/CT, contrast-enhanced MRI and non-contrast MRI, non-contrast T2w MRI was the most effective and efficient imaging technique. On non-contrast T2 weighted MRI, hepatic metastases were observed in over 70% of animals at 52 days post tumor implantation without resection of the xenograft and in 100% of animals at day 52 following resection of the xenograft. In a group of animals receiving one cycle of effective chemotherapy, no animals demonstrated metastasis by imaging, confirming the utility of this model for therapy evaluation. There was good agreement between pathologic grade and extent of involvement observed on MRI T2w imaging.

PDX BL0293F is a reliable visceral organ (liver) metastatic model with high penetrance in both non-aggravated and post excisional situations, providing a reliable window for therapy intervention prior to required excision of the xenograft. The imaging characteristics of this model are highly favorable for non-clinical research studies of metastatic disease when used in conjunction with non-contrast T2 weighted MRI.

Journal of translational medicine. 2019 Dec 19*** epublish ***

James L Tatum, Joseph D Kalen, Paula M Jacobs, Lilia V Ileva, Lisa A Riffle, Melinda G Hollingshead, James H Doroshow

Cancer Imaging Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institute of Health, Rockville, MD, USA., Small Animal Imaging Program, Frederick National Laboratory for Cancer Research, Frederick, MD, USA., Cancer Imaging Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institute of Health, Rockville, MD, USA. ., Biological Testing Branch, Developmental Therapeutics Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institute of Health, Frederick, MD, USA., Division of Cancer Treatment and Diagnosis, and Center for Cancer Research, National Cancer Institute, National Institute of Health, Rockville, MD, USA.