Magnetic Resonance Imaging Assessment of Carcinogen-induced Murine Bladder Tumors

Summary

Murine bladder tumors are induced with the N-butyl-N-(4-hydroxybutyl) nitrosamine carcinogen (BBN). Bladder tumor generation is heterogeneous; therefore, an accurate assessment of tumor burden is needed before randomization to experimental treatment. Here we present a fast, reliable MRI protocol to assess tumor size and stage.

Abstract

Murine bladder tumor models are critical for the evaluation of new therapeutic options. Bladder tumors induced with the N-butyl-N-(4-hydroxybutyl) nitrosamine (BBN) carcinogen are advantageous over cell line-based models because they closely replicate the genomic profiles of human tumors, and, unlike cell models and xenografts, they provide a good opportunity for the study of immunotherapies. However, bladder tumor generation is heterogeneous; therefore, an accurate assessment of tumor burden is needed before randomization to experimental treatment. Described here is a BBN mouse model and protocol to evaluate bladder cancer tumor burden in vivo using a fast and reliable magnetic resonance (MR) sequence (true FISP). This method is simple and reliable because, unlike ultrasound, MR is operator-independent and allows for the straightforward post-acquisition image processing and review. Using axial images of the bladder, analysis of regions of interest along the bladder wall and tumor allow for the calculation of bladder wall and tumor area. This measurement correlates with ex vivo bladder weight (r_s= 0.37, p = 0.009) and tumor stage (p = 0.0003). In conclusion, BBN generates heterogeneous tumors that are ideal for evaluation of immunotherapies, and MRI can quickly and reliably assess tumor burden prior to randomization to experimental treatment arms.

Introduction

Bladder cancer is the fifth most common cancer overall, responsible for approximately 80,000 new cases and 16,000 deaths in the United States in 2017¹. After about 30 years without significant advances in the systemic treatment of bladder cancer², recent anti-PD-1 and anti-PD-L1 checkpoint inhibitor trials have demonstrated exciting and occasionally durable responses in patients with advanced urothelial carcinoma^3,4,5. However, only approximately 20% of patients show an objective response to these treatments, and further studies....

Protocol

All methods described here have been approved by the Institutional Animal Care and Use Committee (IACUC) of Northwestern University.

1. Induction of tumors with BBN

1. Obtain male C57/BL6 mice, each at least 6 weeks old.
   NOTE: Male mice develop bladder cancer more quickly and consistently than female mice^14,15.
2. Add N-nitrosobutyl(4-hydroxybutyl) amine (BBN) at a dose of 0.05% to the drinking water. Store it in.......

Discussion

Accurate imaging of tumor models is necessary for appropriate pre-euthanasia staging and animal randomization prior to initiation of experimental treatment. Using the procedure presented here, we demonstrate methodology to (1) generate bladder tumors using the BBN carcinogen and (2) stratify bladder tumor burden through the use of MR. An MR-derived area measurement (BLA_wall) correlates significantly with ex vivo bladder weight and is associated with pathologic tumor stage.

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Materials

Name	Company	Catalog Number	Comments
C57BL/6 mice	The Jackson Laboratory	664	Mice
N-butyl-N-(4-hydroxybutyl)nitrosamine carcinogen (BBN)	TCI American	B0938	Carcinogen
0.9% normal saline	Hospira, Inc	NDC 0409-488-02
Isoflurane	Piramal HealthCare	60307-120-25	Anesthetic
7Tesla ClinScan MRI	Bruker	NA	Dedicated Small Animal Imaging MRI
Syngo	Siemens	NA	MR Integrated Imaging Software
Model 1030 Monitoring & Gating System	Small Animal Instruments, Inc. (SAII)	NA	Small animal physiologic monitoring
Formalin, Neutral Buffered, 10%	Sigma	HT501128	Fixative
Eosin Y	Fisher Scientific	NC1093844	Histologic staining agent
Hematoxylin	Fisher Scientific	23-245651	Histologic staining agent
Jim7	Xinapse Systems	NA	Medical image analysis software
GraphPad Prism v7.04	Graphpad	NA	Graphing software
R v3.4.2	The R Project for Statistical Computing	NA	Statistical software
R package pROC v1.10.0.	The R Project for Statistical Computing	NA	ROC analysis