Mammary cancer initiation and progression studied with magnetic resonance imaging.

INTRODUCTION

Previous work from this laboratory demonstrated that magnetic resonance imaging (MRI) detects early murine mammary cancers and reliably differentiates between in situ and invasive cancer. Based on this previous work, we used MRI to study initiation and progression of murine mammary cancer, and monitor the transition from the in situ to the invasive phase.

METHODS

In total, seven female C3(1) SV40 Tag mice were imaged every two weeks between the ages of 8 to 23 weeks. Lesions were identified on T2-weighted images acquired at 9.4 Tesla based on their morphology and growth rates. Lesions were traced manually on MR images of each slice. Volume of each lesion was calculated by adding measurements from individual slices. Plots of lesion volume versus time were analyzed to obtain the specific growth rate (SGR). The time at which in situ cancers (referred to as 'mammary intraepithelial neoplasia (MIN)') and invasive cancers were first detected; and the time at which in situ cancers became invasive were recorded.

RESULTS

A total of 121 cancers (14 to 25 per mouse) were identified in seven mice. On average the MIN lesions and invasive cancers were first detected when mice were 13 and 18 weeks old, respectively. The average SGR was 0.47 ± 0.18 week(-1) and there were no differences (P >0.05) between mice. 74 lesions had significantly different tumor growth rates before and after ~17 weeks of age; with average doubling times (DT) of 1.88 and 1.27 weeks, respectively. The average DT was significantly shorter (P <0.0001) after 17 weeks of age. However, the DT for some cancers was longer after 17 weeks of age, and about 10% of the cancers detected did not progress to the invasive stage.

CONCLUSIONS

A wide range of growth rates were observed in SV40 mammary cancers. Most cancers transitioned to a more aggressive phenotype at approximately 17 weeks of age, but some cancers became less aggressive. The results suggest that the biology of mammary cancers is extremely heterogeneous. This work is a first step towards use of MRI to improve understanding of factors that control and/or signal the development of aggressive breast cancer.