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MGI Accession ID: MGI:1298147
J Number: J:50294
Other Accession IDs: Title: Longitudinal cohort analysis of lethal prostate cancer progression in transgenic mice.
Authors: Hsu CX; Ross BD; Chrisp CE; Derrow SZ; Charles LG; Pienta KJ; Greenberg NM; Zeng Z; Sanda MG
Journal: J Urol
Volume: 160
Issue: 4
Date: 1998 Oct
Year: 1998
Pages: 1500-5
Review Status: Peer Reviewed

Abstract:

PURPOSE: Human prostate cancer is variably lethal, shows heterogeneous progression, and exhibits a spectrum of histopathology. Traditional rodent models of prostate cancer lack these characteristics. An alternative, autochthonous model of prostate cancer consists of transgenic mice which develop prostate cancer due to prostatic expression of SV40 T antigen. Lethal progression of such cancers in individual mice has not been previously characterized. Studies were undertaken to characterize the longitudinal progression of prostate cancers in these transgenic mice. METHODS: A prospective longitudinal cohort study was undertaken to characterize prostate cancer volume, progression, lethality, and histological heterogeneity in a transgenic mouse model of prostatic adenocarcinoma. Fifty-one transgenic mice were followed prospectively to determine the age at onset of palpable tumor and age at cancer-related death. Tumor volume was followed longitudinally by magnetic resonance imaging (MRI) in a subset of these mice and lethal cancers were evaluated by histopathology. RESULTS: Primary tumors became palpable at 10-38 weeks of age. Palpable tumors always preceded lethal progression. Cancer death followed 2-9 weeks later, and age at cancer death varied from 24 to 39 weeks of age. The histopathological changes were heterogeneous. Primary tumors were detectable by MRI before they became detectable by palpation. MRI showed that, analogous to human prostate cancers, volume of early stage primary tumors did not necessarily predict age at cancer death. CONCLUSION: Prostate cancer in transgenic mice mimics heterogeneic tumor progression in human prostate cancer, providing a uniquely relevant pre-clinical model. Tumor detection by MRI and palpation are valid surrogate measures of tumor progression in this model.

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