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Preclinical Model of Primary Prostate Cancer

Mar. 25, 2010 — A group led by Dr. Massimo Loda at the Dana Farber Cancer Institute, Boston, MA has developed a preclinical model of human prostate cancer that mimics the genetic and growth behavior of primary tumors.


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Their report can be found in the April 2010 issue of the American Journal of Pathology.

Prostate cancer tends to develop in men over the age of 50 and is one of the most prevalent types of cancer in men. As prostate cancer is often slow-growing and symptom-free, treatment decisions are frequently based on a risk/benefit analysis determined by the underlying health and quality of life concerns of the patient.

Despite earlier detection and treatment of prostate cancer, novel biomarkers are needed to discriminate between aggressive and slow-developing tumors. Priolo et al therefore generated a preclinical model of human prostate cancer that mimics the genetic and growth behavior of primary tumors. In their model, the prostate cancer cells maintained both the histological and genetic characteristics of the parent tumor. In these mice, measurement of prostate-specific antigen levels correlated with tumor engraftment, but not engraftment of normal prostate tissue. Thus, this model should provide a platform for biomarker and drug discovery in prostate cancer.

Dr. Loda and colleagues conclude that "the mouse xenograft model that we have established through direct implantation of human primary prostate tumors represents a useful preclinical model for future applications in biological studies aimed at the identification of the most aggressive and possibly recurrent human localized prostate tumors as well as in biomarker discovery."

Priolo C, Agostini M, Vena N, Ligon AH, Fiorentino M, Shin E, Farsetti A, Pontecorvi A, Sicinska E, Loda M: Establishment and Genomic Characterization of Mouse Xenografts of Human Primary Prostate Tumors. Am J Pathol 2010, 176: 1901-1913

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The above story is reprinted from materials provided by American Journal of Pathology, via EurekAlert!, a service of AAAS.

Note: Materials may be edited for content and length. For further information, please contact the source cited above.


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