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Curr Protoc Pharmacol. 2018 Jun;81(1):e39. doi: 10.1002/cpph.39. Epub 2018 Jun 7.

Overview of Genetically Engineered Mouse Models of Prostate Cancer and Their Applications in Drug Discovery.

Author information

1
Experimental Therapeutics Group, Institute of Oncology Research (IOR), Università della Svizzera Italiana (USI), Bellinzona, Switzerland.
2
Prostate Cancer Biology Group, Institute of Oncology Research (IOR), Università della Svizzera Italiana (USI), Bellinzona, Switzerland.
3
Department of Oncology, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland.

Abstract

Prostate cancer (PCa) is the most common malignant visceral neoplasm in males in Western countries. Despite progress made in the early treatment of localized malignancies, there remains a need for therapies effective against advanced forms of the disease. Genetically engineered mouse (GEM) models are valuable tools for addressing this issue, particularly in defining the cellular and molecular mechanisms responsible for tumor initiation and progression. While cell and tissue culture systems are important models for this purpose as well, they cannot recapitulate the complex interactions within heterotypic cells and the tumor microenvironment that are crucial in the initiation and progression of prostate tumors. Limitations of GEM models include resistance to developing invasive and metastatic tumors that resemble the advanced stages of human PCa. Nonetheless, because genetic models provide valuable information on the human condition that would otherwise be impossible to obtain, they are increasingly employed to identify molecular targets and to examine the efficacy of cancer therapeutics. The aim of this overview is to provide a brief but comprehensive summary of GEM models for PCa, with particular emphasis on the strengths and weaknesses of this experimental approach.

KEYWORDS:

cancer models; genetically engineered mice; pre-clinical models; prostate cancer

PMID:
29927081
DOI:
10.1002/cpph.39
[Indexed for MEDLINE]

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