Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

In Vivo Models for Prostate Cancer Research

Version 1 : Received: 25 August 2022 / Approved: 26 August 2022 / Online: 26 August 2022 (04:16:25 CEST)

A peer-reviewed article of this Preprint also exists.

Adamiecki, R.; Hryniewicz-Jankowska, A.; Ortiz, M.A.; Li, X.; Porter-Hansen, B.A.; Nsouli, I.; Bratslavsky, G.; Kotula, L. In Vivo Models for Prostate Cancer Research. Cancers 2022, 14, 5321. Adamiecki, R.; Hryniewicz-Jankowska, A.; Ortiz, M.A.; Li, X.; Porter-Hansen, B.A.; Nsouli, I.; Bratslavsky, G.; Kotula, L. In Vivo Models for Prostate Cancer Research. Cancers 2022, 14, 5321.

Abstract

In 2022, prostate cancer (PCa) is estimated to be the most commonly diagnosed cancer in men in the United States – almost 270,000 American men are estimated to be diagnosed with PCa in 2022 [1]. This review compares and contrasts in vivo models of PCa with regards to the altered genes, signaling pathways, and stages of tumor progression associated with each model. The main type of model included in this review are genetically engineered mouse models, which include conditional and constitutive knockout model. 2D cell lines, 3D organoids and spheroids, xenografts and allografts, and patient derived models are also included. The major applications, advantages and disadvantages, and ease of use and cost are unique to each type of model, but they all make it easier to translate the tumor progression that is seen in the mouse prostate to the human prostate. Although both human and mouse prostates are androgen-dependent, the fact that the native, genetically unaltered prostate in mice cannot give rise to carcinoma is an especially critical component of PCa models. Thanks to the similarities between the mouse and human genome, our knowledge of PCa has been expanded, and will continue to do so, through models of PCa.

Keywords

prostate cancer; knockout mouse models; genetically-engineered mouse models; xenografts; patient derived xenografts; organoids; signaling pathways

Subject

Medicine and Pharmacology, Oncology and Oncogenics

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