Τετάρτη 5 Ιουλίου 2017

Transdifferentiation as a Mechanism of Treatment Resistance in a Mouse Model of Castration-Resistant Prostate Cancer [Research Articles]

Current treatments for castration-resistant prostate cancer (CRPC) that target androgen receptor (AR) signaling improve patient survival, yet ultimately fail. Here, we provide novel insights into treatment response for the antiandrogen abiraterone by analyses of a genetically engineered mouse (GEM) model with combined inactivation of Trp53 and Pten, which are frequently comutated in human CRPC. These NPp53 mice fail to respond to abiraterone and display accelerated progression to tumors resembling treatment-related CRPC with neuroendocrine differentiation (CRPC-NE) in humans. Cross-species computational analyses identify master regulators of adverse response that are conserved with human CRPC-NE, including the neural differentiation factor SOX11, which promotes neuroendocrine differentiation in cells derived from NPp53 tumors. Furthermore, abiraterone-treated NPp53 prostate tumors contain regions of focal and/or overt neuroendocrine differentiation, distinguished by their proliferative potential. Notably, lineage tracing in vivo provides definitive and quantitative evidence that focal and overt neuroendocrine regions arise by transdifferentiation of luminal adenocarcinoma cells. These findings underscore principal roles for TP53 and PTEN inactivation in abiraterone resistance and progression from adenocarcinoma to CRPC-NE by transdifferentiation.

Significance: Understanding adverse treatment response and identifying patients likely to fail treatment represent fundamental clinical challenges. By integrating analyses of GEM models and human clinical data, we provide direct genetic evidence for transdifferentiation as a mechanism of drug resistance as well as for stratifying patients for treatment with antiandrogens. Cancer Discov; 7(7); 736–49. ©2017 AACR.

See related commentary by Sinha and Nelson, p. 673.

This article is highlighted in the In This Issue feature, p. 653



from #ENT-AlexandrosSfakianakis via ola Kala on Inoreader http://ift.tt/2srF341

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