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The E2F1/DNMT1 axis is associated with the development of AR negative castration resistant prostate cancer

By Conrad David Valdez, Lakshmi Kunju, Stephanie Daignault, Kirk J. Wojno and Mark L. Day

Abstract

BACKGROUND Research on castration resistant prostate cancer (CRPC) has focused primarily on functional alterations of the androgen receptor (AR). However, little is known about the loss of AR gene expression itself and the possible contribution of AR negative cells to CRPC. METHODS Human and murine prostate cancer tissue microarrays (TMAs) were evaluated with antibodies specific for E2F1, DNA methyltransferase 1 or AR. The human prostate cancer TMA consisted of clinical samples ranging from normal tissue to samples of metastatic disease. The murine TMA was comprised of benign, localized or metastatic prostate cancer acquired from TRAMP mice treated with castration and/or 5′‐Aza‐2′‐deoxycytidine (5Aza). RESULTS Immunohistochemical analysis revealed increased nuclear DNMT1 staining in localized PCa ( P  < 0.0001) and metastatic PCa ( P  < 0.0001) compared to normal tissue. Examination of specific diagnoses revealed that Gleason seven tumors exhibited greater nuclear DNMT1 staining than Gleason six tumors ( P  < 0.05) and that metastatic tissue exhibited greater levels of nuclear DNMT1 than Gleason seven tumors ( P  < 0.01). Evaluation of the murine tissue cores revealed that 8.2% and 8.1% of benign tissue cores stained positive for E2F1 and DNMT1 respectively, while 97.0% were AR positive. Conversely, 81% and 100% of tumors were positive for E2F1and DNMT1 respectively. This was in stark contrast to only 18% of tumors positive for AR. Treatment of mice with 5Aza reduced DNMT1 staining by 30%, while AR increased by 27%. CONCLUSIONS These findings demonstrate that the E2F1/DNMT1 inhibitory axis of AR transcription is activated during the emergence of CRPC. Prostate 73:1776–1785, 2013 . © 2013 Wiley Periodicals, Inc

Publisher: Wiley Periodicals, Inc.
Year: 2013
DOI identifier: 10.1002/pros.22715
OAI identifier: oai:deepblue.lib.umich.edu:2027.42/100341
Journal:

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