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Usage Information

Molecular determinants of response to high-dose androgen therapy in prostate cancer
Michael D. Nyquist, Alexandra Corella, Osama Mohamad, Ilsa Coleman, Arja Kaipainen, Daniel A. Kuppers, Jared M. Lucas, Patrick J. Paddison, Stephen R. Plymate, Peter S. Nelson, Elahe A. Mostaghel
Michael D. Nyquist, Alexandra Corella, Osama Mohamad, Ilsa Coleman, Arja Kaipainen, Daniel A. Kuppers, Jared M. Lucas, Patrick J. Paddison, Stephen R. Plymate, Peter S. Nelson, Elahe A. Mostaghel
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Research Article Genetics Oncology

Molecular determinants of response to high-dose androgen therapy in prostate cancer

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Abstract

Clinical trials of high-dose androgen (HDA) therapy for prostate cancer (PC) have shown promising efficacy but are limited by lack of criteria to identify likely responders. To elucidate factors that govern the growth-repressive effects of HDAs, we applied an unbiased integrative approach using genetic screens and transcriptional profiling of PC cells with or without demonstrated phenotypic sensitivity to androgen-mediated growth repression. Through this comprehensive analysis, we identified genetic events and related signaling networks that determine the response to both HDA and androgen withdrawal. We applied these findings to develop a gene signature that may serve as an early indicator of treatment response and identify men with tumors that are amenable to HDA therapy.

Authors

Michael D. Nyquist, Alexandra Corella, Osama Mohamad, Ilsa Coleman, Arja Kaipainen, Daniel A. Kuppers, Jared M. Lucas, Patrick J. Paddison, Stephen R. Plymate, Peter S. Nelson, Elahe A. Mostaghel

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Usage data is cumulative from February 2025 through February 2026.

Usage JCI PMC
Text version 1,240 198
PDF 191 32
Figure 675 0
Supplemental data 143 15
Citation downloads 121 0
Totals 2,370 245
Total Views 2,615
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Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

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