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Usage Information

Targeting castration-resistant prostate cancer with androgen receptor antisense oligonucleotide therapy
Marco A. De Velasco, Yurie Kura, Kazuko Sakai, Yuji Hatanaka, Barry R. Davies, Hayley Campbell, Stephanie Klein, Youngsoo Kim, A. Robert MacLeod, Koichi Sugimoto, Kazuhiro Yoshikawa, Kazuto Nishio, Hirotsugu Uemura
Marco A. De Velasco, Yurie Kura, Kazuko Sakai, Yuji Hatanaka, Barry R. Davies, Hayley Campbell, Stephanie Klein, Youngsoo Kim, A. Robert MacLeod, Koichi Sugimoto, Kazuhiro Yoshikawa, Kazuto Nishio, Hirotsugu Uemura
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Research Article Endocrinology Therapeutics

Targeting castration-resistant prostate cancer with androgen receptor antisense oligonucleotide therapy

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Abstract

Sustained therapeutic responses from traditional and next-generation antiandrogen therapies remain elusive in clinical practice due to inherent and/or acquired resistance resulting in persistent androgen receptor (AR) activity. Antisense oligonucleotides (ASO) have the ability to block target gene expression and associated protein products and provide an alternate treatment strategy for castration-resistant prostate cancer (CRPC). We demonstrate the efficacy and therapeutic potential of this approach with a Generation-2.5 ASO targeting the mouse AR in genetically engineered models of prostate cancer. Furthermore, reciprocal feedback between AR and PI3K/AKT signaling was circumvented using a combination approach of AR-ASO therapy with the potent pan-AKT inhibitor, AZD5363. This treatment strategy effectively improved treatment responses and prolonged survival in a clinically relevant mouse model of advanced CRPC. Thus, our data provide preclinical evidence to support a combination strategy of next-generation ASOs targeting AR in combination with AKT inhibition as a potentially beneficial treatment approach for CRPC.

Authors

Marco A. De Velasco, Yurie Kura, Kazuko Sakai, Yuji Hatanaka, Barry R. Davies, Hayley Campbell, Stephanie Klein, Youngsoo Kim, A. Robert MacLeod, Koichi Sugimoto, Kazuhiro Yoshikawa, Kazuto Nishio, Hirotsugu Uemura

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Usage data is cumulative from January 2025 through January 2026.

Usage JCI PMC
Text version 538 133
PDF 145 28
Figure 407 9
Supplemental data 55 8
Citation downloads 142 0
Totals 1,287 178
Total Views 1,465
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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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