Yinan Li1, Nilgun Donmez2, Cenk Sahinalp2, Ning Xie1, Yuwei Wang3, Hui Xue3, Fan Mo1, Himisha Beltran4, Martin Gleave1, Yuzhuo Wang5, Colin Collins6, Xuesen Dong7. 1. Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, Canada. 2. Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, Canada; School of Computing Science, Simon Fraser University, Burnaby, Canada. 3. Department of Experimental Therapeutics, British Columbia Cancer Agency, Vancouver, Canada. 4. Department of Medicine, Weill Cornell Medicine, New York, NY, USA. 5. Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, Canada; Department of Experimental Therapeutics, British Columbia Cancer Agency, Vancouver, Canada. 6. Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, Canada; School of Computing Science, Simon Fraser University, Burnaby, Canada; Laboratory for Advanced Genome Analysis, Vancouver, Canada. Electronic address: ccollins@prostatecentre.com. 7. Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, Canada. Electronic address: xdong@prostatecentre.com.
Abstract
BACKGROUND: Neuroendocrine prostate cancer (NEPC) is an aggressive subtype of castration-resistant prostate cancer that typically does not respond to androgen receptor pathway inhibition (ARPI), and its diagnosis is increasing. OBJECTIVE: To understand how NEPC develops and to identify driver genes to inform therapy for NEPC prevention. DESIGN, SETTING, AND PARTICIPANTS: Whole-transcriptome sequencing data were extracted from prostate tumors from two independent cohorts: The Beltran cohort contained 27 adenocarcinoma and five NEPC patient samples, and the Vancouver Prostate Centre cohort contained three patient samples and nine patient-derived xenografts. INTERVENTION: A novel bioinformatics tool, comparative alternative splicing detection (COMPAS), was invented to analyze alternative RNA splicing on RNA-sequencing data. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: COMPAS identified potential driver genes for NEPC development. Biochemical and biological validations were performed in both prostate cell and tumor models. RESULTS AND LIMITATION: More than 66% of the splice events were predicted to be regulated by the RNA splicing factor serine/arginine repetitive matrix 4 (SRRM4). In vitro and in vivo evidence confirmed that one SRRM4 target gene was the RE1 silencing transcription factor (REST), a master regulator of neurogenesis. Moreover, SRRM4 strongly stimulated adenocarcinoma cells to express NEPC biomarkers, and this effect was exacerbated by ARPI. ARPI combined with a gain of SRRM4-induced adenocarcinoma cells to assume multicellular spheroid morphology and was essential in establishing progressive NEPC xenografts. These SRRM4 actions were further enhanced by loss of function of TP53. CONCLUSIONS: SRRM4 drives NEPC progression. This knowledge may guide the development of novel therapeutics aimed at NEPC. PATIENT SUMMARY: Using next-generation RNA sequencing and our newly developed bioinformatics tool, we identified a neuroendocrine prostate cancer (NEPC)-specific RNA splicing signature that is predominantly controlled by serine/arginine repetitive matrix 4 (SRRM4). We confirmed that SRRM4 drives NEPC progression, and we propose SRRM4 as a potential therapeutic target for NEPC.
BACKGROUND:Neuroendocrine prostate cancer (NEPC) is an aggressive subtype of castration-resistant prostate cancer that typically does not respond to androgen receptor pathway inhibition (ARPI), and its diagnosis is increasing. OBJECTIVE: To understand how NEPC develops and to identify driver genes to inform therapy for NEPC prevention. DESIGN, SETTING, AND PARTICIPANTS: Whole-transcriptome sequencing data were extracted from prostate tumors from two independent cohorts: The Beltran cohort contained 27 adenocarcinoma and five NEPC patient samples, and the Vancouver Prostate Centre cohort contained three patient samples and nine patient-derived xenografts. INTERVENTION: A novel bioinformatics tool, comparative alternative splicing detection (COMPAS), was invented to analyze alternative RNA splicing on RNA-sequencing data. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: COMPAS identified potential driver genes for NEPC development. Biochemical and biological validations were performed in both prostate cell and tumor models. RESULTS AND LIMITATION: More than 66% of the splice events were predicted to be regulated by the RNA splicing factor serine/arginine repetitive matrix 4 (SRRM4). In vitro and in vivo evidence confirmed that one SRRM4 target gene was the RE1 silencing transcription factor (REST), a master regulator of neurogenesis. Moreover, SRRM4 strongly stimulated adenocarcinoma cells to express NEPC biomarkers, and this effect was exacerbated by ARPI. ARPI combined with a gain of SRRM4-induced adenocarcinoma cells to assume multicellular spheroid morphology and was essential in establishing progressive NEPC xenografts. These SRRM4 actions were further enhanced by loss of function of TP53. CONCLUSIONS:SRRM4 drives NEPC progression. This knowledge may guide the development of novel therapeutics aimed at NEPC. PATIENT SUMMARY: Using next-generation RNA sequencing and our newly developed bioinformatics tool, we identified a neuroendocrine prostate cancer (NEPC)-specific RNA splicing signature that is predominantly controlled by serine/arginine repetitive matrix 4 (SRRM4). We confirmed that SRRM4 drives NEPC progression, and we propose SRRM4 as a potential therapeutic target for NEPC.
Authors: Mark P Labrecque; Ilsa M Coleman; Lisha G Brown; Lawrence D True; Lori Kollath; Bryce Lakely; Holly M Nguyen; Yu C Yang; Rui M Gil da Costa; Arja Kaipainen; Roger Coleman; Celestia S Higano; Evan Y Yu; Heather H Cheng; Elahe A Mostaghel; Bruce Montgomery; Michael T Schweizer; Andrew C Hsieh; Daniel W Lin; Eva Corey; Peter S Nelson; Colm Morrissey Journal: J Clin Invest Date: 2019-07-30 Impact factor: 14.808