Abstract

BackgroundExtracellular vesicles released by prostate cancer present in seminal fluid, urine, and blood may represent a non-invasive means to identify and prioritize patients with intermediate risk and high risk of prostate cancer. We hypothesize that enumeration of circulating prostate microparticles (PMPs), a type of extracellular vesicle (EV), can identify patients with Gleason Score≥4+4 prostate cancer (PCa) in a manner independent of PSA.Patients and MethodsPlasmas from healthy volunteers, benign prostatic hyperplasia patients, and PCa patients with various Gleason score patterns were analyzed for PMPs. We used nanoscale flow cytometry to enumerate PMPs which were defined as submicron events (100-1000nm) immunoreactive to anti-PSMA mAb when compared to isotype control labeled samples. Levels of PMPs (counts/μL of plasma) were also compared to CellSearch CTC Subclasses in various PCa metastatic disease subtypes (treatment naïve, castration resistant prostate cancer) and in serially collected plasma sets from patients undergoing radical prostatectomy.ResultsPMP levels in plasma as enumerated by nanoscale flow cytometry are effective in distinguishing PCa patients with Gleason Score≥8 disease, a high-risk prognostic factor, from patients with Gleason Score≤7 PCa, which carries an intermediate risk of PCa recurrence. PMP levels were independent of PSA and significantly decreased after surgical resection of the prostate, demonstrating its prognostic potential for clinical follow-up. CTC subclasses did not decrease after prostatectomy and were not effective in distinguishing localized PCa patients from metastatic PCa patients.ConclusionsPMP enumeration was able to identify patients with Gleason Score ≥8 PCa but not patients with Gleason Score 4+3 PCa, but offers greater confidence than CTC counts in identifying patients with metastatic prostate cancer. CTC Subclass analysis was also not effective for post-prostatectomy follow up and for distinguishing metastatic PCa and localized PCa patients. Nanoscale flow cytometry of PMPs presents an emerging biomarker platform for various stages of prostate cancer.

Highlights

  • A blood/urine based “liquid biopsy” for prostate cancer (PCa) could minimize the iatrogenic effects associated with needle core biopsies [1] and provide more accurate information regarding risk stratification

  • prostate microparticles (PMPs) levels in plasma as enumerated by nanoscale flow cytometry are effective in distinguishing PCa patients with Gleason Score≥8 disease, a highrisk prognostic factor, from patients with Gleason Score≤7 PCa, which carries an intermediate risk of PCa recurrence

  • PMP enumeration was able to identify patients with Gleason Score ≥8 PCa but not patients with Gleason Score 4+3 PCa, but offers greater confidence www.impactjournals.com/oncotarget than circulating tumor cells (CTCs) counts in identifying patients with metastatic prostate cancer

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Summary

Introduction

A blood/urine based “liquid biopsy” for prostate cancer (PCa) could minimize the iatrogenic effects associated with needle core biopsies [1] and provide more accurate information regarding risk stratification. CTCs are rare in localized PCa disease [5], and enumerating circulating TCFs by the CellSearch Instrument [4] or other high-throughput methods may be more appropriate for early stage disease. Known as prostate microparticles, these cell fragments taxonomically fall under the umbrella term, extracellular vesicles (EVs). A high-throughput and multi-parametric method is needed to enumerate prostate microparticles and its associated biomarkers for correlation to clinical outcomes. Extracellular vesicles released by prostate cancer present in seminal fluid, urine, and blood may represent a non-invasive means to identify and prioritize patients with intermediate risk and high risk of prostate cancer. We hypothesize that enumeration of circulating prostate microparticles (PMPs), a type of extracellular vesicle (EV), can identify patients with Gleason Score≥4+4 prostate cancer (PCa) in a manner independent of PSA

Methods
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Conclusion

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