Prostate extracellular vesicles in patient plasma as a liquid biopsy platform for prostate cancer using nanoscale flow cytometry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
// Colleen N. Biggs 1,3,* , Khurram M. Siddiqui 1,3,* , Ali A. Al-Zahrani 1,3,7 , Siddika Pardhan 1,3 , Sabine I. Brett 1,3 , Qiu Q. Guo 8 , Jun Yang 8 , Philipp Wolf 6 , Nicholas E. Power 1,2,3 , Paul N. Durfee 5 , Connor D. MacMillan 1,3 , Jason L. Townson 5 , Jeffrey C. Brinker 5 , Neil E. Fleshner 4 , Jonathan I. Izawa 1,2,3 , Ann F. Chambers 2 , Joseph L. Chin 1,2,3 and Hon S. Leong 1,3 1 Department of Surgery, Western University, London, Canada 2 Department of Oncology, Western University, London, Canada 3 Translational Prostate Cancer Research Laboratory, Lawson Health Research Institute, London, Canada 4 University Health Network, University of Toronto, Toronto, Canada 5 Sandia National Laboratories, Albuquerque, NM, USA 6 Department of Urology, University Medical Center Freiburg, Freiburg, Germany 7 Department of Urology, University of Dammam, Dammam, Saudi Arabia 8 Department of Mechanical and Materials Engineering, Western University, London, Canada * These authors have contributed equally to this work Correspondence to: Hon S. Leong, email: // Keywords : prostate microparticles, extracellular vesicles, nanoscale flow cytometry, prostate cancer, liquid biopsy Received : December 28, 2015 Accepted : January 16, 2016 Published : January 22, 2016 Abstract Background: 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. Patients and Methods: Plasmas 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. Results: PMP 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. Conclusions: 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 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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it