Nanoscale flow cytometry to distinguish subpopulations of prostate extracellular vesicles in patient plasma
Bibliographic record
Abstract
OBJECTIVE: To determine if prostate-derived extracellular vesicles (EVs) present in patient plasma samples are of exocytotic origin (exosomes) or released by the cell membrane (microparticles/microvesicles). Both malignant and normal prostate cells release two types of EVs into the circulation, exosomes, and microparticles/microvesicles which differ in size, origin, and mode of release. Determining what proportion of prostate-derived EVs are of exosomal versus microparticle/microvesicle EV subtype is of potential diagnostic significance. MATERIALS AND METHODS: Multi-parametric analytical platforms such as nanoscale flow cytometry (nFC) were used to analyze prostate derived extracellular vesicles. Plasmas from prostate cancer (PCa) patient plasmas representing benign prostatic hyperplasia (BPH), low grade prostate cancer (Gleason Score 3 + 3) and high grade prostate cancer (Gleason Score ≥4 + 4) were analyzed for various exosome markers (CD9, CD63, CD81) and a prostate specific tissue marker (prostate specific membrane antigen/PSMA). RESULTS: By using nanoscale flow cytometry, we determine that prostate derived EVs are primarily of cell membrane origin, microparticles/microvesicles, and not all PSMA expressing EVs co-express exosomal markers such as CD9, CD63, and CD81. CD9 was the most abundant exosomal marker on prostate derived EVs (12-19%). There was no trend observed in terms of more PSMA + CD9 or PSMA + CD63 co-expressing EVs versus increasing grade of prostate cancer. CONCLUSION: The majority of prostate derived EVs present in plasmas are from the cell membrane as evidenced by their size and most importantly, lack of co-expression of exosomal markers such as CD9/CD63/CD81. In fact, CD81 was not present on any prostate derived EVs in patient plasmas whereas CD9 was present on a minority of prostate derived EVs. The addition of an exosomal marker for detection of prostate-derived EVs does not provide greater clarity in distinguishing EVs released by the prostate.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".