Abstract 4716: Discovery of biomarkers from highly enriched prostate cancer microparticles for prognostication of prostate cancer
Bibliographic record
Abstract
Abstract Prostate cancer microparticles (PCMPs) are essentially fragments of tumor cells that are present in various bodily fluids such as plasma and urine. By using nanoscale flow cytometry, multiple biomarkers can be assessed on PCMPs in patient plasma, a convenient “fluid biopsy” for prostate cancer (PCa). Discovering biomarkers specific for metastatic PCMPs would establish a non-invasive fluid biopsy for detecting the earliest onset of metastatic disease for patients post-prostatectomy. Discovery of biomarkers specific to Gleason score 6 (3+3) and 8 (4+4) lesions that are decorated on the surface of PCMPs would help establish a non-invasvie fluid biopsy for tumor upstaging (i.e., Gleason 6 to 7) of patients placed on active surveillance who have deferred prostatectomy. We hypothesize that biomarkers specific for metastatic PCMPs or Gleason Score-specific PCMPs can only be discovered via proteomics analysis on highly purified PCMPs from plasmas which have minimal levels of non-target microparticles and plasma proteins. To do this, plasmas were incubated with biotinylated anti-PSMA mAb and PSMA+ve microparticles were isolated from plasma by using a magnetic column after several purification runs. Eluted samples were then submitted to nanoscale flow cytometry in which elution fractions that exhibited minimal non-target microparticle concentrations (<1000 events/uL) were submitted to proteomics analysis. PCMPs from plasma samples representing localized (N=7, lymph node negative, PSA>5 ng/mL, Gleason Score 3+3) and metastatic (N=7, confirmed bone metastases, PSA>10 ng/mL, Gleason 4+4) were isolated, evaluated and submitted for iTRAQ labeling, high pH reversed phase fractionation and LC-MS/MS analysis. All data was analyzed using Proteome Discoverer 1.3 and MASCOT v2.3 software. Mass spectometry analysis revealed 8 proteins significantly upregulated and 5 proteins downregulated in the majority of metastatic plasma samples compared to localized plasma samples. Data was normalized to albumin levels by western blot and mass spectrometry. Based on these results, we have identified 8 proteins that may be specific for a subpopulation of PCMPs from metastatic PCa patients. Out of these, 6 may be candidates for flow cytometry because they are membrane-bound or are cytoskeletal elements potentially exposed to the extracellular space (CLIC1, PVR, YWHAE, KRT16, K1C10, KRT2). Citation Format: Colleen N. Biggs, Quiquan Guo, Jun Yang, Ann F. Chambers, Joseph L. Chin, Nicholas Power, Hon S. Leong. Discovery of biomarkers from highly enriched prostate cancer microparticles for prognostication of prostate cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4716. doi:10.1158/1538-7445.AM2014-4716
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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 | 0.000 | 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) | 0.003 | 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".