Abstract LB-177: Handling of liquid biopsy samples can dramatically change the numbers of PSMA-positive microparticles
Bibliographic record
Abstract
Abstract The use of PSA as the gold standard for diagnosing prostate cancer (PCa) has been challenged recently and the search for new PCa biomarkers has increased. Although the PSA test has acceptable sensitivity, it lacks the necessary specificity to discriminate benign prostatic diseases, resulting in overdiagnosis and overtreatment. Thus new, more specific biomarkers for PCa are needed to prevent unnecessary surgical biopsies. The development of fluid biopsies which analyze extracellular microvesicles in plasma, urine or semen are an exciting new area of investigation. Extracellular microvesicles are a new, heterogenous group and while the nomenclature is still being defined by the research community, we define microvesicles as submicron vesicles shed from the plasma membrane. These microvesicles can contain mRNA, microRNA, and membrane proteins - any of which are potential sources for new PCa biomarkers. The diagnostic test must differentiate microvesicles originating from PCa cells versus non-cancerous origins, and also define a biomarker which is enriched in this prostate cancer microvesicle (PCMV) population. In our assay, the prostate specific membrane antigen (PSMA) which has been shown to be highly specific for PCa cells, is used. As the microvesicle field is new, no standard methods for specimen isolation, handling or even proper controls for direct comparisons have yet been accepted. Our initial studies examined plasma preparation and storage as a source of variation. Blood was collected from five prostate cancer patients and plasma prepared under different handling conditions; EDTA was used as the anticoagulant in all cases. Microparticles were assessed directly in plasma using the Apogee A50 micro-flow cytometer and the Nanosight LM10, and ranged in size from ∼80-200nm. Matched isotype controls were used for gating purposes. Significantly, fresh, never frozen plasma had dramatically more PSMA positive microparticles than any other treatment group. However, assaying fresh patient plasma is not practical; development of any biomarker assay will utilize retrospective samples, so frozen samples resemble true sample availability. Plasma prepared within 2hrs of collection, aliquoted and frozen at -80C was considered as “control”. Plasma or whole blood stored at RT overnight significantly increased PCMV (ie PSMA+) counts (2-4 fold respectively) compared to control. Whole blood that was stored at 4C for 30 min or overnight also had significantly more PCMVs. Plasma stored at RT for 6hrs or at -20C O/N and then frozen at -80C had similar PCMPs compared to control. In agreement with other published data, isotype controls yielded significant numbers of “positive” microvesicles. The size of vesicles consistently ranged from 80-200nm with a sharp drop off at both ends and a significant peak at ∼90nm. After freezing, the numbers of microvesicles <80nm increased but the sharp cutoff at 200nm remained. Freeze thaw (10x) of the plasma increased microvesicle size to 400nm. In conclusion, the storage and handling of patient plasma can significantly affect the number of microvesicles which stain positive for PSMA and hence be classified as prostate cancer microvesicles. Standardization of processing and handling of patient samples is necessary to be able to assay the effectiveness any potential biomarker for diagnostic value. Citation Format: Desmond B. Pink, Deborah Sosnowski, Robert Paproski, Andries Zijlstra, John D. Lewis. Handling of liquid biopsy samples can dramatically change the numbers of PSMA-positive microparticles. [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 LB-177. doi:10.1158/1538-7445.AM2014-LB-177
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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 | 0.001 |
| 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".