Exosomes as Biomarker Enriched Microvesicles: Characterization of Exosomal Proteins Derived from a Panel of Prostate Cell Lines with Distinct AR Phenotypes
Bibliographic record
Abstract
Prostate cancer is the leading type of cancer diagnosed in men. In 2010, ~217,730 new cases of prostate cancer were reported in the United States. Prompt diagnosis of the disease can substantially improve its clinical outcome. Improving capability for early detection, as well as developing new therapeutic targets in advanced disease are research priorities that will ultimately lead to better patient survival. Eukaryotic cells secrete proteins via distinct regulated mechanisms which are either ER/Golgi dependent or microvesicle mediated. The release of microvesicles has been shown to provide a novel mechanism for intercellular communication. Exosomes are nanometer sized cup-shaped membrane vesicles which are secreted from normal and cancerous cells. They are present in various biological fluids and are rich in characteristic proteins. Exosomes may thus have potential both in facilitating early diagnosis via less invasive procedures or be candidates for novel therapeutic approaches for castration resistance prostate cancer. Because exosomes have been shown previously to have a role in cell-cell communication in the local tumor microenvironment, conferring activation of numerous survival mechanisms, we characterized constitutive lipids, cholesterol and proteins from exosomes derived from six prostate cell lines and tracked their uptake in both cancerous and benign prostate cell lines respectively. Our comprehensive proteomic and lipidomic analysis of prostate derived exosomes could provide insight for future work on both biomarker and therapeutic targets for the treatment of prostate cancer.
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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 | 0.001 | 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 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".