Isolation of Human Prostatic Epithelial Plasma Membranes for Proteomics Using Mirror Image Tissue Banking of Radical Prostatectomy Specimens
Bibliographic record
Abstract
PURPOSE: To isolate human prostatic epithelial plasma membranes for the identification of cell surface proteins in the therapeutic targeting of cancer cells while permitting the retrieval of banked samples for clinical purposes. EXPERIMENTAL DESIGN: Radical prostatectomies from 84 patients (median, 61 years; prostate-specific antigen, 5.9; 66% nonpalpable) were processed with alternate, mirror image slices submitted for histology and tissue banking. Benign and malignant foci were macrodissected from the banked sections using the pathologically mapped, mirror image histology sections as a guide. Epithelial plasma membranes were isolated using novel immunomagnetic purification and their purity was assessed. Tissue homogenates were probed by Western blot for malignant (AMACR) and benign (p63) markers to test the accuracy of this protocol. Selected banked tissue slices were retrieved, thawed, and compared pathologically to their corresponding routinely processed alternate slices. RESULTS: Plasma membrane preparations showed the enrichment of epithelial plasma membrane markers (prostate-specific membrane antigen and epithelial-specific antigen) with minimal marker expression from nonepithelial cells or intracellular organelles. Cancer homogenates showed up-regulated AMACR and down-regulated p63, whereas benign homogenates showed up-regulated p63 and down-regulated AMACR. There was 30% benign (p63+) contamination in cancer slices and <6% cancer (AMACR+) contamination in benign slices. Retrieved tissues showed the retention of immunoreactivity while their histology was always adequate for diagnosis. CONCLUSIONS: We have successfully isolated purified epithelial plasma membranes from benign and malignant human prostates and provided validation data for the accuracy of our protocol in a prostate-specific antigen-screened cohort. Our method also enabled the retrieval of banked tissues for clinical purposes with the retention of good histologic and immunohistochemical quality.
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.
How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".