PC Cell-Derived Growth Factor Expression in Prostatic Intraepithelial Neoplasia and Prostatic Adenocarcinoma
Bibliographic record
Abstract
PURPOSE: PCDGF (PC cell-derived growth factor), also called progranulin, is a M(r) 88000 glycoprotein precursor of granulin. It is a novel growth factor that stimulates cell proliferation, confers epithelial tumorigenesis, and promotes tumor invasion. Here we investigate the potential of PCDGF as a therapeutic target for prostate cancer. EXPERIMENTAL DESIGN: We studied the expression of PCDGF in invasive prostate cancer, adjacent high-grade prostatic intraepithelial neoplasia (PIN), and benign prostate tissue from 99 human prostate specimens. The level of PCDGF expression was correlated with various clinicopathological characteristics. RESULTS: Normal prostate tissue did not express (53/99), or expressed low levels (46/99) of PCDGF. In the 46 normal prostate specimens that expressed PCDGF, most of them had less than 10% of cells expressing PCDGF. PCDGF expression could be detected in more than 50% of cells in all specimens of PIN and invasive prostate cancer. The expression of PCDGF in normal prostate tissue was much less intense and in a smaller fraction of cells than in PIN and invasive adenocarcinoma (P < 0.0001). There was no correlation of PCDGF expression with age, Gleason score, pathological stage, status of lymph node metastasis, extraprostatic extension, perineural invasion, surgical margins, and vascular invasion. CONCLUSIONS: Our data suggest that the induction of PCDGF expression occurs during the development of PIN. PCDGF may be a new molecular target for the treatment and prevention 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 | 0.000 | 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) | 0.001 | 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".