Validation of stem cell markers in clinical prostate cancer: α6-Integrin is predictive for non-aggressive disease
Bibliographic record
Abstract
BACKGROUND: Stem cells are postulated to mediate prostate cancer progression, and represent a small fraction of the entire tumor. Various proteins (α2-integrin, α6-integrin, CD117, CD133, EZH2, OCT3/4) are associated with a prostate cancer stem cell phenotype in cell lines and xenografts. Our objective was to investigate expression of stem cell markers in clinical prostate cancer in relation to outcome. METHODS: We validated immunohistochemical expression of stem cell markers in 481 prostate cancer patients and correlated expression with clinicopathologic parameters. RESULTS: Sporadic expression of α2-integrin was present in a fraction of tumor cells (<5%) in 94.7% of tumors and associated with PSA > 10 ng/ml (P = 0.04). α6-Integrin expression (<5%) occurred in 28.4% patients, while ≥5% α6-integrin expression was associated with PSA≤10 ng/ml (P = 0.01), Gleason score <7 (P < 0.01) and pT2-disease (P = 0.02). α6-integrin was predictive for biochemical recurrence (P < 0.01), local recurrence (P = 0.03) and disease specific death (P = 0.03). EZH2 expression was generally low with 2.6% of tumors showing ≥1% positive cells. EZH2 was associated with Gleason score ≥7 (P = 0.01) and biochemical recurrence (P = 0.01). We did not identify expression of CD117, CD133, and OCT3/4 in prostate cancer samples. CONCLUSIONS: Expression of α2-integrin and EZH2 in a small fraction of prostate cancer cells is supportive for their role as stem cell marker. Although α6-integrin was not a unique stem cell marker, it was predictive for prostate cancer biochemical and local recurrence, and disease specific death. The validity of CD117, CD133, and OCT3/4 as prostate cancer stem cell marker is questionable since these proteins were not expressed in clinical 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".