EphB4 Expression and Biological Significance in Prostate Cancer
Bibliographic record
Abstract
Prostate cancer is the most common cancer in men. Advanced prostate cancer spreading beyond the gland is incurable. Identifying factors that regulate the spread of tumor into the regional nodes and distant sites would guide the development of novel diagnostic, prognostic, and therapeutic targets. The aim of our study was to examine the expression and biological role of EphB4 in prostate cancer. EphB4 mRNA is expressed in 64 of 72 (89%) prostate tumor tissues assessed. EphB4 protein expression is found in the majority (41 of 62, 66%) of tumors, and 3 of 20 (15%) normal prostate tissues. Little or no expression was observed in benign prostate epithelial cell line, but EphB4 was expressed in all prostate cancer cell lines to varying degrees. EphB4 protein levels are high in the PC3 prostate cancer cell line and several folds higher in a metastatic clone of PC3 (PC3M) where overexpression was accompanied by EphB4 gene amplification. EphB4 expression is induced by loss of PTEN, p53, and induced by epidermal growth factor/epidermal growth factor receptor and insulin-like growth factor-I/insulin-like growth factor-IR. Knockdown of the EphB4 protein using EphB4 short interfering RNA or antisense oligodeoxynucleotide significantly inhibits cell growth/viability, migration, and invasion, and induces apoptosis in prostate cancer cell lines. Antisense oligodeoxynucleotide targeting EphB4 in vivo showed antitumor activity in murine human tumor xenograft model. These data show a role for EphB4 in prostate cancer and provide a rationale to study EphB4 for diagnostic, prognostic, and therapeutic applications.
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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".