Molecular Validation of PACE4 as a Target in Prostate Cancer
Bibliographic record
Abstract
Prostate cancer remains the single most prevalent cancer in men. Standard therapies are still limited and include androgen ablation that initially causes tumor regression. However, tumor cells eventually relapse and develop into a hormone-refractory prostate cancer. One of the current challenges in this disease is to define new therapeutic targets, which have been virtually unchanged in the past 30 years. Recent studies have suggested that the family of enzymes known as the proprotein convertases (PCs) is involved in various types of cancers and their progression. The present study examined PC expression in prostate cancer and validates one PC, namely PACE4, as a target. The evidence includes the observed high expression of PACE4 in all different clinical stages of human prostate tumor tissues. Gene silencing studies targeting PACE4 in the DU145 prostate cancer cell line produced cells (cell line 4-2) with slower proliferation rates, reduced clonogenic activity, and inability to grow as xenografts in nude mice. Gene expression and proteomic profiling of the 4-2 cell line reveals an increased expression of known cancer-related genes (e.g., GJA1, CD44, IGFBP6) that are downregulated in prostate cancer. Similarly, cancer genes whose expression is decreased in the 4-2 cell line were upregulated in prostate cancer (e.g., MUC1, IL6). The direct role of PACE4 in prostate cancer is most likely through the upregulated processing of growth factors or through the aberrant processing of growth factors leading to sustained cancer progression, suggesting that PACE4 holds a central role in 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".