Unraveling the Prognostic Significance of BRCA1-Associated Protein 1 (BAP1) Expression in Advanced and Castrate-Resistant Prostate Cancer
Bibliographic record
Abstract
Prostate cancer (PCa) is ranked as one of the top cancers affecting men in Western societies. BRCA1-associated protein 1 (BAP1) expression significance has been observed in various cancers, including prostate cancer. The search for prognostic models allowing better risk stratification and prediction of disease progression in prostate cancer patients is still of major clinical need. Our data showed that nuclear BAP1 expression is the most associated with cancer clinical outcomes and other biomarkers. The data confirmed that decreased BAP1 nuclear expression is linked to aggressive tumors and poorer prognosis. We assessed BAP1 expression in 202 cases, including advanced and castrate-resistant PCa (CRPCa). Our data indicated low BAP1 nuclear expression in advanced and castrate-resistant disease (CRPCa). Furthermore, there was a significant difference between high and low BAP1 nuclear expression relative to the patient’s clinical outcome. In the present cohort, decreased BAP1 intensity exhibited a significant association with unfavorable overall survival (OS) (HR 2.31, CI: 1.38–3.86, p = 0.001) and cause-specific survival (CSS) (HR 2.44, CI: 1.24–4.78, p = 0.01). Additionally, this association was more pronounced when low BAP1 expression (high risk) was combined with other common PCa genomic alterations such as phosphatase and tensin homolog (PTEN) loss or ETS-related gene (ERG)-positive cases, resulting in higher unfavorable OS and CSS. Conversely, high BAP1 nuclear expression (moderate and high intensity) combined with no ERG expression or PTEN (moderate or high expression), p53 (wild type), and androgen receptor (AR) (low/moderate intensity) showed better association with higher survival rates. All these data support the notion that BAP1 functions as a tumor suppressor. Integrating BAP1 status with other genomic alterations offers a more comprehensive understanding of disease aggressiveness.
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 | 0.000 | 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) | 0.000 | 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".