Association of loss of tumor suppressor ZFP36 with lethal prostate cancer.
Bibliographic record
Abstract
5062 Background: Inflammation has been linked to prostate cancer (PCa) progression which may be mediated by the transcription factor nuclear factor kappa B (NFκB). Using a bioinformatic screen focused on NFκB pathway activation in lethal PCa, we identified the tumor suppressor ZFP36 as a key node of the NFκB network. We also showed in vitro that ZFP36 expression was inversely associated with both NFκB-controlled gene levels and proliferation and sensitivity to enzalutamide. We examined the role of ZFP36 and PCa progression in patient cohorts. Methods: The association between low mRNA expression of ZFP36 (levels in the lower quartile) and lethal PCa (defined as metastatic disease or death) was assessed with logistic regression among men with localized PCa in two independent cohorts treated with radical prostatectomy (RP). The discovery cohort was RP samples from Health Professional Follow-up Study and Physicians Health Study and the validation cohort was RP samples from Cleveland Clinic, Mayo Clinic, Johns Hopkins and MSKCC. In a third cohort from Cornell University, ZFP36 expression levels were assessed in RP samples from patients with localized PCa and biopsies of metastatic castration resistant prostate cancer (mCRPC). Results: Table 1 shows men with localized PCa and lower quartile of tumor ZFP36 expression had a nearly 2-fold higher risk of lethal PCa after adjusting for known clinical and histological prognostic features (age, RP Gleason score, T-stage); an association confirmed in the validation cohort. ZFP36 gene expression was also significantly lower in mCRPC (n=53) compared with a localized RP cohort (n=68) (p-value <0.0001). Conclusions: In humans lower ZFP36 in RP specimens is associated with clinically significant risk of lethal PCa after treatment with curative intent and lower ZFP36levels are found in metastatic tissue. [Table: see text]
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".