Association of tissue promoter methylation levels of <i>APC</i>, <i>TGFβ2</i>, <i>HOXD3</i> and <i>RASSF1A</i> with prostate cancer progression
Bibliographic record
Abstract
Aberrant promoter methylation is known to silence tumor-suppressor genes in prostate cancer (PCa). We correlated quantitative promoter methylation levels of APC, TGFβ2 and RASSF1A in 219 radical prostatectomies diagnosed between 1998 and 2001 with clinicopathological follow-up data available including Gleason Pattern (GP), Gleason Score (GS) and pathological stage and explored their potential in predicting biochemical recurrence using univariate and multivariate analyses. We observed that the average methylation levels of APC increased significantly from GS ≤ 6 to GS7, and pT2 to pT3a, and that of TGFβ2 increased from GS ≤ 6 to GS7, but not for RASSF1A. PCa samples were also stratified into high methylation (HM) and low methylation (LM) groups based on the PMR scores of all cases analyzed for each marker. The HM frequency of APC was greater in pT3a than pT2, and in GS ≥ 8 than GS ≤ 6. The HM frequency also increased significantly from GP3 to GP4 for APC, TGFβ2 and RASSF1A. APC methylation level was a significant predictor of biochemical recurrence in univariate analysis (p-value = 0.028). Finally, we combined methylation data of these three genes with the previously reported novel methylation biomarker HOXD3. Quantitative methylation assessment of a multiplex panel of markers, consisting of APC, HOXD3 and TGFβ2, outperforms any single marker for the prediction of biochemical recurrence (p-value = 0.017). Our study demonstrated that quantitative increase in promoter methylation levels of APC, HOXD3 and TGFβ2 are associated with PCa progression.
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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 | 0.000 | 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".