Impact of decitabine on immunohistochemistry expression of the putative tumor suppressor genes FHIT, WWOX, FUS1 and PTEN in clinical tumor samples
Bibliographic record
Abstract
BACKGROUND: Since tumor suppressor gene function may be lost through hypermethylation, we assessed whether the demethylating agent decitabine could increase tumor suppressor gene expression clinically. For fragile histidine triad (FHIT), WW domain-containing oxidoreductase (WWOX), fused in sarcoma-1 (FUS1) and phosphatase and tensin homolog (PTEN), immunohistochemistry scores from pre- and post-decitabine tumor biopsies (25 patients) were correlated with methylation of the long interspersed nuclear element-1 (LINE-1) repetitive DNA element (as a surrogate for global DNA methylation) and with tumor regression. RESULTS: With negative staining pre-decitabine (score = 0), the number of patients converting to positive staining post-decitabine was 1 of 1 for FHIT, 3 of 6 for WWOX, 2 of 3 for FUS1 and 1 of 10 for PTEN. In tumors with low pre-decitabine tumor suppressor gene scores (≤150), expression was higher post-treatment in 8 of 8 cases for FHIT (P = 0.014), 7 of 17 for WWOX (P = 0.0547), 7 of 12 for FUS1 (P = 0.0726), and 1 of 16 for PTEN (P = 0.2034). If FHIT, WWOX and FUS1 were considered together, median pre- versus post-decitabine scores were 60 versus 100 (P = 0.0002). Overall, tumor suppressor gene expression change did not correlate with LINE-1 demethylation, although tumors converting from negative to positive had a median decrease in LINE-1 methylation of 24%, compared to 6% in those not converting (P = 0.069). Five of 15 fully evaluable patients had reductions in tumor diameter (range 0.2% to 33.4%). Of these, three had simultaneous increases in three tumor suppressor genes (including the two patients with the greatest tumor regression) compared to 2 of 10 with tumor growth (P = 0.25). CONCLUSIONS: In tumors with low tumor suppressor gene expression, decitabine may be associated with increased expression of the tumor suppressor genes FHIT, FUS1, and WWOX, but not PTEN.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".