Microsatellite instability and loss of PTEN expression in early versus late-stage endometrial cancer: Results from studies of the National Cancer Institute of Canada Clinical Trials Group (NCIC-CTG)
Bibliographic record
Abstract
5534 Background: Microsatellite instability (MSI+) and inactivation of the tumor suppressor gene PTEN are implicated in the development of endometrial cancer (EC). The aim of this study was to compare the prognostic value of MSI and PTEN in 2 patient (pt) populations, early stage vs. advanced/recurrent disease. Methods: Archival paraffin embedded tumor from pts with EC enrolled in closed NCIC-CTG studies: stage I/II (EN5) and advanced/recurrent disease(IND 126, 148 and 160) were examined for MSI (BAT 25/26) and for PTEN expression (immunohistochemistry). PTEN and MSI status were correlated with clinicopathologic features and outcome from NCIC-CTG trial databases. Results: 188 pt samples (97 stage I/II;91 advanced/recurrent disease) were examined. Results are available for PTEN in 129 pts and MSI in 166 pts. Overall, 55% were PTEN negative (-) and 19.3% MSI+. 33 (56.9%) pts were PTEN - in EN5 vs. 38 pts (53.5%) IND studies (p = 0.73). Overall, no association was seen between PTEN or MSI status and age, performance status (PS), tumor grade or histology. In univariate analysis, there was a trend towards improved survival (S) in pts with PTEN - EC (HR = 0.61; 95% CI, 0.36 -1.04, p = 0.07), weaker in multivariate analysis (HR = 0.56; 95% CI, 0.26–1.18 p = 0.12). In EN5, PTEN status was not associated with S in uni-or multivariate analyses. In the IND studies there was a trend towards improved S in univariate analysis (HR = 0.57; 95% CI, 0.32–1.06 p = 0.07). More pts were MSI+ in EN5, 23 (27.4%) vs. IND studies, 9 (11%) p = 0.01. In EN5, microsatellite stable (MSS) tumors were associated with a better prognosis in both univariate (HR = 0.18; 95% CI, 0.06–0.51, p < 0.0001) and multivariate analysis (HR = 0.16; 95% CI, 0.05 to 0.5, p < 0.0001). There was no difference in S between pts with MSS vs. MSI+ tumors overall, or in the IND studies. in uni- or multivariate analyses. There was no correlation between MSI and PTEN status overall or in either group of pts. Conclusions: MSI+ tumors are more common, and are associated with a worse prognosis, in early stage EC. There is a trend towards improved S for pts with PTEN- advanced EC. There is no association between PTEN and MSI status. No significant financial relationships to disclose.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".