L1CAM further stratifies endometrial carcinoma patients with no specific molecular risk profile
Bibliographic record
Abstract
BACKGROUND: The newly developed Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE) has consistently been shown to be prognostically significant in endometrial carcinomas (EC). Recently, we and others have demonstrated L1 cell-adhesion molecule (L1CAM) to be a significant indicator of high-risk disease in EC. In the current study, it was our aim to determine the prognostic significance of aberrant L1CAM expression in ProMisE subgroups in a large, single centre, population-based EC cohort. METHODS: ProMisE (POLE; MMR-D; p53 wt/NSMP; p53 abn) classification results from a cohort of 452 EC were available for analysis. L1CAM expression was studied by immunohistochemistry on whole slides. Correlations between clinicopathological data and survival were calculated. RESULTS: Expression of L1CAM was most frequent in p53 abnormal tumours (80%). L1CAM status was predictive of worse outcome among tumours with no specific molecular profile (p53 wt/NSMP) (p < 0.0001). Among p53 wt/NSMP EC, L1CAM remained a significant prognosticator for disease-specific survival after multivariate analysis (p = 0.035). CONCLUSION: L1CAM status was able to significantly stratify risk among tumours of the large p53 wt/NSMP ProMisE subgroup of EC. Furthermore, our study confirms a highly significant correlation between mutation-type p53 immunostaining and abnormal L1CAM expression in EC.
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) | 0.001 | 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 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".