Endometrial carcinoma and immune escape: prognostic relevance of <scp>HLA</scp> class I loss in <scp>NSMP</scp> subtype
Bibliographic record
Abstract
AIMS: This study aims to define and characterize human leukocyte antigen class I (HLA-I) expression in a consecutive series of molecularly classified endometrial carcinomas (ECs), and to evaluate its association with clinicopathologic features, spatial cancer-immune phenotypes and patient prognosis, with a focus on the NSMP (no specific molecular profile) subtype. METHODS AND RESULTS: HLA-I expression was assessed by immunohistochemistry on whole tissue sections from 208 ECs, classified into POLE-mutated, MMR-deficient (MMRd), p53-abnormal (p53abn) and NSMP subtypes. Loss of HLA-I was identified in 31% of cases and was associated with adverse features including high-grade, aggressive histotypes, deep myometrial invasion, substantial lymphovascular space invasion (LVSI), extensive tumour necrosis and an 'excluded' immune phenotype. While HLA-I loss showed no significant prognostic impact in POLE, MMRd or p53abn tumours, it significantly correlated with worse disease-free survival in NSMP tumours (P < 0.001). Multivariate analysis confirmed HLA-I loss as an independent prognostic factor in early-stage NSMP ECs, in addition to substantial LVSI, presence of lymph node metastases and spatial cancer-immune phenotypes. Integration of HLA-I status improved the performance of predictive models over time. CONCLUSIONS: HLA-I loss defines a biologically aggressive subgroup within NSMP ECs and is associated with adverse clinicopathologic and immune features. Assessment of HLA-I expression could refine risk stratification in NSMP ECs, a group traditionally lacking robust prognostic markers and may help identify patients who could benefit from intensified clinical surveillance and future immunomodulatory treatment strategies.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".