Molecular Subtype Not Immune Response Drives Outcomes in Endometrial Carcinoma
Bibliographic record
Abstract
Abstract Purpose: Tumors with high mutation load are thought to engender stronger immune responses, which in turn promote prolonged patient survival. To investigate this, we assessed tumor-infiltrating lymphocytes (TILs) and immunosuppressive factors across the 4 molecular subtypes of endometrial cancer, which have characteristic mutation rates ranging from low to ultra-high. Experimental Design: A total of 460 endometrial cancers were stratified by ProMisE (Proactive Molecular Risk Classifier in Endometrial cancer) into 4 molecular subtypes: mismatch repair-deficient (MMRd), POLE mutant (POLE), p53 abnormal (p53abn), and p53 wild-type (p53wt). Immune markers (CD3, CD8, CD79a, CD138, PD-1, PD-L1, FoxP3, IDO-1) were quantified by multiplex IHC and tested for associations with ProMisE subtype, survival, and other clinicopathologic parameters. Results: Two major TIL patterns were observed. TILhigh tumors harbored dense T- and B-lineage infiltrates and multiple immunosuppressive features and were common in molecular subtypes associated with high mutation load (MMRd and POLE); however, equally strong responses were seen in significant numbers of p53abn and p53wt tumors, which have characteristically low mutation loads. TILlow tumors were generally devoid of immunologic features and were more prevalent in p53abn and p53wt endometrial cancers, yet were also seen in MMRd and POLE subtypes. In multivariable models involving ProMisE subtype, T-cell markers, and TIL clusters, only ProMisE showed independent prognostic significance. Conclusions: Immune response correlates with endometrial cancer molecular subtype but does not carry independent prognostic significance. Profound variation in immune response is seen across and within endometrial cancer molecular subtypes, suggesting that assessment of immune response rather than molecular subtype may better predict response to immunotherapy. See related commentary by Mullen and Mutch, p. 2366
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".