Immune-molecular interactions in high-grade serous ovarian cancer distinguish long-term survivors
Bibliographic record
Abstract
The approach and efficacy of treatments for high-grade serous carcinoma (HGSC) of the ovary have changed little in decades. Although numerous studies demonstrated immune infiltration as frequent and prognostically beneficial, clinical trials of immunotherapies have generated benefit in fewer than 15% of patients. In this issue of the JCI, Nelson and colleagues compiled 1,233 HGSC samples from patients across four continents and compared the molecular and immunologic features that associate with long-term survival (greater than 10 years). Diversity among HGSC tumors is well defined, but this study explored the combined influence of immunologic and molecular features. Long-term survivors harbored tumors with high epithelial content and overrepresentation of the C4/differentiated molecular signature, with cytotoxic T and B cells infiltrating to the tumor epithelium and stroma, respectively. These findings highlight features that might underly poor responsiveness to existing immunotherapies of most HGSC tumors and considerations for the design of future, more precise treatments for HGSC.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".