Mesothelin Expression in Patients with High-Grade Serous Ovarian Cancer Does Not Predict Clinical Outcome But Correlates with CD11c+ Expression in Tumor
Bibliographic record
Abstract
INTRODUCTION: Mesothelin (MSLN) is overexpressed in several tumors including ovarian cancer and is the target of current trials. There is limited and conflicting data on MSLN prognostic impact in ovarian cancer. METHODS: We performed a retrospective study on patients with high-grade serous ovarian cancer, analyzing MSLN expression by immunohistochemistry and examining the correlation of its expression to overall and progression-free survival. Correlations of expression of MSLN, CD8, and macrophage markers in different tumor compartments were also investigated. RESULTS: Positive MSLN expression was detected in 55.1% of primary tumors and 51.5% of the metastases. MSLN expression was not correlated with survival. We observed a significant positive correlation (r = 0.34, p = 0.01) between MSLN expression in the metastatic site and CD11c expression in total tumor area and perivascular area in the primary tumor. CONCLUSION: cells on immunotherapy outcome should be further explored.
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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 | 0.000 | 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) | 0.002 | 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".