CD16a <sup>high</sup> NK cell infiltration and spatial relationships with T cells and macrophages can predict improved progression-free survival in high grade ovarian cancer
Bibliographic record
Abstract
ABSTRACT Background High grade serous cancer (HGSC) remains a highly fatal malignancy with less than 50% of patients surviving 5 years after diagnosis. Despite its high mutational burden, HGSC is relatively refractory to checkpoint immunotherapy, suggesting that additional features of the cancer and its interactions with the immune system remain to be understood. Natural killer (NK) cells may contribute to HGSC control, but the role(s) of this population or its subsets in this disease are poorly understood. Methods We used a TMA containing duplicate treatment-naïve tumors from 1145 patients with HGSC and a custom staining panel to simultaneously measure macrophages, T cells and NK cells, separating NK cells based on CD16a expression. Using pathologist-validated digital pathology, machine learning, computational analysis and Pearson’s correlations, we quantitated infiltrating immune cell density, co-infiltration and co-localization with spatial resolution to tumor region. We compared the prognostic value of innate, general, and adaptive immune cell “neighborhoods” to define characteristics of HGSC tumors predictive for progression-free survival and used flow cytometry to define additional features of the CD16a dim NK cell subset. Results NK cells were observed in >95% of tumor cores. Intrastromal localization of CD16a low and CD16a high NK cells was associated with shorter and longer progression-free survival, respectively. CD16a high NK cells most frequently co-localized with T cells and macrophages; their proximity was termed an “adaptive” neighborhood. We find that tumors with more area represented by adaptive immune cell neighborhoods corresponded to superior progression free survival. In contrast, CD16a low NK cells did not co-infiltrate with other immune cell types, and expressed the ectonucleotidases, CD39 and CD73, which have been previously associated with poor prognosis in patients with HGSC. Conclusions Progression-free survival for patients with HGSC may be predicted by the subset of NK cells within the tumor infiltrate (i.e. CD16a high vs. CD16a low ). NK cell subtypes were associated predictable co-infiltrating and co-localizing leukocyte subsets, suggesting that their presence and activity may influence, or be influenced by the tumor microenvironment. Our data suggest that immunotherapeutic strategies for HGSC should consider the constitution of NK cell subsets and may benefit from mobilizing and activating CD16 high NK cells.
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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) | 0.001 | 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".