Prognostically favorable immune responses to ovarian cancer are distinguished by self-reactive intra-epithelial plasma cells
Bibliographic record
Abstract
SUMMARY Tumor-infiltrating B cells (TIL-Bs) are strongly associated with patient survival; however, the underlying mechanisms are poorly understood. Using integrated single-cell and spatial biology approaches, we defined at clonal resolution the molecular phenotypes, tumor reactivity patterns, and microenvironmental locations of TIL-Bs in high-grade serous ovarian cancer (HGSC). Prognostic benefit was associated with a TIL-B-rich tumor microenvironment with marked infiltration of malignant epithelium by plasma cells (PCs). PCs spanned five molecular phenotypes; exhibited high rates of somatic hypermutation and clonal expansion; and expressed predominantly IgG1 antibodies recognizing broadly expressed nuclear, cytoplasmic, and cell surface self-antigens. Many PC-derived antibodies were polyreactive. Self- and poly-reactive TIL-Bs penetrated tumor epithelium and stroma and expressed interferon-stimulated genes, indicating strong in situ activation. The self- and poly-reactive nature of TIL-B responses, reminiscent of autoimmune disease, may provide a means for the immune system to combat tumor heterogeneity and could potentially be harnessed for more effective immunotherapy.
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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 | 0.000 |
| 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".