Characterization of T cell repertoire of blood, tumor, and ascites in ovarian cancer patients using next generation sequencing
Why this work is in the frame
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Bibliographic record
Abstract
Tumor-infiltrating lymphocytes (TILs) play an important role in regulating the host immune response and are one of key factors in defining tumor microenvironment. Some studies have indicated that T cell infiltration in malignant ascites is associated with clinical outcome, but few studies have performed detailed characterization of T cell diversity or clonality in malignant effusions. We have applied a next generation sequencing method to characterize T cell repertoire of a set of primary cancers, ascites, and blood from 12 ovarian cancer patients and also analyzed the T cell subtype populations in malignant fluids from 3 ovarian cancer patients. We observed enrichment of certain T cells in tumors and ascites, but most of the enriched T cell receptor (TCR) sequences in tumors and ascites were not common. Moreover, we analyzed TCR sequences of T cell subtypes (CD4+, CD8+, and regulatory T cells) isolated from malignant effusions and also found clonal expansion of certain T cell populations, but the TCR sequences were almost mutually exclusive among the three subgroups. Although functional studies of clonally expanded T cell populations are definitely required, our approach offers a detailed characterization of T cell immune microenvironment in tumors and ascites that might differently affect antitumor immune response.
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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 | 0.000 | 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) | 0.000 | 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 it