CD8+CD28+PD1− T Cells as a Prognostic Biomarker in Endometrial Cancer
Bibliographic record
Abstract
Endometrial cancer (EC) is an immunogenic tumor, with CD8+ T cells playing a pivotal role in antitumor immunity. Overexpression of PD1 suppresses T cell function by inhibiting CD28, a critical co-stimulatory molecule. Classifying CD8+ T cells based on PD1 and CD28 expression provides valuable insights into the immune microenvironment of EC. Peripheral blood samples from 120 EC patients and tumor tissue samples from 81 EC patients were analyzed via flow cytometry. CD8+ T cells were categorized according to PD1 and CD28 expression, and their associations with clinical characteristics were systematically evaluated. Peripheral CD28−/CD8+ and PD1+/CD8+ T cell proportions were significantly associated with several high-risk factors, including deep myometrial invasion, and LVSI, as well as metabolic disorders such as dyslipidemia. Peripheral CD28+PD1−/CD8+ T cells were associated with stage, grade, and LVSI, inversely correlated with age, and elevated in patients with hypertension or dyslipidemia. Tumor-infiltrating CD28+PD1−/CD8+ T cells were associated with tumor grade and LVSI, with multivariate analysis identifying low proportions as an independent predictor of relapse. In summary, CD8+CD28− and CD8+PD1+ T cells are linked to high-risk clinical features in EC, while tumor-infiltrating CD8+CD28+PD1− T cells serve as a key independent prognostic marker for relapse. Additionally, CD8+CD28−, CD8+PD1+, and CD8+CD28+PD1− T cell proportions in PBMC are closely associated with metabolic disorders, emphasizing their potential as biomarkers for immune and metabolic interactions in EC.
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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 | 0.001 | 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 | 0.000 | 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".