PD-1 and CD103 Are Widely Coexpressed on Prognostically Favorable Intraepithelial CD8 T Cells in Human Ovarian Cancer
Bibliographic record
Abstract
αE(CD103)β7 is a TGFβ-regulated integrin that mediates retention of lymphocytes in peripheral tissues by binding to E-cadherin expressed on epithelial cells. We recently reported that αE(CD103)β7 specifically demarcates intraepithelial CD8(+) tumor-infiltrating lymphocytes (CD8 TIL) in ovarian cancer and that CD103(+) TIL have a surface profile consistent with an active effector phenotype (HLA-DR(+), Ki67(+), and CD127(lo)). These findings led us to hypothesize that, over time, CD103-mediated retention of CD8 TIL within the tumor epithelium might result in chronic stimulation by tumor antigen, which in turn might lead to an exhausted phenotype. To investigate this possibility, we evaluated PD-1 expression in a large cohort of ovarian tumors (N = 489) with known CD103(+) TIL content. PD-1(+) cells were present in 38.5% of high-grade serous carcinomas (HGSC), but were less prevalent in other histologic subtypes. PD-1(+) TIL were strongly associated with increased disease-specific survival in HGSC (HR, 0.4864; P = 0.0007). Multicolor immunohistochemistry and flow cytometry revealed a high degree of PD-1 and CD103 coexpression, specifically within the CD8 TIL compartment. PD-1(+)CD103(+) CD8 TIL were quiescent when assessed directly ex vivo yet were capable of robust cytokine production after pharmacologic stimulation. Moreover, they showed negligible expression of additional exhaustion-associated markers, including TIM-3, CTLA-4, and LAG-3. Thus, as hypothesized, CD103(+) CD8 TIL express PD-1 and appear quiescent in the tumor microenvironment. However, these cells retain functional competence and demonstrate strong prognostic significance. We speculate that, after standard treatment, PD-1(+)CD103(+) CD8 TIL might regain functional antitumor activity, an effect that potentially could be augmented by immune modulation.
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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".