Reduced CD5 on CD8+ T Cells in Tumors but Not Lymphoid Organs Is Associated With Increased Activation and Effector Function
Bibliographic record
Abstract
CD5, a member of the scavenger receptor cysteine-rich superfamily, is a marker for T cells and a subset of B cells (B1a). CD5 associates with T-cell and B-cell receptors and increased CD5 is an indication of B cell activation. In tumor-infiltrating lymphocytes (TILs) isolated from lung cancer patients, CD5 levels were negatively correlated with anti-tumor activity and tumor‐mediated activation-induced T cell death, suggesting that CD5 could impair activation of anti-tumor T cells. We determined CD5 levels in T cell subsets in different organs in mice bearing syngeneic 4T1 breast tumor homografts and assessed the relationship between CD5 and increased T cell activation and effector function by flow cytometry. We report that T cell CD5 levels were higher in CD4+T cells than in CD8+T cells in 4T1 tumor-bearing mice, and that high CD5 levels on CD4+T cells were maintained in peripheral organs (spleen and lymph nodes). However, both CD4+and CD8+T cells recruited to tumors had reduced CD5 compared to CD4+and CD8+T cells in peripheral organs. In addition, CD5high/CD4+T cells and CD5high/CD8+T cells from peripheral organs exhibited higher levels of activation and associated effector function compared to CD5low/CD4+T cell and CD5low/CD8+T cell from the same organs. Interestingly, CD8+T cells among TILs and downregulated CD5 were activated to a higher level, with concomitantly increased effector function markers, than CD8+/CD5highTILs. Thus, differential CD5 levels among T cells in tumors and lymphoid organs can be associated with different levels of T cell activation and effector function, suggesting that CD5 may be a therapeutic target for immunotherapeutic activation in cancer therapy.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".