<i>In-vitro</i> effect of pembrolizumab on different T regulatory cell subsets
Bibliographic record
Abstract
Summary Programmed death-1 (PD-1) and interactions with PD-ligand 1 (PD-L1) play critical roles in the tumour evasion of immune responses through different mechanisms, including inhibition of effector T cell proliferation, reducing cytotoxic activity, induction of apoptosis in tumour-infiltrating T cells and regulatory T cell (Treg) expansion. Effective blockade of immune checkpoints can therefore potentially eliminate these detrimental effects. The aim of this study was to investigate the effect of anti-PD-1 antibody, pembrolizumab, on various Treg subpopulations. Peripheral blood mononuclear cells (PBMC) from healthy donors (HD) and primary breast cancer patients (PBC) were treated in vitro with pembrolizumab, which effectively reduced PD-1 expression in both cohorts. We found that PD-1 was expressed mainly on CD4+CD25+ T cells and pembrolizumab had a greater effect on PD-1 expression in CD4+CD25− T cells, compared to CD4+CD25+ cells. In addition, pembrolizumab did not affect the expression levels of Treg-related markers, including cytotoxic T lymphocyte antigen-4 (CTLA-4), CD15s, latency-associated peptide (LAP) and Ki-67. Moreover, we report that CD15s is expressed mainly on forkhead box P3 (FoxP3)−Helios+ Treg in HD, but it is expressed on FoxP3+Helios− Treg subset in addition to FoxP3−Helios+ Treg in PBC. Pembrolizumab did not affect the levels of FoxP3+/−Helios+/− Treg subsets in both cohorts. Taken together, our study suggests that pembrolizumab does not affect Treg or change their phenotype or function but rather blocks signalling via the PD-1/PD-L1 axis in activated T cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".