The PDL1-PD1 Axis Converts Human T <sub>H</sub> 1 Cells into Regulatory T Cells
Why this work is in the frame
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Bibliographic record
Abstract
Immune surveillance by T helper type 1 (T(H)1) cells is not only critical for the host response to tumors and infection, but also contributes to autoimmunity and graft-versus-host disease (GVHD) after transplantation. The inhibitory molecule programmed death ligand 1 (PDL1) has been shown to anergize human T(H)1 cells, but other mechanisms of PDL1-mediated T(H)1 inhibition such as the conversion of T(H)1 cells to a regulatory phenotype have not been well characterized. We hypothesized that PDL1 may cause T(H)1 cells to manifest differentiation plasticity. Conventional T cells or irradiated K562 myeloid tumor cells overexpressing PDL1 converted TBET(+) T(H)1 cells into FOXP3(+) regulatory T (T(reg)) cells in vivo, thereby preventing human-into-mouse xenogeneic GVHD (xGVHD). Either blocking PD1 expression on T(H)1 cells by small interfering RNA targeting or abrogation of PD1 signaling by SHP1/2 pharmacologic inhibition stabilized T(H)1 cell differentiation during PDL1 challenge and restored the capacity of T(H)1 cells to mediate lethal xGVHD. PD1 signaling therefore induces human T(H)1 cells to manifest in vivo plasticity, resulting in a T(reg) phenotype that severely impairs cell-mediated immunity. Converting human T(H)1 cells to a regulatory phenotype with PD1 signaling provides a potential way to block GVHD after transplantation. Moreover, because this conversion can be prevented by blocking PD1 expression or pharmacologically inhibiting SHP1/2, this pathway provides a new therapeutic direction for enhancing T cell immunity to cancer and infection.
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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 | 0.001 | 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 | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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