Modulating levels of cell surface CD6 is a novel mechanism for regulating T cell activity.
Bibliographic record
Abstract
Abstract CD6 is a co-stimulatory receptor expressed on the surface of T cells that promotes immune synapse formation, T cell activation, and migration into tissues by engaging its ligand, ALCAM. CD6high cells have been described to be more pathogenic relative to CD6low cells. Furthermore, T cells in CD6 knockout mice have decreased proliferation and inflammatory responses. Hence, a therapeutic that can modulate surface levels of CD6 may have favorable outcomes for autoimmune/inflammatory conditions. We recently demonstrated that the anti-CD6 mAb, itolizumab, induces proteolytic cleavage of cell surface CD6. The goal of the work shown here is to characterize the mechanism of cleavage and the downstream functional consequences of reduced cell surface CD6. Treatment of PBMCs with itolizumab induces CD6 cleavage from the cell surface and a concomitant increase in the soluble form detected in the supernatant. Itolizumab-induced loss of CD6 was not observed with isolated T cells, however CD6 levels were reduced by 87% when T cells and monocytes were cocultured with itolizumab. The cleavage of CD6 is initiated through rapid cell-to-cell contact between T cells and monocytes via FcγRI. The dose-dependent reduction in surface levels of CD6 positively correlates with decreases in T cell activation markers such as CD25, PD-1, and CD71 (Pearson, p<0.001) and cytokine production including IL-2 (p<0.01) and TNFα (p<0.05). Itolizumab-treated cells are also less alloreactive as shown by a reduction in proliferation and cytokine production of responder cells in a mixed-lymphocyte reaction. This data further supports targeting CD6 as an effective means to inhibit pathogenic T cell activity in the treatment of autoimmune and inflammatory diseases.
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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 | 0.001 |
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 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".