Itolizumab-induced antigenic modulation of CD6 inhibits T cell activity
Bibliographic record
Abstract
Abstract CD6 is an immunomodulatory receptor on T cells that promotes immune synapse formation, T-cell activation, and cell migration into tissues by binding activated leukocyte cell adhesion molecule (ALCAM). Excessive activation through the CD6-ALCAM pathway has been implicated in the pathogenesis of multiple autoimmune and inflammatory diseases. Hence, the ability to modulate the level of activation is beneficial to disease resolution. Itolizumab is a humanized anti-CD6 monoclonal antibody that is specific for the membrane distal domain 1 of CD6. Previously, itolizumab was believed to sterically hinder the CD6-ALCAM interaction, thereby blocking T-cell co-stimulation. Here we describe antigenic modulation as an additional mechanism whereby binding of itolizumab to CD6 induces proteolytic cleavage of the extracellular portion of CD6. Upon treatment with itolizumab, surface levels of CD6 decreased in a dose- and time-dependent manner, as monitored by flow cytometry using a noncompetitive anti-CD6 monoclonal antibody. This loss was inhibited in the presence of protease inhibitors and the decrease in surface levels of CD6 was accompanied by an increase in levels of soluble CD6 in the supernatant. Furthermore, we assessed the effect of surface levels of CD6 on the response of cells to T cell stimulation in the presence of ALCAM. CD6low cells showed reduced T-cell activity compared to CD6highcells as measured by cell surface activation makers, including CD25, CD69 and PD-1, and cytokine production. These findings demonstrate that CD6 is an important regulator of T-cell activity and that modulating surface levels of CD6 is an effective method for fine-tuning the activity of T-cells.
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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) | 0.001 | 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".