Enhancement of Rituximab-induced cell death by the physical association of CD20 with CD40 molecules on the cell surface
Bibliographic record
Abstract
CD20 is an attractive therapeutic target given the success of its monoclonal antibody, Rituximab, in the treatment of B-cell malignancies and B-cell-mediated autoimmune diseases. Treatment with Rituximab causes a rapid depletion of B cells and a decrease in disease symptoms. Despite the clinical efficiency of Rituximab, its mechanism of action is not completely understood. In this study, we aimed at further investigating the Rituximab-induced cell death and the factors affecting such responses. Our results indicate that Rituximab-induced cell death depends on the nature of the cells and levels of CD20 expression on the cell surface. Coexpression of CD20 with CD40, a member of the TNF receptor family that is known to be physically associated with CD20 on the cell surface, enhances the apoptotic response induced by Rituximab. Inhibiting the formation of CD40 disulfide-bound-homodimers, a process required for some CD40 signaling, further enhances Rituximab-induced cell death. Cell death induced by anti-CD40 mAb is also upregulated by the presence of CD20, suggesting a bidirectional influence of the CD20/CD40 association. Moreover, treating cells with both anti-CD20 and anti-CD40 antibodies improves the cell death response induced by a single-agent treatment. These results highlight the role of the CD20/CD40 association in triggering B-cell depletion and may pave the way for an alternative more efficient therapeutic strategy in treating B-cell-mediated disorders.
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 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 | 0.000 |
| 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".