Lupus Regulator Peptide P140 Represses B Cell Differentiation by Reducing HLA Class II Molecule Overexpression
Bibliographic record
Abstract
OBJECTIVE: Phosphopeptide P140 (Lupuzor) is an inhibitor of autophagy currently being evaluated in late-stage clinical trials for the treatment of lupus. This study was undertaken to investigate the effect of P140 ex vivo on human T and B cells. METHODS: Human B cells, T cells, and dendritic cells were analyzed by flow cytometry and cellular assays. The expression of autophagy markers was evaluated by immunoblotting and flow cytometry. The levels of B cell receptor (BCR) signaling markers and HLA molecules were assessed by flow cytometry. Toll-like receptor ligands were screened using an assay with transfected HEK 293 cells. P140 cell entry and trafficking were measured by immunofluorescence in the presence of various inhibitors of endosomal pathways. RESULTS: As was previously observed after intravenous injection of the peptide in a mouse model of lupus, P140 entered human B cells by a clathrin coat-dependent endocytosis process and homed into lysosomes. The peptide displayed no direct effect on BCR signaling of memory, naive mature, transitional, and B1 cells. However, it strongly reduced the overexpression of HLA class II molecules on lupus B cells that were acting as antigen-presenting cells, down-regulated the maturation and differentiation of B cells into plasma cells, and decreased IgG secretion. CONCLUSION: These findings show that P140 down-regulates HLA class II overexpression in human lupus B cells, and also that P140 hampers the differentiation of B cells into autoantibody-secreting plasma cells, likely due to the resulting lack of T cell signaling and activation. This mechanism appears to switch off the downstream events leading to secretion of pathogenic autoantibodies, thus explaining the highly promising results obtained in clinical trials of P140 (Lupuzor) for the treatment of lupus.
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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 | 0.000 |
| 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".