POTENT AND SPECIFIC KILLING OF SLE B CELLS WITH ALLONK <sup>®</sup> (AB-101), AN ALLOGENEIC CORD BLOOD-NK CELL THERAPY, IN COMBINATION WITH ANTI-CD19 OR ANTI-CD20 MONOCLONAL ANTIBODIES
Bibliographic record
Abstract
PV250 / #419 Poster Topic: AS24 - SLE-Treatment Background/Purpose Systemic lupus erythematosus (SLE) is a systemic inflammatory disorder involving loss of tolerance and development of autoantibodies. B cells play a crucial role in the pathogenesis of SLE by producing autoantibodies that target self-antigens, leading to tissue damage and inflammation. In individuals with SLE, Natural Killer (NK) cells are often found to be fewer in number and functionally impaired, including defective antibody-dependent cellular cytotoxicity (ADCC), altered differentiation and abnormal cytokine production. Given the reported defects in NK cells from SLE patient samples, we hypothesize that administration of an NK cell therapy, in combination with B cell-depleting monoclonal antibodies (mAbs), will have the potential to induce deeper B cell depletion and improve efficacy, over the mAb alone. Here we demonstrate proof of concept for the use of an NK cell therapy to enhance the depletion of SLE donor B cells in the presence of anti-CD19 or anti-CD20 mAbs by an ADCC mechanism. AlloNK ® is a non-genetically modified, allogeneic, off-the-shelf, cryopreserved NK cell product, currently being evaluated in a Phase 1 clinical trial in combination with rituximab or obinutuzumab in subjects with SLE or lupus nephritis ( NCT06265220 ). Methods Comprehensive immunophenotypic analysis of B and NK cell subsets from SLE (n=9) and healthy donor (n=6) peripheral blood mononuclear cells (PBMC) was conducted by flow cytometry. In addition, PBMC were isolated from SLE donors (n=9) and co-cultured with AlloNK at various effector to target (E:T) ratios and mAbs concentrations to assess ADCC. Results To further investigate these findings, B and NK cell subsets from both SLE patients and healthy individuals were assessed. In SLE patient samples, there was an observed increase in transitional B and a decrease in activated memory B cells compared to healthy individuals. Additionally, SLE patient samples had a reduction in total NK, CD16 and NKG2D but an increase in CD56 bright CD16 neg NK cells compared to healthy donors. AlloNK, which has been optimized for ADCC through the preselection of cord blood units for the natural high-affinity variant of CD16 (158V/V), was tested in combination with anti-CD20 (rituximab, obinutuzumab) or anti-CD19 (tafasitamab) mAbs in a short-term ADCC assay to show specific killing of SLE donor B cells. After 4h, the percentage of caspase 3/7 + B and T cells was determined by flow cytometry. At a 1:1 E:T ratio, AlloNK mediated killing of B cells in the presence of obinutuzumab (range 79-95%), rituximab (range 19-62%), and tafasitamab (range 24-77%) in a dose-dependent manner. Killing was specific as no off-target apoptosis of T cells was observed. Conclusions Taken together, these data suggest that AlloNK has the potential to be effective in combination with mAbs to induce deeper B cell depletion and improved efficacy, over the mAbs alone, in SLE and LN.
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) | 0.002 | 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".