Amelioration of Murine Immune Thrombocytopenia by CD44 Antibodies: a Potential Therapy for ITP?
Bibliographic record
Abstract
Abstract Abstract 2528 Intravenous immunoglobulin (IVIg) is used to treat autoimmune diseases such as ITP. IVIg is a limited resource and its dosage and cost are both high. Although considered safe, it will always carry a theoretical risk of transferring infectious disease. Thus it would thus be highly desirable to improve the efficacy of IVIg or develop monoclonal antibodies, capable of mimicking the clinical effects of IVIg. Work by others has successfully improved the efficaciousness of IVIg in murine models of autoimmunity: It has been shown that enriched sialylated IVIg has a therapeutic effect at a 1 log fold lower dosage than IVIg; and a sialylated recombinant Fc fragment of IgG functions successfully at a 2 log fold lower dosage than IVIg. CD44 is a widely expressed cell surface polymorphic glycoprotein. It is involved in many processes including tumour metastasis and inflammation. CD44 antibodies have been successfully used to treat several murine autoimmune disease models, including inflammatory arthritis and experimental autoimmune encephalomyelitis, although their mechanism of action remains unclear. To explore the potential for monoclonal antibodies as a treatment for ITP as well as further explore their mechanisms of action, we tested 8 monoclonal CD44 antibodies in murine ITP, and found 4 antibodies which could successfully ameliorate ITP; 2 of these antibodies function at a full 3 log fold lower dosage as compared to IVIg. Further characterization of the 2 most successful antibodies (5035-41.1D and KM114) demonstrated that, similar to IVIg, i) the expression of the inhibitory IgG receptor FcγRIIB was required for their ameliorative function and ii) complement-depleted mice also responded to anti-CD44 treatment. Dissimilar to IVIg, the Fc portion of the CD44 antibody was not required: an F(ab')2 fragment of antibody KM114 also significantly ameliorated thrombocytopenia at an equivalent molar concentration as intact KM114. Thus while KM114 functions by an FcγRIIB sensitive mechanism, FcγRIIB is unlikely a direct target of the Fc region of this antibody and likely plays a downstream role in the amelioration of immune thrombocytopenia, similar to IVIg. These data demonstrate that CD44 antibodies can function therapeutically in murine ITP and we speculate that they could potentially provide a very low dose recombinant therapy for the treatment of ITP. Disclosures: No relevant conflicts of interest to declare.
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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".