CD20-Directed Serotherapy in Patients With Multiple Myeloma: Biologic Considerations and Therapeutic Applications
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Bibliographic record
Abstract
Clonotypic B cells circulating in patients with multiple myeloma (MM) express CD20, and it has been suggested that these cells may be clonogenic. Furthermore, 20% of patients with MM express CD20 on their bone marrow plasma cells (BMPCs). Therefore, the authors began a phase II clinical study to determine the activity of the anti-CD20 monoclonal antibody rituximab in MM patients. Nineteen previously treated MM patients received 375 mg/m2 rituximab per week for 4 weeks. Three months after initiation of treatment, patients were assessed for response and received a second course of therapy if their disease was stable (SD) or they achieved a partial response (PR). Six of 19 (32%) patients had either a PR (n = 1) or SD (n = 5), with a median time to treatment failure of 5.5 months (mean, 10.3 months; range, 3-27+ months). All six patients who had a PR or SD had CD20+ BMPC. Overall, rituximab therapy was well tolerated. Because most patients with MM poorly express CD20 on their BMPCs, the authors evaluated agents for their ability to induce CD20 expression and thereby facilitate rituximab binding on MM cells. These studies show that interferon-gamma (IFN-y) induced CD20 expression on MM BMPCs, MM B cells, and healthy donor BMPCs. In contrast, CD20 expression on chronic lymphocytic leukemia, follicular non-Hodgkin's lymphoma, healthy donor B cells, and progenitor cells was unaffected by IFN-y. Rituximab binding to the BMPCs of MM patients was also increased after culture with pharmacologically attainable levels of IFN-gamma (1-100 U/mL). In conclusion, these studies suggest that MM patients with CD20+ BMPCs may benefit from rituximab therapy. Furthermore, IFN-gamma induces CD20 expression on MM BMPCs and B cells and facilitates rituximab binding to MM BMPCs, providing the rationale for clinical trials to examine its use with CD20-directed serotherapies in MM.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it