AGS67E, an Anti-CD37 Monomethyl Auristatin E Antibody–Drug Conjugate as a Potential Therapeutic for B/T-Cell Malignancies and AML: A New Role for CD37 in AML
Why this work is in the frame
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Bibliographic record
Abstract
CD37 is a tetraspanin expressed on malignant B cells. Recently, CD37 has gained interest as a therapeutic target. We developed AGS67E, an antibody-drug conjugate that targets CD37 for the potential treatment of B/T-cell malignancies. It is a fully human monoclonal IgG2 antibody (AGS67C) conjugated, via a protease-cleavable linker, to the microtubule-disrupting agent monomethyl auristatin E (MMAE). AGS67E induces potent cytotoxicity, apoptosis, and cell-cycle alterations in many non-Hodgkin lymphoma (NHL) and chronic lymphocytic leukemia (CLL) cell lines and patient-derived samples in vitro. It also shows potent antitumor activity in NHL and CLL xenografts, including Rituxan-refractory models. During profiling studies to confirm the reported expression of CD37 in normal tissues and B-cell malignancies, we made the novel discovery that the CD37 protein was expressed in T-cell lymphomas and in AML. AGS67E bound to >80% of NHL and T-cell lymphomas, 100% of CLL and 100% of AML patient-derived samples, including CD34(+)CD38(-) leukemic stem cells. It also induced cytotoxicity, apoptosis, and cell-cycle alterations in AML cell lines and antitumor efficacy in orthotopic AML xenografts. Taken together, this study shows not only that AGS67E may serve as a potential therapeutic for B/T-cell malignancies, but it also demonstrates, for the first time, that CD37 is well expressed and a potential drug target in AML.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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