Analysis of preclinical and clinical samples after treatment with a <scp>CD37</scp> targeting antibody drug conjugate (<scp>AGS67E</scp>) support a high level of <scp>CD37</scp> expression in <scp>NHL</scp>
Bibliographic record
Abstract
Introduction: AGS67E is an antibody drug conjugate against CD37 bound to monomethyl auristatin E (MMAE) via a protease-cleavable linker currently being investigated in subjects with relapsed/refractory NHL in a phase I dose-escalation study. CD37 is expressed in normal white blood cells (WBCs: B and T lymphocytes, NK cells, monocytes, and neutrophils). CD37 is also highly expressed in CLL, AML, and NHL, including 80% expression in DLBCL, as detected in tumor microarrays (TMA) of formalin-fixed paraffin-embedded (FFPE) tumor samples using the proprietary vCD37-9a73.1 antibody (Pereira et al., 2015). In contrast, the percentage of CD37 expression in DLBCL was recently determined to be 40% using a commercial antibody (2B8) on FFPE samples (Xu-Monette et al., 2016). Clinical and preclinical results, including a comparison of vCD37-9a73.1 with commercially available anti-CD37 reagents, are presented here in order to clarify the CD37 expression in DLBCL and in NHL in general. Methods: CD37 expression was investigated on WBCs by flow cytometry and on archived FFPE tumor samples by immunohistochemistry (IHC) from subjects in the phase I trial using the proprietary anti-CD37 antibody (vCD37-9a73.1). This antibody was selected for flow cytometry since it could detect CD37 on the surface of cells in the presence of AGS67E and showed similar CD37 levels to other anti-CD37 proprietary antibodies tested. The vCD37-9a73.1 and 2B8 antibodies were evaluated by IHC in FFPE cells and xenografts with different levels of CD37 mRNA levels, as well as in TMA of NHL. Results: CD37 expression in patient's WBCs was downregulated after AGS67E dosing, presumably due to AGS67E-mediated, dose-dependent decreases in WBCs. Furthermore, samples were CD37 positive as detected by both AGS67E and vCD37-9a73.1. These data support vCD37-9a73.1 as a suitable reagent for CD37 detection. IHC data from FFPE tumor samples from subjects enrolled in the ongoing phase I clinical trial with a variety of NHL pathologies demonstrated that CD37 was expressed in 100% of the samples examined (23 subjects) with an average H-score of 270 (maximum is 300), including 7 subjects with DLBCL (average H-score 277). Overall, the level and degree of expression were slightly higher than previously seen in TMA samples of NHL (~80%) with the same antibody and significantly higher than those reported with the 2B8 antibody. Evaluation of CD37 expression using vCD37-9a73.1 side-by-side with 2B8 in FFPE cells, xenografts, and TMA of NHL indicated that vCD37-9a73.1 has better sensitivity and specificity compared to 2B8 under the conditions tested. Keywords: CD37; diffuse large B-cell lymphoma (DLBCL); non-Hodgkin lymphoma (NHL)
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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) | 0.003 | 0.001 |
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".