Abstract A075 GD2-SADA, a bispecific fusion protein that forms self-assembling and disassembling (SADA), GD2-avid tetramers with high affinity for chelated radiolanthanides
Bibliographic record
Abstract
Abstract Background: High-risk neuroblastoma (HRNB) has an especially poor prognosis, underscoring the need for improved treatment strategies. Two-step pretargeted radioimmunotherapy (PRIT) is an investigational approach designed to deliver cytotoxic radiation to cancer cells and limit off-target exposure. GD2-SADA PRIT uses GD2-SADA, a bispecific fusion protein that binds the glycolipid GD2 and radionuclides chelated to tetraxetan (DOTA). The protein contains a p53-derived tetramerization domain that drives the SADA of GD2-SADA tetramers, which have 4 distinct GD2 binding sites. Previous studies have shown that, in the 1st step, nonradiolabeled GD2-SADA tetramers are infused and bind with high avidity to GD2+ cells, at levels that in vitro results suggest are ∼50-fold greater than GD2-SADA mutants unable to self-assemble. Tetramer assembly and disassembly are in dynamic equilibrium, with disassembly yielding renally cleared monomers. In the 2nd step, the DOTA-chelated radioactive payload is infused and binds to GD2-SADA on GD2+ tumors, where it delivers ionizing radiation. In a xenograft model of NB, GD2-SADA PRIT with Lu177-DOTA demonstrated potent anti-tumor responses. Here, we report results from in vitro analyses describing the SADA properties of GD2-SADA and the high-affinity binding of GD2-SADA to Tb-DOTA. Methods: Real-time binding kinetics and binding affinities of the Tb-DOTA complex (association [ka] and dissociation [kd] rate constants and equilibrium constant (KD) were evaluated using Biacore Surface Plasmon Resonance (SPR) technology and compared with positive (Lu-DOTA) and negative (empty DOTA) controls. Disassembly of GD2-SADA was characterized over concentrations ranging from 5-200nM. Briefly, diluted GD2-SADA solutions were prepared in PBS equilibrated at 37°C for ≤180 min, after which an equilibrium was reached, and the distribution of tetramers and monomers was measured using a Refeyn TwoMP instrument. Results: SPR kinetic analysis demonstrated tight binding interactions between GD2-SADA and Tb-DOTA (kd=3.1E-3 1/s; ka=2.7E5 1/Ms; KD=12nM) comparable to Lu-DOTA (kd=8.6E-3 1/s; ka=4.5E5 1/Ms; KD=19nM). The empty DOTA, by contrast, showed response levels comparable to blank samples. Mass photometry demonstrated a concentration-dependent shift in the distribution of GD2-SADA tetramers, from 88% to 32% at 200 and 5nM GD2-SADA, respectively. The change in distribution patterns followed a logarithmic profile with a plateau observed above ∼100nM, and an equivalent distribution of 50% tetramers and 50% monomers observed at 12nM GD2-SADA. Conclusions: GD2-SADA demonstrated high-affinity binding to Tb-DOTA, a chelated lanthanide metal with multiple medical isotopes of potential benefit for targeted radiotherapy. The time- and concentration-dependent disassembly of GD2-SADA tetramers has informed ongoing PK/PD modeling and initial dosing in Trial 1001 (NCT05130255), a first-in-human, phase 1 trial of GD2-SADA PRIT with Lu177-DOTA in adolescent and adult patients with GD2+ solid tumors, with Trial 1002 planned for pediatric patients with HRNB. Citation Format: Nico Liebenberg, Johannes Nagel, Michael S. Windahl, Hannah Paar, Simon Gaderer, Brian H. Santich. GD2-SADA, a bispecific fusion protein that forms self-assembling and disassembling (SADA), GD2-avid tetramers with high affinity for chelated radiolanthanides [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr A075.
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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 | 0.000 |
| 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".