Abstract LB313: EGFRvIII-targeted alpha therapy shows significant therapeutic efficacy as both a single-agent and in combination with standard of care against preclinical GBM models
Bibliographic record
Abstract
Abstract Targeted alpha therapy (TAT) is a rapidly advancing class of radiotherapeutics that can effectively deliver potent and local radiation to cancer cells while sparing the surrounding normal cells. TATs hold great promise for treatment-resistant tumors such as glioblastoma multiforme (GBM) due to the extensive DNA damage and cell death induced by alpha particles. GBM is an aggressive and lethal primary adult brain tumor that is highly resistant to external beam radiation and chemotherapy. Herein, we present the preclinical evaluation of a novel TAT for treatment of GBM targeting the most common tumour-specific mutant, epidermal growth factor receptor variant 3 (EGFRvIII). Our EGFRvIII TAT consists of a humanized EGFRvIII monoclonal antibody, a proprietary bifunctional chelate, and the alpha-emitting radionuclide, actinium-225 (225Ac). In vivo biodistribution and efficacy of our EGFRvIII TAT was evaluated in two aggressive orthotopic EGFRvIII-expressing GBM patient-derived xenograft models (PDXs; G06 and G39) with varying degrees of blood-brain-tumor barrier (BBTB) permeability. Imaging biodistribution studies were performed using an [111In]-anti-EGFRvIII agent analogous to our [225Ac] therapeutic candidate. SPECT/BLT imaging 96 h after intravenous administration of the imaging agent revealed high tumor-specific uptake of 50.2 %ID/cc in G39 tumors with a disrupted BBTB, and 10.4% ID/cc in G06 tumors with a relatively intact BBTB. Normal brain showed very low uptake (1.6-2.1% ID/cc), and all other normal organs were <10 % ID/cc except for highly perfused organs such as heart and liver, indicating no significant off-target uptake. [225Ac]-anti-EGFRvIII single-dose and fractionated multi-dose efficacy studies were conducted in G06 and G39 orthotopic PDX models, respectively. Survival analysis showed a dose-dependent increase in survival in response to treatment with [225Ac]-anti-EGFRvIII therapy, with a greater than 3-fold increase in survival compared to vehicle controls at doses of 200-400 nCi. Furthermore, the survival benefit of the 400 nCi single-dose or fractionated equivalent dose groups were comparable, demonstrating that efficacy was dependent upon the total administered radioactivity dose. Finally, we show that combined treatment of [225Ac]-anti-EGFRvIII with the standard of care (SoC), external beam radiation plus temozolomide, resulted in a significant survival advantage (>1.7-fold) compared to TAT or SoC therapy alone. Collectively, these results demonstrate that [225Ac]-anti-EGFRvIII is a highly selective and potent therapeutic for GBM which holds great potential as both a single-agent and in combination with SoC. Citation Format: Julie Metcalf, Alexander Nielsen, Suma Prabhu, Nicole Robinson, Sarah Marinacci, Natalie Grinshtein, Brigitte L. Theriault, Anne Marcil, Maria L. Jaramillo, Traian Sulea, Ivan A. Lessard, Maria Moreno, Christopher P. Leamon, Eric Burak, John Valliant. EGFRvIII-targeted alpha therapy shows significant therapeutic efficacy as both a single-agent and in combination with standard of care against preclinical GBM models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB313.
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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".