Abstract 581: Better together: Biparatopic [225Ac]Ac-labeled anti-HER2 antibody-drug radioconjugates using two domain-specific antibodies for the treatment of trastuzumab and T-DM1 resistant HER2-positive breast cancer xenografts
Bibliographic record
Abstract
Abstract Purpose: HER2 is amplified and overexpressed in breast cancer (BC) and other cancers where it promotes proliferation and mediates resistance to targeted therapies. A combination of anti-HER2 trastuzumab and pertuzumab is approved for treatment. Aim: To develop and evaluate a combination antibody-drug radioconjugates (ADRs) [225Ac]Ac-Macropa-trastuzumab-PEG6-DM1 ([225Ac]Ac-Macropa-T-PEG6-DM1) and [225Ac]Ac-Macropa-pertuzumab-PEG6-DM1 ([225Ac]Ac-Macropa-P-PEG6-DM1) against HER2-positive BC. Experimental Design: Therapeutics [225Ac]Ac-Macropa-T-PEG6-DM1 and [225Ac]Ac-Macropa-P-PEG6-DM1 and their respective imaging pairs [89Zr]Zr-DFO-trastuzumab-PEG6-DM1 and [67Cu]Cu-DOTA-pertuzumab-PEG6-DM1 were developed and characterized. Biodistribution and toxicological evaluation of [225Ac]Ac-Macropa-T-PEG6-DM1 and [225Ac]Ac-Macropa-P-PEG6-DM1 were carried out in healthy female Balb/C mice. Dual microPET/SPECT/CT imaging and biodistribution using [89Zr]Zr-DFO-T-PEG6-DM1 and [67Cu]Cu-DOTA-P-PEG6-DM1 was performed in female athymic Balb/C nude mice bearing HCC1954 and JIMT-1 xenografts. Therapy was carried out using ADCs (T-PEG6-DM1 + P-PEG6-DM1) and ADRs ([225Ac]Ac-Macropa-T-PEG6-DM1 + [225Ac]Ac-Macropa-P-PEG6-DM1 = [225Ac]Ac-Macropa-(T+P)-PEG6-DM1) in athymic Balb/C nude mice bearing trastuzumab-resistant HCC1954 (high HER2 density) and T-DM1/trastuzumab-resistant JIMT-1 (medium HER2 density) tumors. Results: Internalization in HCC1954 and JIMT-1 cells was HER2 density-dependent, with the highest total red object area values recorded with the ADC combination (T-ADC + P-ADC) compared with the single agents (p < 0.0001). Dual microPET/SPECT/CT imaging and biodistribution of [89Zr]Zr-DFO-T-PEG6-DM1 and [67Cu]Cu-DOTA-P-PEG6-DM1 showed very high tumor uptake in both HCC1954 and JIMT-1 xenografts with high tumor-non-target ratios. The combination of ADCs (T-ADC + P-ADC) and ADRs ([225Ac]Ac-Macropa-(T+P)-PEG6-DM1) administered separately in healthy Balb/C mice, 10 days apart was well tolerated biochemically and haematologically for 20 days (d). Compared with the individual agents, there was improved non-target clearance using the combined ADRs [225Ac]Ac-Macropa-(T+P)-PEG6-DM1. In HCC1954-tumor bearing mice, all treatment groups had complete remission (CR) after 29d and 22d for (T-PEG6-DM1 + P-PEG6-DM1) and ADRs ([225Ac]Ac-Macropa-(T+P)-PEG6-DM1) respectively. Interestingly, in JIMT-1 xenografts at 60d post treatment, no CR was observed for the ADCs group whereas in the ADRs group, the average tumor volume was 11.5 ± 4.4 mm3 with 3/8 CRs. Conclusion: [225Ac]Ac-Macropa-(T+P)-PEG6-DM1 is more potent than their respective combined ADCs against HER2-positive BC and warrants further evaluation. Citation Format: Jessica Pougoue Ketchemen, Alissar Monzer, Fabrice Ngoh Njotu, Hanan Babeker, Emmanuel Nwangele, Anjong Florence Tikum, Nikita Henning, Nava Hassani, Alireza Doroudi, Humphrey Fonge. Better together: Biparatopic [225Ac]Ac-labeled anti-HER2 antibody-drug radioconjugates using two domain-specific antibodies for the treatment of trastuzumab and T-DM1 resistant HER2-positive breast cancer xenografts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 581.
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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) | 0.004 | 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".