Abstract 1813: Tumor and normal tissue localization of trastuzumab-modified with a metal chelating polymer for auger electron radioimmunotherapy in HER2-positive xenografts
Bibliographic record
Abstract
Abstract Purpose We have been investigating a potential radioimmunotherapeutic (RIT) agent using the anti-HER2 monoclonal antibody trastuzumab to address the issue of primary and acquired resistances in HER2-positive Breast cancer (BC). Trastuzumab was conjugated to a metal chelating polymer (MCP) with multiple DTPA units for labeling with the Auger electron emitter Indium-111 (111In) [trastuzumab-MCP-111In]. We aim to increase the amount of radioactivity delivered and enhance the therapeutic effect towards trastuzumab sensitive and resistant tumors. High specific activity (SA) (5.5 MBq/μg) trastuzumab-Hy-MCP-111In was more cytotoxic at killing HER2-positive BC cells sensitive and resistant than low SA (0.37MBq/μg) radioimmunoconjugates (RICs) in vitro. The current study aimed to investigate the tumor localization properties of this new RIT in mice with HER-2 positive BC xenografts. Methods Hydrazide MCP with polyglutamide backbone, 20 or 30 DTPA units, and without or with PEG chains [Hy-(PEG)-MCP-111In] were site-specifically linked to periodate-oxidized carbohydrates on the Fc domain of trastuzumab. Tumor and normal tissue distribution were assessed in CD-1 athymic mice bearing BT-474 (1×106 HER2 receptors/cell) or trastuzumab resistant TrR1 (5×105 HER2 receptors/cell) xenografts. Mice were injected intravenously with trastuzumab-Hy-(PEG)-MCP-111In (10μg; 3-4 MBq/μg), or trastuzumab-Hy-(PEG)-MCP-111In (1μg; 3-5 MBq/μg) without or with non-labeled non specific anti-CD20 rituximab (9μg). Controls consisted of mice injected with MCPs only and trastuzumab-NH-Bn-DTPA-111In. Results Trastuzumab-Hy-(PEG)-MCP-111In exhibited a HER2-mediated uptake in BT-474 tumors. Both RICs (10μg) had a higher tumor uptake (0.8±0.4 and 1.3±0.3%ID/g) than the non-targeted Hy-(PEG)-MCP-111In (0.2±0.04 and 0.3±0.1%ID/g) (p = 0.0104; p<0.0001). Tumor uptake was also HER2-density dependent with about a 3-fold decrease (0.4±0.1%ID/g) in TrR1-bearing mice for trastuzumab-Hy-PEG-MCP-111In. Kidneys were found to be the major normal organ accumulation in both formulations. Nevertheless, pegylation of the MCP caused a 4-fold decrease in kidneys uptake (6.9±2.5 to 1.6±0.1% ID/g; p = 0.0018). At low mass (1μg) and high SA, addition of non-labeled rituximab improved the tumor uptake of trastumab-Hy-MCP-111In by 2 fold (0.3±0.1 to 0.6±0.1%ID/g), but no change in tumor uptake was seen for trastuzumab-Hy-PEG-MCP-111In. Nonetheless, BT-474 tumor uptake of trastuzumab-Hy-(PEG)-MCP-111In was lower than the one obtained with trastuzumab-NH-Bn-DTPA-111In (13.3±3.4%ID/g). Conclusion Our results suggest that trastuzumab-Hy-(PEG)-MCP-111In could target HER2-positive xenografts sensitive and resistant to trastuzumab. Further modifications on the MCP are needed to improve the tumor uptake for Auger electron radioimmunotherapy. Citation Format: Ghislaine Ngo Ndjock Mbong, Yijie Lu, Conrad Chan, Zhongli Cai, Mitchell A. Winnik, Raymond Reilly. Tumor and normal tissue localization of trastuzumab-modified with a metal chelating polymer for auger electron radioimmunotherapy in HER2-positive xenografts. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1813. doi:10.1158/1538-7445.AM2015-1813
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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) | 0.001 | 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".