Abstract 4553: Novel bispecific 111In-labeled immunoconjugates (bsICs) for imaging HER2/HER3 heterodimerization in breast cancer
Bibliographic record
Abstract
Abstract Objective: Our objective was to construct novel bsICs capable of binding HER2 and HER3 labeled with 111In for imaging HER2-HER3 heterodimerization in breast cancer (BC) possibly through higher avidity for dimeric vs. monomeric complexes. Methods: bsICs were composed of trastuzumab Fab recognizing HER2 linked to a 7.5 kDa HER3-binding peptide of heregulin-β1 (pHRG). Fab were produced by digestion of trastuzumab IgG with papain. Fab were modified with Sulfosuccinimidyl-4-(N-maleimidomethyl)cyclohexane-1-carboxylate (sulfo-SMCC) or related analogues with polyethyleneglycol (PEG) spacers (SM-PEG12-NHS and SM-PEG24-NHS) to introduce maleimide groups for cross-linking to pHRG thiolated with Traut's reagent. bsICs were derivatized with diethylenetriaminepentaacetic acid (DTPA) for labeling with 111In. The ability to independently bind HER2 or HER3 was determined in competition assays using 111In-bsICs on cells expressing HER2, HER3 or both receptors competed with a 25-fold excess of Fab, pHRG or combined ligands. Results: Conjugation of Fab to pHRG was confirmed by SDS-PAGE, Western blot and size-exclusion HPLC. bsICs were labeled with 111In to a radiochemical purity of 98.9 ± 0.2% (specific activity 375 ± 14 MBq/mg). Insertion of a PEG spacer between Fab and pHRG was required for displacement of binding of 111In-bsICs to HER3 but not HER2. For 111In-bsICs with the longest spacer (PEG24), the binding to SKBR-3 cells (HER2+/HER3+) was reduced to 32.7 ± 0.7%, 85.9 ± 1.0% or 30.4 ± 1.6%, respectively by Fab, pHRG or both ligands. The binding to SKOV-3 cells (HER2+/HER3-) was reduced to 16.7 ± 0.8%, 88.8 ± 5.3% or 13.4 ± 0.1% by Fab, pHRG or both ligands. The binding to MDA-MB-468 cells (HER2-/HER3+) was reduced to 98.5 ± 1.5%, 68.8 ± 0.3% or 64.8 ± 4.5% by Fab, pHRG or both ligands. Less efficient competition for HER3 was observed for the PEG12 spacer and no competition for 111In-bsICs without a spacer. Conclusion: 111In-bsICs composed of trastuzumab Fab and pHRG bound specifically to HER2 and HER3 when an appropriate length PEG spacer was inserted between these two binding moieies. These 111In-bsICs may be useful for imaging HER2-HER3 heterodimerization in BC. Supported by the Ontario Institute of Cancer Research (1 mm Challenge) and the Canadian Breast Cancer Foundation (Ontario Branch). Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4553.
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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 | 0.001 |
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".