Dual-Receptor–Targeted Radioimmunotherapy of Human Breast Cancer Xenografts in Athymic Mice Coexpressing HER2 and EGFR Using <sup>177</sup>Lu- or <sup>111</sup>In-Labeled Bispecific Radioimmunoconjugates
Bibliographic record
Abstract
UNLABELLED: One mechanism of resistance to trastuzumab in human epidermal growth factor receptor-2 (HER2)-positive breast cancer (BC) is increased epidermal growth factor receptor (EGFR) expression. We have developed (111)In-labeled bispecific radioimmunoconjugates (bsRICs) that bind HER2 and EGFR on BC cells by linking trastuzumab Fab fragments through a polyethylene glycol (PEG24) spacer to epidermal growth factor (EGF). We hypothesized that tumors coexpressing HER2 and EGFR could be treated by dual-receptor-targeted radioimmunotherapy with these bsRICs labeled with the β-particle emitter (177)Lu or the Auger electron-emitter (111)In. METHODS: The binding of (177)Lu-DOTA-Fab-PEG24-EGF to tumor cells (MDA-MB-231, SK-OV-3, MDA-MB-231/H2N, or TrR1) coexpressing HER2 and EGFR was assessed in competition assays. The clonogenic survival of these cells was measured after exposure to (177)Lu-DOTA-Fab-PEG24-EGF or (111)In-DTPA-Fab-PEG24-EGF or to monospecific (177)Lu- or (111)In-labeled trastuzumab Fab or EGF. The tumor and normal tissue biodistribution of (177)Lu-DOTA-Fab-PEG24-EGF was studied at 48 h after injection in athymic mice bearing subcutaneous MDA-MB-231/H2N tumors. Radiation-absorbed doses to tumors and normal tissues were estimated and compared for (111)In- and (177)Lu-labeled bsRICs. The maximum injected amount of (177)Lu-DOTA-Fab-PEG24-EGF that caused no observable adverse effects (NOAEL) was identified in BALB/c mice. Athymic CD1 nu/nu mice bearing subcutaneous trastuzumab-sensitive MDA-MB-231/H2N or trastuzumab-resistant TrR1 tumors were treated with (177)Lu-DOTA-Fab-PEG24-EGF or (111)In-DTPA-Fab-PEG24-EGF at the NOAEL, or with unlabeled immunoconjugates or normal saline. Tumor growth was evaluated over a period of 49 d. RESULTS: (177)Lu-DOTA-Fab-PEG24-EGF bound specifically to HER2 and EGFR on tumor cells. Monospecific (177)Lu- and (111)In-labeled trastuzumab Fab or EGF killed tumor cells that predominantly expressed HER2 or EGFR, respectively, whereas bsRICs were cytotoxic to cells that displayed either HER2 or EGFR or both receptors. bsRICs were more effective than monospecific agents. (177)Lu-DOTA-Fab-PEG24-EGF was more cytotoxic than (111)In-DTPA-Fab-PEG24-EGF. The tumor uptake of (177)Lu-DOTA-Fab-PEG24-EGF was 2-fold greater than (177)Lu-DOTA-trastuzumab Fab or (177)Lu-DOTA-EGF. The NOAEL for (177)Lu-DOTA-Fab-PEG24-EGF was 11.1 MBq (10 μg). Trastuzumab-sensitive MDA-MB-231/H2N and trastuzumab-resistant TrR1 tumors were growth-inhibited by (177)Lu-DOTA-Fab-PEG24-EGF or (111)In-DTPA-Fab-PEG24-EGF. Unlabeled immunoconjugates had no effect on tumor growth. (177)Lu-DOTA-Fab-PEG24-EGF inhibited tumor growth more effectively than (111)In-DTPA-Fab-PEG24-EGF because of a 9.3-fold-higher radiation-absorbed dose (55.0 vs. 5.9 Gy, respectively). CONCLUSION: These results are encouraging for further development of these bsRICs for dual-receptor-targeted radioimmunotherapy of BC coexpressing HER2 and EGFR, including trastuzumab-resistant tumors.
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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) | 0.001 | 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".