EGFR-Targeted Metal Chelating Polymers (MCPs) Harboring Multiple Pendant PEG<sub>2K</sub> Chains for MicroPET/CT Imaging of Patient-Derived Pancreatic Cancer Xenografts
Bibliographic record
Abstract
Abstract In this study, we developed a new generation of metal chelating polymer (MCP) reagents that carry multiple polyethylene glycol (PEG) pendant groups to provide stealth to MCP-based radioimmunoconjugates (RICs). We describe the MCP synthesis for covalent attachment to panitumumab F(ab′)2 fragments (pmabF(ab′)2) in which different numbers of pendant methoxy-PEG chains [M = 2000, ∼45 ethylene glycol (EG) repeat units, referred to as PEG2K] are incorporated into the polymer backbone. The pendant PEG2K chains were designed to provide a protein-repellant corona so that metal chelators attached closer to the polymer backbone will be less apparent to the physiological environment. DOTA (1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid) groups to chelate 64Cu were installed on these conjugates to be employed for PET imaging. The conjugation of MCPs to pmabF(ab′)2 was based on a UV quantifiable bis-aromatic hydrazone formation under mild conditions (pH 5–6) between an aromatic aldehyde introduced on ε-NH2 groups of lysines in the F(ab′)2 fragments and a hydrazinonicotinamide (HyNic) group installed on the initiating end of the MCP. Three MCPs with 17 polyglutamide (PGlu) repeat units, DOTA chelators and with an average of 2, 4, and 8 pendant PEG2K chains were studied to examine their in vitro and in vivo characteristics, as well as their potential for PET/CT imaging. A pmabF(ab′)2-MCP conjugate carrying 2 PEG2K and one carrying 8 PEG2K pendant chains in the polymer were selected for microPET/CT imaging and biodistribution studies in tumor-bearing mice. Orthotopic pancreatic patient-derived xenografts tumors were visualized by PET/CT imaging. These RICs showed low levels of liver and spleen uptake along with even lower levels of kidney uptake. These encouraging results confirm the stealth properties of the MCPs with pendant PEG2K chains.
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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".