Dose predictions for [177Lu]Lu-DOTA-panitumumab F(ab′)2 in NRG mice with HNSCC patient-derived tumour xenografts based on [64Cu]Cu-DOTA-panitumumab F(ab′)2 – implications for a PET theranostic strategy
Bibliographic record
Abstract
Abstract Background Epidermal growth factor receptors (EGFR) are overexpressed on many head and neck squamous cell carcinoma (HNSCC). Radioimmunotherapy (RIT) with F(ab')2 of the anti-EGFR monoclonal antibody panitumumab labeled with the β-particle emitter, 177Lu may be a promising treatment for HNSCC. Our aim was to assess the feasibility of a theranostic strategy that combines positron emission tomography (PET) with [64Cu]Cu-DOTA-panitumumab F(ab')2 to image HNSCC and predict the radiation equivalent doses to the tumour and normal organs from RIT with [177Lu]Lu-DOTA-panitumumab F(ab')2. Results Panitumumab F(ab')2 were conjugated to DOTA and complexed to 64Cu or 177Lu in high radiochemical purity (95.6 ± 2.1% and 96.7 ± 3.5%, respectively) and exhibited high affinity EGFR binding (Kd = 2.9 ± 0.7 × 10− 9 mol/L). Biodistribution (BOD) studies at 6, 24 or 48 h post-injection (p.i.) of [64Cu]Cu-DOTA-panitumumab F(ab')2 (5.5–14.0 MBq; 50 μg) or [177Lu]Lu-DOTA-panitumumab F(ab')2 (6.5 MBq; 50 μg) in NRG mice with s.c. HNSCC patient-derived xenografts (PDX) overall showed no significant differences in tumour uptake but modest differences in normal organ uptake were noted at certain time points. Tumours were imaged by microPET/CT with [64Cu]Cu-DOTA-panitumumab F(ab')2 or microSPECT/CT with [177Lu]Lu-DOTA-panitumumab F(ab')2 but not with irrelevant [177Lu]Lu-DOTA-trastuzumab F(ab')2. Tumour uptake at 24 h p.i. of [64Cu]Cu-DOTA-panitumumab F(ab')2 [14.9 ± 1.1% injected dose/gram (%ID/g) and [177Lu]Lu-DOTA-panitumumab F(ab')2 (18.0 ± 0.4%ID/g) were significantly higher (P < 0.05) than [177Lu]Lu-DOTA-trastuzumab F(ab')2 (2.6 ± 0.5%ID/g), demonstrating EGFR-mediated tumour uptake. There were no significant differences in the radiation equivalent doses in the tumour and most normal organs estimated for [177Lu]Lu-DOTA-panitumumab F(ab')2 based on the BOD of [64Cu]Cu-DOTA-panitumumab F(ab')2 compared to those estimated directly from the BOD of [177Lu]Lu-DOTA-panitumumab F(ab')2 except for the liver and whole body which were modestly underestimated by [64Cu]Cu-DOTA-panitumumab F(ab')2. Region-of-interest (ROI) analysis of microPET/CT images provided dose estimates for the tumour and liver that were not significantly different for the two radioimmunoconjugates. Human doses from administration of [177Lu]Lu-DOTA-panitumumab F(ab')2 predicted that a 2 cm diameter HNSCC tumour in a patient would receive 1.1–1.5 mSv/MBq and the whole body dose would be 0.15–0.22 mSv/MBq. Conclusion A PET theranostic strategy combining [64Cu]Cu-DOTA-panitumumab F(ab')2 to image HNSCC tumours and predict the equivalent radiation doses in the tumour and normal organs from RIT with [177Lu]Lu-DOTA-panitumumab F(ab')2 is feasible. RIT with [177Lu]Lu-DOTA-panitumumab F(ab')2 may be a promising approach to treatment of HNSCC due to frequent overexpression of EGFR.
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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".