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Record W3190870985 · doi:10.1186/s41181-021-00140-1

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

2021· article· en· W3190870985 on OpenAlexafffund
Anthony Ku, Misaki Kondo, Zhongli Cai, Jalna Meens, Min Rong Li, Laurie Ailles, Raymond M. Reilly

Bibliographic record

VenueEJNMMI Radiopharmacy and Chemistry · 2021
Typearticle
Languageen
FieldMedicine
TopicRadiopharmaceutical Chemistry and Applications
Canadian institutionsUniversity Health NetworkPrincess Margaret Cancer CentreUniversity of Toronto
FundersUniversity of TorontoCanadian Cancer SocietyTerry Fox FoundationGovernment of OntarioAmgen CanadaAmgen
KeywordsPanitumumabDOTARadioimmunotherapyMedicineCancer researchEpidermal growth factor receptorNuclear medicineBiodistributionMonoclonal antibodyChemistryCetuximabInternal medicineReceptorAntibodyChelationImmunology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.026
GPT teacher head0.307
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations12
Published2021
Admission routes2
Has abstractyes

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