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Record W3104946688 · doi:10.1186/s41181-020-00111-y

Radioimmunotherapy of PANC-1 human pancreatic cancer xenografts in NOD/SCID or NRG mice with Panitumumab labeled with Auger electron emitting, 111In or β-particle emitting, 177Lu

2020· article· en· W3104946688 on OpenAlexafffund
Sadaf Aghevlian, Zhongli Cai, David W. Hedley, Mitchell A. Winnik, Raymond M. Reilly

Bibliographic record

VenueEJNMMI Radiopharmacy and Chemistry · 2020
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaTerry Fox FoundationUniversity of TorontoCanadian Cancer Society
KeywordsPanitumumabDOTARadioimmunotherapyCancer researchRadionuclide therapyChemistryMolecular biologyMedicineMonoclonal antibodyCetuximabInternal medicineImmunologyBiologyAntibodyChelation

Abstract

fetched live from OpenAlex

Abstract Background Epidermal growth factor receptors (EGFR) are overexpressed on > 90% of pancreatic cancers (PnCa) and represent an attractive target for the development of novel therapies, including radioimmunotherapy (RIT). Our aim was to study RIT of subcutaneous (s.c.) PANC-1 human PnCa xenografts in mice using the anti-EGFR monoclonal antibody, panitumumab labeled with Auger electron (AE)-emitting, 111 In or β-particle emitting, 177 Lu at amounts that were non-toxic to normal tissues. Results Panitumumab was conjugated to DOTA chelators for complexing 111 In or 177 Lu (panitumumab-DOTA-[ 111 In]In and panitumumab-DOTA-[ 177 Lu]Lu) or to a metal-chelating polymer (MCP) with multiple DOTA to bind 111 In (panitumumab-MCP-[ 111 In]In). Panitumumab-DOTA-[ 177 Lu]Lu was more effective per MBq exposure at reducing the clonogenic survival in vitro of PANC-1 cells than panitumumab-DOTA-[ 111 In]In or panitumumab-MCP-[ 111 In]In. Panitumumab-DOTA-[ 177 Lu]Lu caused the greatest density of DNA double-strand breaks (DSBs) in the nucleus measured by immunofluorescence for γ-H2AX. The absorbed dose in the nucleus was 3.9-fold higher for panitumumab-DOTA-[ 177 Lu]Lu than panitumumab-DOTA-[ 111 In]In and 7.7-fold greater than panitumumab-MCP-[ 111 In]In. No normal tissue toxicity was observed in NOD/SCID mice injected intravenously (i.v.) with 10.0 MBq (10 μg; ~ 0.07 nmoles) of panitumumab-DOTA-[ 111 In]In or panitumumab-MCP-[ 111 In]In or in NRG mice injected i.v. with 6.0 MBq (10 μg; ~ 0.07 nmoles) of panitumumab-DOTA-[ 177 Lu]Lu. There was no decrease in complete blood cell counts (CBC) or increased serum alanine aminotransferase (ALT) or creatinine (Cr) or decreased body weight. RIT inhibited the growth of PANC-1 tumours but a 5-fold greater total amount of panitumumab-DOTA-[ 111 In]In or panitumumab-MCP-[ 111 In]In (30 MBq; 30 μg; ~ 0.21 nmoles) administered in three fractionated amounts every three weeks was required to achieve greater or equivalent tumour growth inhibition, respectively, compared to a single amount of panitumumab-DOTA-[ 177 Lu]Lu (6 MBq; 10 μg; ~ 0.07 nmoles). The tumour doubling time (TDT) for NOD/SCID mice with s.c. PANC-1 tumours treated with panitumumab-DOTA-[ 111 In]In or panitumumab-MCP-[ 111 In]In was 51.8 days and 28.1 days, respectively. Panitumumab was ineffective yielding a TDT of 15.3 days vs. 15.6 days for normal saline treated mice. RIT of NRG mice with s.c. PANC-1 tumours with 6.0 MBq (10 μg; ~ 0.07 nmoles) of panitumumab-DOTA-[ 177 Lu]Lu increased the TDT to 20.9 days vs. 11.5 days for panitumumab and 9.1 days for normal saline. The absorbed doses in PANC-1 tumours were 8.8 ± 3.0 Gy and 2.6 ± 0.3 Gy for panitumumab-DOTA-[ 111 In]In and panitumumab-MCP-[ 111 In]In, respectively, and 11.6 ± 4.9 Gy for panitumumab-DOTA-[ 177 Lu]Lu. Conclusion RIT with panitumumab labeled with Auger electron-emitting, 111 In or β-particle-emitting, 177 Lu inhibited the growth of s.c. PANC-1 tumours in NOD/SCID or NRG mice, at administered amounts that caused no normal tissue toxicity. We conclude that EGFR-targeted RIT is a promising approach to treatment of PnCa.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.318
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.029
GPT teacher head0.342
Teacher spread0.313 · 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 teacher head, not a consensus.

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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Citations18
Published2020
Admission routes2
Has abstractyes

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