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Adjuvant Auger Electron-Emitting Radioimmunotherapy with [<sup>111</sup>In]In-DOTA-Panitumumab in a Mouse Model of Local Recurrence and Metastatic Progression of Human Triple-Negative Breast Cancer

2023· article· en· W4388834513 on OpenAlexafffund
Valerie J. Facca, Zhongli Cai, Anthony Ku, Constantine J. Georgiou, Raymond M. Reilly

Bibliographic record

VenueMolecular Pharmaceutics · 2023
Typearticle
Languageen
FieldMedicine
TopicRadiopharmaceutical Chemistry and Applications
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkUniversity of Toronto
FundersLeslie Dan Faculty of Pharmacy, University of TorontoNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchTerry Fox Foundation
KeywordsPanitumumabRadioimmunotherapyDOTAMedicineCancer researchOncologyNuclear medicineCancerInternal medicineColorectal cancerMonoclonal antibodyKRASImmunologyAntibodyIn vivoBiology

Abstract

fetched live from OpenAlex

Triple-negative breast cancer (TNBC) has a high risk for recurrence and metastasis. We studied the effectiveness of Auger electron (AE) radioimmunotherapy (RIT) with antiepidermal growth factor receptor (EGFR) panitumumab conjugated with DOTA complexed to 111 In ([ 111 In]In-DOTA-panitumumab) for preventing metastatic progression after local treatment of 231/LM2–4 Luc+ human TNBC tumors in the mammary fat pad of NRG mice. Prior to RIT, the primary tumor was resected, and tumor margins were treated with X-irradiation (XRT; 5 days × 6 Gy/d). RIT was administered 1 day post-XRT by intravenous injection of 26 MBq (15 μg) or 2 × 10 MBq (15 μg each) separated by 7 d. These treatments were compared to tumor resection with or without XRT combined with DOTA-panitumumab (15 μg) or irrelevant [ 111 In]In-DOTA-IgG 2 (24 MBq; 15 μg), and efficacy was evaluated by Kaplan–Meier survival curves. The effect of [ 111 In]In-DOTA-panitumumab (23 MBq; 15 μg) after tumor resection without local XRT was also studied. Tumor resection followed by XRT and RIT with 26 MBq [ 111 In]In-DOTA-panitumumab significantly increased the median survival to 35 d compared to tumor resection with or without XRT (23–24 d; P < 0.0001). Local treatment with tumor resection and XRT followed by 2 × 10 MBq of [ 111 In]In-DOTA-panitumumab, DOTA-panitumumab, or [ 111 In]In-DOTA-IgG 2 did not significantly improve median survival (26 days for all treatments). RIT alone with [ 111 In]In-DOTA-panitumumab postresection of the tumor without XRT increased median survival to 29 days, though this was not significant. Despite significantly improved survival in mice treated with tumor resection, XRT, and RIT with [ 111 In]In-DOTA-panitumumab, all mice eventually succumbed to advanced metastatic disease by 45 d post-tumor resection. SPECT/CT with [ 111 In]In-DOTA-panitumumab, PET/MRI with [ 64 Cu]Cu-DOTA-panitumumab F(ab′) 2, and PET/CT with [ 18 F]FDG were used to detect recurrent and metastatic disease. Uptake of [ 111 In]In-DOTA-panitumumab at 4 d p.i. in the MFP tumor was 26.8 ± 9.7% ID/g and in metastatic lymph nodes (LN), lungs, and liver was 34.2 ± 26.9% ID/g, 17.5 ± 6.0% ID/g, and 9.4 ± 2.4%ID/g, respectively, while uptake in the lungs (6.0 ± 0.9% ID/g) and liver (5.2 ± 2.9% ID/g) of non-tumor-bearing NRG was significantly lower ( P < 0.05). Radiation-absorbed doses in metastatic LN, lungs, and liver were 9.7 ± 6.1, 6.4 ± 2.1, and 10.9 ± 2.7 Gy, respectively. In conclusion, we demonstrated that RIT with [ 111 In]In-DOTA-panitumumab combined with tumor resection and XRT significantly improved the survival of mice with recurrent TNBC. However, the aggressive nature of 231/LM2–4 Luc+ tumors in NRG mice may have contributed to the tumor recurrence and progression observed.

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 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 score0.307
Threshold uncertainty score0.861

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)0.0000.000

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 head0.038
GPT teacher head0.384
Teacher spread0.347 · 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.

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".

Quick stats

Citations7
Published2023
Admission routes2
Has abstractyes

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