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Record W4393085465 · doi:10.1158/1538-7445.am2024-6030

Abstract 6030: Optimizing the therapeutic index of targeted α-particle radioimmuotherapy (TART) of HER2-positive breast cancer tumors in NRG mice with 225Ac-labeled trastuzumab

2024· article· en· W4393085465 on OpenAlexaff
Misaki Kondo, Zhongli Cai, Conrad Chan, Raymond M. Reilly

Bibliographic record

VenueCancer Research · 2024
Typearticle
Languageen
FieldMedicine
TopicRadiopharmaceutical Chemistry and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTrastuzumabMedicineCancerBreast cancerOncologyInternal medicine

Abstract

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Abstract Introduction: Our aim was to optimize the therapeutic index of TART of HER2-positive BC in NRG mice by studying the effectiveness and normal tissue toxicity of trastuzumab IgG, F(ab’)2 or Fab modified with DOTA for complexing the α-particle emitter, 225Ac. Methods: The toxicity of [225Ac]Ac-DOTA-trastuzumab IgG, F(ab’)2 and Fab were assessed in NRG mice (n=5) injected i.v. with 2 and 4 kBq (total 80 μg) separated by 8 d. Body weight was monitored and complete blood cell (CBC) counts and alanine aminotransferase (ALT) and creatinine (CRE) were measured at 14 d post-injection (p.i.). TART was performed in NRG mice (n=7) with s.c. HER2-positive 164/8-1B/H2N.luc+ xenografts injected i.v. with 2 and 4 kBq (total 80 μg) separated by 8 d of [225Ac]Ac-DOTA-trastuzumab IgG, F(ab’)2 or Fab. Control mice received irrelevant [225Ac]Ac-DOTA-IgG, trastuzumab or saline. The tumor growth index (TGI=tumor volume/initial tumor volume) was measured and Kaplan-Meier median survival estimated. Tumor and normal tissue uptake (%ID/g) of [225Ac]Ac-DOTA-trastuzumab IgG, F(ab’)2 and Fab (4 kBq) in tumor-bearing NRG mice were measured up to 14 d p.i.. Results: [225Ac]Ac-DOTA-trastuzumab F(ab’)2 and Fab caused no decrease in CBC, while [225Ac]Ac-DOTA-trastuzumab IgG decreased white blood cells by 4.5-fold, platelets by 7.5-fold, red blood cells by 1.2-fold and hematocrit by 1.2-fold compared to saline-treated mice. [225Ac]Ac-trastuzumab F(ab’)2 or Fab caused no increase in ALT or CRE. Body weight was not decreased in all groups of mice. [225Ac]Ac-DOTA-trastuzumab IgG, F(ab’)2 or Fab inhibited tumor growth (TGI at 15 d = 2.5, 1.8, and 1.9, respectively) vs. saline or trastuzumab (TGI= 6.3 and 5.2; P=0.0047 and 0.0028). Median survival was increased to 46 d for mice treated with [225Ac]Ac-DOTA-trastuzumab F(ab’)2 vs. 29 d for Fab (P=0.008), 22 d for IgG (P=0.0005) and 15 d for saline (P=0.0005). Median survival for mice treated with [225Ac]Ac-DOTA-IgG was 20 d and for trastuzumab was 22 d. Tumor uptake of [225Ac]Ac-DOTA-trastuzumab IgG and F(ab’)2 at 48 h p.i. were 10.6 ± 0.6 and 8.7 ± 0.8, respectively, while uptake of [225Ac]Ac-DOTA-trastuzumab Fab at 18 h p.i. was 3.1 ± 0.5 %ID/g. Elimination from the blood was slowest for [225Ac]Ac-DOTA-trastuzumab IgG followed by F(ab’)2 then Fab. Spleen and liver uptake were greatest for [225Ac]Ac-DOTA-trastuzumab IgG but much lower for F(ab’)2 and Fab. Kidney uptake was highest for [225Ac]Ac-DOTA-trastuzumab Fab. Conclusion: [225Ac]Ac-DOTA-trastuzumab F(ab’)2 provided the highest therapeutic index, inhibiting tumor growth and improving survival while minimizing toxicity. TART with [225Ac]Ac-DOTA-trastuzumab F(ab’)2 is a promising new treatment for HER2-positive BC that could be more effective than trastuzumab. Citation Format: Misaki Kondo, Zhongli Cai, Conrad Chan, Raymond M. Reilly. Optimizing the therapeutic index of targeted α-particle radioimmuotherapy (TART) of HER2-positive breast cancer tumors in NRG mice with 225Ac-labeled trastuzumab [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6030.

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 score0.001
Threshold uncertainty score0.003

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 integrity0.0000.001
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 head0.054
GPT teacher head0.417
Teacher spread0.363 · 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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Citations0
Published2024
Admission routes1
Has abstractyes

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