Abstract 584: Preclinical efficacy and safety of [161Tb]Tb-labeled anti-nectin-4 radioimmunoconjugate as theranostic against triple-negative breast cancer (TNBC) and non-small cell lung cancer (NSCLC)
Bibliographic record
Abstract
Abstract Purpose: Targeted radioligand therapy (RLT) and radioimmunotherapy (RIT) have emerged as effective and safe treatment modalities for metastatic cancers. Nectin-4 is a Ca2+-independent immunoglobulin-like cell adhesion molecule. Aberrant expression of Nectin-4 is observed in many cancers notably TNBC and NSCLC. No RLT/RIT is approved/in advanced clinical development against TNBC and NSCLC. For the first time, we report the efficacy and safety of 161Tb-labeled anti-Nectin-4 antibody ([161Tb]Tb-DOTA-N4MU01) against Nectin-4 positive TNBC and NSCLC mouse models. Procedures: Nectin-4-expressing mouse syngeneic cell lines for TNBC (4T1.Nectin-4 and E0771.Nectin-4) and NSCLC (LLC.Nectin-4 and CMT167.Nectin-4) were obtained by stable transduction or transfection. Nectin-4 expression and binding affinity of immunoconjugates were assessed by flow cytometry and radioligand binding assays, with internalization studied using live-cell imaging. Pharmacokinetics and safety of the radioligand were evaluated in healthy female Balb/C mice, with tumor uptake assessed by SPECT/CT and biodistribution in tumor-bearing mice. The efficacy of the radioligand was assessed in mouse xenograft models of Nectin-4-expressing human cell line, MDA-MB468, and mouse syngeneic cell lines 4T1.Nectin-4 (immune checkpoint blockade therapy (ICBT) resistant), E0771.Nectin-4, CMT167.Nectin-4, and LLC.Nectin-4. Results: Nectin-4 expression on syngeneic cell lines was high. DOTA conjugation did not affect the internalization of N4MU01 (p ˃ 0.999) while immunoconjugates retained strong binding affinities to human Nectin-4 (≤ 11 nM). 161Tb was stably chelated to DOTA-N4MU01 with yield and purity ˃ 95 %. The clearance half-life of [161Tb]Tb-DOTA-N4MU01 was 120 ± 20 h while a dose of 2x 5 MBq administered intravenously, and 7 d apart was well tolerated over 28 d. Tumor targeting was specific with tumor-to-muscle uptake ratios of 7.7 and 6.7 for CMT167.Nectin-4 and 4T1.Nectin-4 at 24 h post-injection. In 4T1.Nectin-4 model, single dose radioligand at 2.5 MBq and 5 MBq and a repeated dose at 2x 5 MBq showed significant dose-dependent anti-tumor efficacy and survival (p ≤ 0.0021) compared with saline and N4MU01 (25 µg), with 2x 5MBq of radioligand producing complete remission in 20 % of mice. Anti-PD-L1 ICBT had no anti-tumor effect (p = 1166) on this model. A dose of 2x 5 MBq of radioligand resulted in significant anti-tumor effects and survival compared with saline and N4MU01 (25 µg), in aggressive E0771.Nectin-4 (p ≤ 0.0316), CMT167.Nectin-4 (p ≤ 0.0236), LLC.Nectin-4 (p ≤ 0.0097), and MDA-MB-468 (p ≤ 0.0.0017) xenograft models. Conclusions: Our findings reveal the clinical potential of [161Tb]Tb-DOTA-N4MU01 as an effective and safe theranostic against Nectin-4-expressing TNBC and NSCLC, even for patients who do not respond to ICBT Citation Format: Fabrice Ngoh Njotu, Hanan Babeker, Jessica Pougoue Ketchemen, Emmanuel Nwangele, Anjong Tikum, Nikita Henning, He Dong, Nava Hassani, Alissar Monzer, Dede Api Fon, Chrysantus Njobinkir Bimela, Therese Mercado, Franco Vizeacoumar, Dennis Elema, Michiel Van de Voorde, Maarten Ooms, Maruti Chandra Uppalapati, Humphrey Fonge. Preclinical efficacy and safety of [161Tb]Tb-labeled anti-nectin-4 radioimmunoconjugate as theranostic against triple-negative breast cancer (TNBC) and non-small cell lung cancer (NSCLC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 584.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".