Abstract 567: Effectiveness of [225Ac]Ac-labeled anti-MUC-16 radioimmunconjugate against CA125 expressing pancreatic and ovarian cancer xenografts
Bibliographic record
Abstract
Purpose: Cancer biomarkers like CA125 (MUC-16) are targets for the selective delivery of toxic radiation and/or cytotoxic molecules to tumor loci. MUC-16 is overexpressed in 80% of epithelial ovarian cancer (EOC) and 65% of pancreatic ductal adenocarcinomas (PDAC). Prognosis of EOC and PDAC has remained poor with 5-year survival rate of between 30-50% and 15-20% for EOC & PDAC respectively, hence, the need for new treatment approaches. Our lab has developed a fully human monoclonal antibody (mAb) that binds specifically to MUC-16 and demonstrated the effectiveness of [89Zr]Zr-DFO-MUC-16 as a PET imaging agent. Here, we have developed [225Ac]Ac-Macropa-MUC-16 and investigated its effectiveness against CA125 expressing EOC and PDAC cell derived xenografts (CDX) and patient derived xenografts (PDX). Method: The anti-MUC-16 mAb was conjugated to macrocyclic bifunctional chelator Macropa-NCS and radiolabeled with [225Ac]AcNO3 to produce [225Ac]Ac-Macropa-MUC-16 radioimmunoconjugate (RIC). Quality control assays were conducted to evaluate the integrity of the antibody, stability of the RIC and binding to MUC-16. We developed MUC-16 positive PDAC CDX (SW1990) and PDX (medium MUC-16 expression) and EOC PDXs (high and low MUC-16 expression).Biodistribution studies of [225Ac]Ac-Macropa-MUC-16 was performed in non-tumor bearing mice at different timepoints and used to project organ doses using OLINDA. Groups of tumor-bearing mice were treated using 2 x of 13 kBq of the RIC at day 0 and 10 and tumor growth was monitored. [225Ac]Ac-Macropa-Rituximab was used as a control RIC.Additionally, safety of the RIC was assessed after administration of 1 or 2 doses of the agent to healthy mice followed by clinical chemistry, CBC and histopathology. Results: 16.67% of CDX (SW1990) treated with 2 x 13 kBq of the RIC had complete remission (CR). The remaining 83.33 % in this group had tumor growth suppression for ≥ 50 days post treatment and never reached endpoint (≥ 1500 mm3), while saline and control RIC groups reached end point by day 33.[225Ac]Ac-Macropa-MUC-16 was very effective against high and medium MUC16 expressing PDAC and EOC PDXs, respectively heading to 100% CRs while median survival for control groups was 36 (PDAC) and 47 (EOC) days. The RIC was less effective at inhibiting EOC PDX with low MUC-16 expression. For this, the % tumor growth inhibition (% TGI) was 94.5±6.8% and 84.7±11% at the day 12 and 21, respectively. Although CBC & clinical chemistry show no safety issues, histopathological studies showed mild to moderate pathologies in the liver and spleen for mice exposed to 2 doses of 15 kBq of the RIC. . Conclusion: [225Ac]Ac-Macropa-MUC-16 is effective against MUC-16 expressing EOC and PDAC xenografts. The exciting therapeutic potential is however dependent on the expression level of MUC-16 and points to the significance of heterogeneity within and between tumor types in cancers. Citation Format: Emmanuel Nwangele,Hanan Babeker,Alyssar Monzer,Fabrice Ngoh Njotu,Jessica Pougoue Ketchemen,Alireza Doroudi,Florence-Anjong Tikum,Nikita Henning,Emina Torlakovic,Maruti Uppalapati,Humphrey Fonge. Effectiveness of [225Ac]Ac-labeled anti-MUC-16 radioimmunconjugate against CA125 expressing pancreatic and ovarian cancer xenografts [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 567.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".