Abstract LB130: Combination of IGF-1R targeted alpha therapy with Olaparib results in synergistic efficacy against colorectal and lung cancer xenografts
Bibliographic record
Abstract
Abstract Objectives: FPI-1434 is a targeted alpha-particle therapeutic consisting of an IGF-1R targeting antibody radiolabeled with Actinium-225. The primary mechanism of action for FPI-1434 is induction of double strand DNA breaks (DSB) in targeted tumors resulting in cell death. Poly (ADP-ribose) polymerase (PARP) is part of the cellular mechanism that repairs DSB. In cancer patients with genetic defects in DSB repair (eg. BRCA1/2), the PARP pathway becomes a primary repair system and its inhibition results in cell death. This mechanism has been leveraged as a therapy against DNA-repair deficient tumors leading to FDA-approval of PARP inhibitors (PARPi) including Olaparib. Treatment with PARPi to block repair of DNA damage driven by FPI-1434 may act synergistically to increase the lethal DNA damage load. To that end, Fusion has performed studies to combine FPI-1434 and Olaparib against tumor models with no pre-disposing defects in DNA repair. Methods: Colorectal (Colo-205) or lung (A549) cancer xenografts were established in Balb/c nude mice. For efficacy studies, a dose combination matrix for FPI-1434 and Olaparib was tested. FPI-1434 was dosed (i.v.) once at 20-200 nCi followed with Olaparib (i.p.) at doses of 0-50 mg/kg. Olaparib was dosed 24h after FPI-1434 using a 5 day on/2 day off schedule (5 mice/group). DSB formation (γH2AX) and apoptosis (cleaved caspase 3) were evaluated in treated tumors by IHC staining. Results: DSB formation and induction of apoptosis were detected in FPI-1434-treated tumors in a time and dose dependent manner. DSB formation was observed in all areas of tumor containing intact or apoptotic cancer cells confirming FPI-1434 mechanism. In tumor efficacy studies, Olaparib had no single-agent efficacy in the Colo-205 or A549 models. Single doses of FPI-1434 at 20 nCi had no effect on Colo-205 tumors, suppressed growth at 50 nCi and caused regression at 100 nCi. Combination efficacy was seen in the 20 and 50 nCi dose groups, including Olaparib. Doses of 20 nCi FPI-1434 and 25 mg/kg Olaparib had the strongest combined effect in this model. In the A549 model, single doses of FPI-1434 had no effect at 20 or 50 nCi, caused growth suppression at 100 nCi and regression at 200 nCi. Combination efficacy was seen in the 20, 50 and 100 nCi dose groups, including Olaparib. Doses of 50 nCi FPI-1434 and 25 mg/kg Olaparib had the strongest combined effect in this model. In general, the strongest efficacy was observed by combining ineffective single-agent doses of the two compounds. Strong efficacy of high dose FPI-1434 masked observable combination effects suggesting that FPI-1434 was the therapeutic driver. Conclusions: Olaparib co-dosing enhanced FPI-1434 efficacy which supports consideration of this combination for clinical use. Ineffective single-agent doses, when combined, resulted in synergistic efficacy in both Colo-205 and A549 models suggesting that the mechanism can be applied to multiple cancer types where predisposing mutations in DNA repair are lacking. The strongest combination effect appeared to occur at the low single-agent doses suggesting that PARP inhibition may potentiate efficacy at lower clinical doses of FPI-1434. Citation Format: Meiduo Hu, John Forbes, Ryan Simms, Yaryna Storozhuk, Eric Burak, John Valliant. Combination of IGF-1R targeted alpha therapy with Olaparib results in synergistic efficacy against colorectal and lung cancer xenografts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB130.
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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 | 0.001 |
| 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".