Abstract PO-100: Theragnostic tumor-targeted manganese dioxide-loaded polymer-lipid nanoparticles for magnetic resonance image-guided radiation therapy
Bibliographic record
Abstract
Abstract Background: Magnetic resonance image-guided radiation therapy (MRgRT) is a new-generation approach to improving treatment outcomes by allowing real-time precise tumor delineation that guides the radiation. However, the existing gadolinium-based contrast agents (GBCAs) are insufficient for MRgRT due to their severe side effects and rapid clearance from the tumor that requires multiple injections to maintain the signal. In addition, tumor hypoxia induced radiation resistance, which attenuates the RT efficacy. To date, there is no FDA-approved contrast agent with high safety and efficacy profile exhibiting both MR signal enhancement and RT sensitization capabilities. Based on our previous findings that manganese-dioxide nanoparticles (MDNP) can convert tumoral ROS (H2O2) into O2 to reduce hypoxia and sensitize RT, we propose the design of a novel tumor-targeting manganese-dioxide nanoparticle (MDNP) with dual MRI and RT enhancement functionalities. In this work, we evaluate the safety profile, biodistribution, in vivo clearance, MR contrast enhancement, and radiation sensitization effect of the MDNPs. Methods: Terpolymer-based MDNP (T-MDNP) were prepared by loading MnO2 precursor in a polymer-lipid matrix. Physicochemical properties and stability of NPs were determined by TEM, DLS, and zeta potential measurements. In vitro cellular uptake by cancer cells was measured via confocal microscopy. The biocompatibility and safety of the NPs was examined in vitro and in vivo. Tissue distribution, clearance, and tumor retention of T-MDNPs was evaluated using MRI and ICP. The tumoral MR signal enhancement by T-MDNP as a function of time was measured and compared with Gadavist™ (gadobutrol) in murine tumor models with human MDA-MB-231 breast or prostate PC3 xenografts. The ability of NPs to modulate tumor microenvironment (TME) and enhance RT efficacy was also evaluated. Results: The prepared T-MDNPs were 120 nm in size and exhibited excellent storage stability at room temperature and 4°C. The NPs showed negligible hemolysis effect suggesting their suitability for intravenous (IV) injection. As a result of in situ generation of Mn+2 ions via the reaction with tumoral ROS, a single dose of 70 μmole Mn/kg of body weight of T-MDNP increased tumor T1 signal by up to 1.4-fold and maintained it up to 4 hrs, while Gadavist™ was eliminated in about 30 min. The NPs were completely cleared from major organs in 72 hrs, as determined by MRI and ICP. Combination of NP treatments with RT resulted in significantly increased median survival time by 2-fold in human PC3 prostate model and 5-fold in human breast tumor model. Conclusions: Our results have demonstrated that the T-MDNPs are safe and effective as a dual MR contrast agent and radiation sensitizer. This system is promising for precise tumor margin delineation, maintaining MR signal in tumor for a duration needed for MRgRT, and improving RT efficacy. These properties make it an excellent candidate and the first-in-class entity that can be utilized with MRgRT. Citation Format: Charles Yen, Azhar Z. Abbasi, Chunsheng He, Mohammad Ali Amini, Hoyin Lip, Michael Rauth, Xiao Yu Wu. Theragnostic tumor-targeted manganese dioxide-loaded polymer-lipid nanoparticles for magnetic resonance image-guided radiation therapy [abstract]. In: Proceedings of the AACR Virtual Special Conference on Radiation Science and Medicine; 2021 Mar 2-3. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(8_Suppl):Abstract nr PO-100.
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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".