Potential of Ruthenium as a photosensitizer in radiation-activated Photodynamic Therapy (radioPDT)
Bibliographic record
Abstract
In Photodynamic Therapy (PDT), light is used to activate photosensitizers (PS) to generate reactive oxygen species (ROS) as a cell-killing mechanism. However, PDT's application is limited to the surface and small size tumors because of the inefficiency of light in penetrating larger and deep-seated tumors. We have developed novel nanoparticles (NPs) that can be activated by radiation, a process known as the radiation-activated PDT (radioPDT). In our studies we developed a new variant of pegylated poly-lactic-co-glycolic (PEG-PLGA) encapsulated nanoscintillators (NSC) and ruthenium-based photosensitizer (Ru/rPDT) that exhibits minimal cell toxicity while having significant cell killing effect upon radiation activation. Our data suggest that radioPDT with Ru/rPDT can be a more effective strategy than previous protoporphyrin-based iterations in treating many deep-seated tumors. Introduction and Background : Toxicity and normal tissue damage are limiting factors for the application of radiotherapy (RT) where higher doses of radiation is required to cure deep-seated tumor such as prostate cancer. In Photodynamic Therapy (PDT), photosensitizers (PS) are activated by light to generate reactive oxygen species (ROS) to kill tumor cells. However, the main limitation of the current PDT is the limited tissue penetration of PS-activating light. Thus, PDT cannot be effectively used to treat deep-seated and larger size tumors. RT has higher tissue penetration depth, making the radiation-activated PDT (radioPDT) advantageous in treating deep seated tumors. We aim to develop novel radioPDT nanoparticles (NP) with more efficient anti-cancer therapeutic effect in vitro and in vivo to enhance targeted radiotherapy. Methods: LaF3:Ce 3+ nanoscintillators (NSCs) were synthesized in a single step wet chemistry technique. The NSCs along with Ruthenium-based PS (Ru) with matching excitation/emission spectra were successfully encapsulated in PEG-PLGA. UV-Vis spectrometry and inductively coupled plasma mass spectrometry (ICP-MS) were used to confirm the presence of NSCs and Ru, and dynamic light scattering (DLS) and transmission electron microscopy (TEM) were used to determine the size of NP. Singlet oxygen generation was measured by Singlet Oxygen Sensor Green (SOSG) and direct singlet oxygen fluorescence. RadioPDT therapeutic potential was evaluated in PC3 prostate cancer cell under radiation by Alamar Blue cell viability assay. Results: UV-Vis spectrometry and ICP-MS determined the successful PEG-PLGA encapsulation of NSC and Ru. The TEM imaging confirmed the encapsulation NSC inside the nanocarrier PEG-PLGA. TEM and DLS measurements showed the size of radioNP ranged from 90nm to 150nm with polydispersity index of <0.3. Singlet oxygen generation by Ru/rPDT NPs was greater than PPIX based radioPDT (PPIX/rPDT) NPs. Furthermore, the direct measurement of singlet oxygen generation with fluorescence spectroscopy of Ru/rPDT showed preserved singlet oxygen yield and no evidence of quenching. The Ru/rPDT and PPIX/rPDT showed minimal PC3 cell cytotoxicity in dark conditions. The PC3 cell killing efficiency was comparable between Ru/rPDT and PPIX/rPDT either under light or radiation activation. Conclusion: Our in vitro studies show Ru/rPDT significantly increases anti-cancer therapeutic effect of RT, with minimal toxicity. Future studies will refine in vivo NP biodistribution, dosing, and RT dose/fractionation schemes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".