Novel Pyropheophorbide Phosphatydic Acids Photosensitizer Combined EGFR siRNA Gene Therapy for Head and Neck Cancer Treatment
Bibliographic record
Abstract
This study combined two novel nanomedicines, a novel LCP Pyro PA photodynamic therapy (PDT) and LCP EGFR siRNA gene therapy, to treat head and neck cancer. A novel photosensitizer, pyropheophorbide phosphatydic acids (Pyro PA), was first modified into Lipid-Calcium phosphate nanoparticles named LCP Pyro PA NPs, and targeted with aminoethylanisamide as a novel PDT photosensitizer. EGFR siRNA was encapsulated into LCP NPs to silence EGFR expression. Measured sizes of LCP EGFR siRNA NPs and LCP Pyro-PA NPs were 34.9 ± 3.0 and 20 nm respectively, and their zeta potentials were 51.8 ± 1.8 and 52.0 ± 7.6 mV respectively. In vitro studies showed that EGFR siRNA was effectively knocked down after photodynamic therapy (PDT) with significant inhibition of cancer growth. SCC4 or SAS xenografted nude mice were used to verify therapeutic efficacy. The LCP Control siRNA+PDT group of SCC4 and SAS showed significantly reduced tumor volume compared to the phosphate buffered saline (PBS) group. In the LCP-EGFR siRNA+LCP Pyro PA without light group and LCP EGFR siRNA + PBS with light group, SCC4 and SAS tumor volumes were reduced by ~140% and ~150%, respectively, compared to the PBS group. The LCP EGFR siRNA+PDT group of SCC4 and SAS tumor volumes were reduced by ~205% and ~220%, respectively, compared to the PBS group. Combined therapy showed significant tumor volume reduction compared to PBS, control siRNA, or PDT alone. QPCR results showed EGFR expression was significantly reduced after treatment with EGFR siRNA with PDT in SCC4 and SAS compared to control siRNA or PDT alone. Western blot results confirmed decreased EGFR protein expression in the combined therapy group. No toxic results were found in serum biomarkers. No inflammatory factors were found in heart, liver and kidney tissues. Results suggest that the novel LCP Pyro PA mediated PDT combined with LCP siEGFR NPs could be developed in clinical modalities for treating human head and neck cancer in the future.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".