A Membrane Fluidization Strategy Significantly Boosts Photodynamic Therapy and Antitumor Immunity of Porphyrin-Lipid Nanoparticles
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Porphysomes (PS) are self-assembled porphyrin–lipid nanoparticles with intrinsic multifunctionality for cancer theranostics. We recently discovered that incorporating EDTA-conjugated lipids (EDTA-lipids) into lipid nanoparticle formulations significantly enhances intracellular uptake by modulating the cell membrane fluidity. To retain the favorable in vivo properties of PS while improving intracellular porphyrin delivery for effective photodynamic therapy (PDT), we developed a dual cellular- and vascular-enriched porphysome (DE-PS) containing 30 mol % cholesterol, 5 mol % PEG2000-DSPE, 27 mol % pyro-lipid, and 38 mol % EDTA-lipid. DE-PS demonstrated favorable pharmacokinetics ( t 1 / 2 β = 7.5 h), robust photostability (>99% fluorescence quenching), and strong serum stability over 24 h (>85% fluorescence quenching retained). Compared to PS, DE-PS resulted in an 11-fold increase in KB cancer cell uptake and achieved >95% PDT-induced cell death, in contrast to <5% with PS. Intravital imaging showed enhanced intratumoral porphyrin activation in DE-PS-treated mice, with stronger fluorescence signals observed in tumor vasculature and necrotic regions, leading to superior in vivo PDT efficacy across all drug-light-intervals. Notably, while low-dose PDT (25 J/cm 2 ) with DE-PS had minimal impact on CT-26 tumor growth in immunodeficient NSG mice, it resulted in marked tumor suppression and prolonged survival in immunocompetent BALB/c mice, highlighting the importance of PDT-induced immune activation in the therapeutic response. A single DE-PS PDT treatment led to durable tumor-free survival exceeding 90 days. Upon CT-26 tumor rechallenge, previously cured mice rejected tumor regrowth, demonstrating development of long-lasting immunity without utilizing additional immunostimulants. This study highlights DE-PS as a promising next-generation porphysome-based photosensitizer platform for effective cancer phototherapy and immune modulation.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".