Platelet Membrane-Coated Poly (Lactic-Co-Glycolic Acid) Nanoparticles as a Targeting Drug Delivery System for Multidrug-Resistant Breast Cancer
Bibliographic record
Abstract
Bomin Song,1,* Young-Guk Na,1,* Byung Jin Kim,1,* Minki Jin,1 Yo Han Song,1 Da-Eun Kim,1 Suyeon Hwang,1 Jong-Suep Baek,2 Hong-Ki Lee,3 Cheong-Weon Cho1 1College of Pharmacy, Chungnam National University, Daejeon, 31434, Republic of Korea; 2Department of Bio-Health Convergence, Kangwon National University, Chuncheon, 24341, Republic of Korea; 3College of Veterinary Medicine, Chungbuk National University, Chungbuk, 28644, Republic of Korea*These authors contributed equally to this workCorrespondence: Cheong-Weon Cho, Email chocw@cnu.ac.kr Hong-Ki Lee, Email hongki.lee@cbnu.ac.krIntroduction: Paclitaxel (PTX), widely used chemotherapeutic agent, is limited by poor solubility, P-glycoprotein (P-gp) mediated efflux, and non-specific toxicity. To overcome these challenges, we developed a triple-functionalized nanocarrier system incorporating poly(lactide-co-glycolide) (PLGA)-based nanoparticles (PNs), D-α-tocopheryl polyethylene glycol succinate (TPGS) for P-gp inhibition, and platelet membrane (PM) coating for targeted tumor delivery.Methods: The PM-coated TPGS-modified PNs with PTX (PTPNs) was characterized by particle size analysis, transmission electron microscopy (TEM), and protein assay to confirm PM coating. In vitro drug release studies were conducted under acidic conditions mimicking the tumor microenvironment. Cellular assays were performed to evaluate cytotoxicity and drug efficacy in multidrug-resistant MCF-7/ADR cells. In vivo biodistribution and xenograft studies assessed tumor accumulation and therapeutic outcomes.Results: PTPNs exhibited a particle size of 221 ± 2 nm with a PDI of 0.090 ± 0.020 and a zeta potential of – 30.5 ± 0.3 mV, indicating a homogeneous particle distribution and successful PM coating. The optimal PM-to-PLGA weight ratio was determined to be 0.005, which ensured structural stability and uniform coating in physiological conditions. Sustained PTX release was observed in acidic conditions, mimicking the tumor microenvironment. Cellular assays showed a 17-fold reduction in PTX IC50 in MCF-7/ADR cells compared to free PTX, attributed to the synergistic effects of TPGS-mediated P-gp inhibition and PM–based tumor targeting. In vivo, PTPNs demonstrated enhanced tumor accumulation and significantly reduced tumor burden, with final tumor volume 2.6-fold lower than that of TPNs and 3.6-fold lower than that of the PTX commercial product (Taxol®)-treated group. Tumor necrosis factor-α (TNF-α) levels were also reduced, reflecting decreased tumor-promoting cytokine activity.Conclusion: The PTPNs enhanced PTX delivery by improving tumor specificity, overcoming multidrug resistance, and reducing systemic toxicity. These results suggested the potential of this biomimetic approach to advance cancer therapy.Keywords: paclitaxel, platelet membrane, Poly(lactide-co-glycolide), nanoparticles, multidrug resistance, cancer therapy
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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) | 0.000 | 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 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".