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Naunyn-Schmiedeberg's archives of pharmacology · 2026

Mechanistic and AI-assisted evaluation of paclitaxel-loaded HSPC liposomes for targeted breast cancer therapy.

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Shenoy Vikram Subraya, Nayak Prashant, Pillappan Ramkumar, Zanwar Shrinivas R, Bhosale Yogesh H, Bhuyar Devendra L, Sharma Mukesh Chandra, Hajare Sunil Tulshiram

Аннотация

Paclitaxel (PCL) faces translational barriers including poor aqueous solubility (log P = 3.0) and dose-limiting toxicity. Hydrogenated soy phosphatidylcholine (HSPC) liposomes were engineered exploiting the lipid's high phase transition temperature (Tm ~ 52 °C) for membrane rigidity and sustained drug retention. Synthesized via thin-film hydration (HSPC:cholesterol:PCL = 7:2:0.1), nano-formulations achieved a mean diameter of 142.3 ± 8.7 nm and PDI of 0.178 ± 0.01 by dynamic light scattering, a zeta potential of - 28.4 ± 1.5 mV determined by electrophoretic light scattering, 87.6 ± 2.1% encapsulation efficiency, and controlled drug release (78.4 ± 5.2% over 72 h). Against MCF-7 breast adenocarcinoma cells, liposomal PCL demonstrated time-dependent cytotoxic amplification with IC₅₀ improving from 0.525 µg/mL (24 h) to 0.09 µg/mL (48 h)-54% superior to free PCL (IC₅₀ = 0.139 µg/mL). Mechanistic studies were conducted, revealing (i) 2.96-fold G2/M phase accumulation (63.23% vs. 21.38% control, p < 0.001), (ii) mitochondrial apoptosis with 2.8-fold caspase-3 and 3.1-fold caspase-9 activation, (iii) 4.2-fold enhanced cellular uptake, and (iv) anti-metastatic activity with 62% migration and 68% invasion inhibition. Complementary computational analyses included the following: principal component analysis (PCA) revealing multivariate separation of treatment groups (PC1, 78.3% variance; PC2, 16.4%); Grad-CAM visualization localizing morphological features associated with apoptosis; and exploratory Random Forest modeling demonstrating time and formulation type as primary determinants of cytotoxic potency. Three-month stability assessment showed minimal drift in physicochemical parameters (particle size, + 10.2%; encapsulation efficiency, - 6.3%), supporting formulation robustness for preclinical studies.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты