Nanocomposite liposomes for pH-controlled porphyrin release into human prostate cancer cells.
German V FuentesEric N DoucetAlyson AbrahamNikki K RodgersFelix AlonsoNelson EucedaMichael H QuinonesPenelope A RiascosKristelle PierreNuhash H SarkerManya Dhar-MascarenoMircea CotletKim KisslingerFernando CaminoMingxing LiFang LuRuomei GaoPublished in: RSC advances (2020)
It is both challenging and desirable to have drug sensitizers released at acidic tumor pH for photodynamic therapy in cancer treatment. A pH-responsive carrier was prepared, in which fumed silica-attached 5,10,15,20-tetrakis(4-trimethylammoniophenyl)porphyrin (TTMAPP) was encapsulated into 1,2-dioleoyl- sn-glycero -3-phosphocholine (DOPC) nanocomposite liposomes. The sizes of agglomerates were determined by dynamic light scattering to be 115 nm for silica and 295 nm for silica-TTMAPP-DOPC liposomes. Morphological changes were also found in TEM images, showing liposome formation at pH 8.5 but collapse upon silanol protonation. TTMAPP release is enhanced from 13% at pH 7.5 to 80% at pH 2.3, as determined spectrophotometrically through dialysis membranes. Fluorescence emission of TTMAPP encapsulated in the dry film of liposomes was reduced to half at pH 8.6 when compared to that at pH 5.4, while the production of singlet oxygen was quintupled at pH 5.0 compared to pH 7.6. Upon treatment of human prostate cancer cells with liposomes containing 6.7 μM, 13 μM, 17 μM and 20 μM TTMAPP, the cell viabilities were determined to be 60%, 18%, 20% and 5% at pH 5.4; 58%, 30%, 25% and 10% at pH 6.3; and 90%, 82%, 68% and 35% at pH 7.4, respectively. Light-induced apoptosis in cancerous cells was only observed in the presence of liposomes at pH 6.3 and pH 5.4 but not at pH 7.4, as indicated by chromatin condensation.
Keyphrases
- photodynamic therapy
- induced apoptosis
- drug delivery
- endothelial cells
- chronic kidney disease
- gold nanoparticles
- drug release
- cell death
- transcription factor
- signaling pathway
- optical coherence tomography
- convolutional neural network
- quantum dots
- single molecule
- combination therapy
- fluorescence imaging
- highly efficient