BiochimieMolecular BiologyPeer-reviewed journal article
Cell-penetrating peptide and cationic liposomes mediated siRNA delivery to arrest growth of chronic myeloid leukemia cells in vitro
Vera V. VysochinskayaiD, Yana A. ZabrodskayaiD, Olesya V. DovbyshiD, Anton EmelyanoviD, Vladimir V. KlimenkoiD, Nikolay Knyazev, Ivan TerteroviD, Marya Egorova, Alexey A. BogdanoviD, Mikhail A. MasloviD, Andrey V. VasiniD, Michael DubinaiD
Abstract
Gene silencing through RNA interference (RNAi) is a promising therapeutic approach for a wide range of disorders, including cancer. Non-viral gene therapy, using specific siRNAs against BCR-ABL, can be a supportive or alternative measure to traditional chronic myeloid leukemia (CML) tyrosine kinase inhibitor (TKIs) therapies, given the prevalence of clinical TKI resistance. The main challenge for such approaches remains the development of the effective delivery system for siRNA tailored to the specific disease model. The purpose of this study was to examine and compare the efficiency of endosomolytic cell penetrating peptide (CPP) EB1 and PEG2000-decorated cationic liposomes composed of polycationic lipid 1,26-bis(cholest-5-en-3-yloxycarbonylamino)-7,11,16,20-tetraazahexacosane tetrahydrochloride (2X3) and helper lipid 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE) for anti-bcr-abl siRNA delivery into the K562 human CML cell line. We show that both EB1 and 2X3-DOPE-DSPE-PEG2000 (0.62% mol.) liposomes effectively deliver siRNA into K562 cells by endocytic mechanisms, and the use of liposomes leads to more effective inhibition of expression of the targeted gene (BCR-ABL) and cancer cell proliferation. Taken together, these findings suggest that PEG-decorated cationic liposomes mediated siRNA delivery allows an effective antisense suppression of certain oncogenes, and represents a promising new class of therapies for CML.
- organism: human
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: drug response / drug discovery
- research focus: variant effect prediction
- approach: experimental assay
- Citations
- 12
- FWCI
- 1.63
- Field percentile
- top 17%
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