Engineering Nanoparticles for Targeted Delivery of Nucleic Acid Therapeutics in Tumor

Purpose: In the past 10 years, many clinical nano-gene therapy trials have been discontinued due to poor efficacy and serious side effects. There is a critical need to design suitable gene delivery systems that can protect nucleic acids, enhance transfection efficiency, penetrate deep into tumors, and remain stable and safe during blood circulation while accumulating at tumor sites. ---

Hypothesis: The review’s central thesis is: if nanoparticles (liposomes, polymers, inorganics) are engineered with appropriate modifications—including stimuli-responsive systems (pH, thermo, redox, enzyme, light, multi-responsive)—then they can effectively deliver DNA/RNA therapeutics to tumors, improve gene delivery efficiency, reduce cytotoxicity and side effects, and enable co-delivery of chemotherapy drugs with drug tolerance-related genes or oncogenes for better clinical cancer gene therapy. ---

Aims: - Introduce the application of liposomes, polymers, and inorganics in gene delivery. - Discuss different modifications with stimuli-responsive systems that improve gene delivery efficiency and reduce cytotoxicity. - Summarize clinical applications of nanoparticle-based RNAi therapy. - Review challenges and barriers of polymer-mediated gene therapy, including cellular uptake, endosomal escape, nuclear entry, and nanotoxicity. - Discuss the co-delivery of chemotherapy drugs with drug tolerance-related genes or oncogenes. - Highlight future directions of cationic polymer design in gene delivery. ---

Delivery system: Payloads: siRNA, microRNA, shRNA, plasmid DNA (pDNA), mRNA, antisense oligonucleotides, CRISPR/Cas9 mRNA, sgRNA. Lipid-based systems: - Cationic liposomes (DC-Chol/DOPE, DOTAP, DOTMA), PEGylated lipoplexes. - Solid lipid nanoparticles (SLNs). - Reconstituted high-density lipoprotein (rHDL) NPs. - Lipid nanoparticles (LNPs) including SNALPs (stable nucleic acid lipid particles). Polymeric systems: - Natural polymers: Chitosan, cationic gelatin, cationic dextran, cationic cellulose, cationic cyclodextrins. - Synthetic polymers: PEI (linear and branched), PLL, PAA (polyacrylic acid), PAE (poly(aliphatic ester)), PDMAEMA, PAMAM dendrimers, cyclodextrin derivatives. - Bioreducible polymers: SS-PAA, SS-PAEIs, poly(disulfide amines). Inorganic systems: - Gold nanoparticles (AuNPs): PEG/CPP-modified beacons, RGD-dendrimer AuNPs, poly(thymine)-functionalized AuNPs. - Calcium phosphate nanoparticles (CaPs): PEG/lipid/CaP, CaP-AHA/siRNA. - Quantum dots (QDs): PEGylated QDs for imaging and siRNA delivery. - Magnetic nanoparticles: iron oxide with dextran coating, lipid shell. - Mesoporous silica nanoparticles (MSNPs): PAMAM-capped, PEI-functionalized. - Carbon nanotubes (CNTs): amine-functionalized, siRNA conjugated via disulfide bonds. Stimuli-responsive systems: - pH-responsive: PEI, chitosan, PAA, polyhistidine. - Thermo-responsive: PNIPAAm, pluronic F-127. - Redox-responsive: disulfide linkages, GSH-sensitive. - Enzyme-responsive: MMP2-sensitive, esterase-responsive. - Light-responsive: NIR-triggered release from gold nanorods/nanoshells. - Multi-responsive: pH/redox, pH/temperature, pH/light, light/redox. Targeting ligands: Transferrin, folate, RGD, iRGD, CPPs (HIV-TAT, VP22), NLS peptides, EGFR-targeted, CD44-targeted (HA), SP94, MC11. Clinical trial formulations: - CALAA-01 (cyclodextrin-based polymer + transferrin-targeted siRNA against RRM2). - siG12D LODER (PLGA matrix + siRNA against KRAS G12D). - TKM-080301 (SNALP + siRNA against PLK1). - Atu027, DCR-MYC, siRNA-EphA2-DOPC, BP1001, SGT-53, etc. ---

Approach: Narrative review of preclinical and clinical literature. No primary experimental groups. Model systems discussed include: - In vitro: Caco-2, COS-7, HEK293, HeLa, B16F10, C26, HepG2, lung cancer cells, breast cancer cells, ovarian cancer cells, pancreatic cancer cells, glioblastoma cells, cardiomyocytes, stem cells. - In vivo: Mouse models of cancer (subcutaneous, orthotopic, metastatic), liver, lung, spleen, kidney, pancreatic tumors, glioma, melanoma, breast cancer, colorectal cancer. - Clinical trials: Phase I, I/II, II, III trials of nanoparticle-based RNAi therapeutics (Table 1 lists NCT numbers including NCT00689065, NCT01188785, NCT02191878, NCT01262235, etc.). - Disease context: Cancer (solid tumors, hematological malignancies), viral infections (Ebola), hepatic fibrosis, hypercholesterolemia. ---

Key methods: Techniques and endpoints highlighted across cited studies: - Transfection efficiency (reporter gene expression, luciferase, GFP, β-galactosidase). - Gene silencing/knockdown (siRNA, shRNA, miRNA). - Flow cytometry for cellular uptake and apoptosis. - Confocal laser scanning microscopy (CLSM) for intracellular trafficking. - Dynamic light scattering (DLS) for particle size and zeta potential. - Transmission electron microscopy (TEM) for morphology. - In vivo tumor growth inhibition and survival analysis. - Biodistribution and pharmacokinetic studies. - Cytotoxicity and biocompatibility assays (MTT, LDH). - Fluorescence imaging for siRNA tracking. - HPLC for drug release monitoring. - MRI for magnetic nanoparticle tracking. - Western blot and qPCR for target gene/protein expression. ---

Key results: - CALAA-01: Polymer-based NP with transferrin targeting and siRNA against RRM2; dose-dependent tumor accumulation and target inhibition; trial terminated due to 21% adverse event rate from drug instability. - siG12D LODER: PLGA matrix implanted into pancreatic tumors; slow release of siRNA against KRAS G12D; passed phase 1/2a with good anticancer effects. - TKM-080301: SNALP with siRNA against PLK1; evaluated in phase I/II for gastrointestinal neuroendocrine tumors and adrenocortical carcinoma. - PEI-HNPs for CRISPR/Cas9: Achieved up to 60% Cas9 transfection efficiency and 67.4% sgRNA uptake efficiency. - Chitosan/siRNA: Up to 90% knockdown in papillary thyroid carcinoma cells. - AuNP-PEI: ~12-fold more potent than PEI alone in COS-7 cells. - AuNP with quaternary ammonium: ~8-fold more effective than PEI in 293T cells. - CNT-siRNA: 60–70% knockdown in human T cells; CNT-pDNA β-galactosidase expression 5–10 fold higher than naked pDNA. - Magnetic dendrimer-siRNA: EGFR protein reduced by 70–80% in human glioblastoma cells. - Calcium phosphate: Up to 60% transfection in low-density primary neuronal cultures. - EPR effect limitation: Only about 0.7% of injected nanomedicine dose actually accumulates in tumors. ---

Interpretation: The authors conclude that engineered nanoparticles—liposomes, polymers, and inorganics—with appropriate modifications (PEGylation, targeting ligands, stimuli-responsive linkages) can effectively deliver nucleic acid therapeutics to tumors, improve transfection efficiency, and reduce cytotoxicity. Co-delivery of siRNAs and anticancer drugs is a promising strategy for drug-resistant cancers. However, challenges remain: off-targeting, nanotoxicity, poor tumor penetration, and the need for appropriate oncogene selection. Future cationic polymer design should focus on biodegradable, biocompatible materials with minimal adverse effects, controllable physicochemical properties, and multifunctional capabilities. ---

Limitations: - EPR effect variability: Only ~0.7% of injected nanoparticles reach tumors; EPR is heterogeneous across tumor types and patients. - Nanotoxicity: Smaller NPs exhibit higher toxic effects due to increased surface area; structure and shape contribute to toxicity; ion/biomolecule adsorption influences cellular responses. - Cellular barriers: Poor cellular uptake, endosomal escape, and nuclear entry for shRNA/pDNA. - Clinical translation challenges: CALAA-01 trial terminated due to adverse events; many trials discontinued due to poor efficacy or side effects. - Stability issues: Cationic liposomes aggregate with blood components; SLN stability is a drawback. - Tumor penetration: Large NP size and crosslinked tumor matrix hinder deep penetration. - Off-target effects: Need for highly specific molecular targets to avoid off-target immune responses. - Oncogene selection: Choosing appropriate oncogenes for gene therapy remains challenging. - Co-delivery complexity: siRNA and drug co-delivery requires optimization for synergistic effects. - As a review: Not a systematic review or meta-analysis; no primary data.