Optimization of peptide-plasmid DNA vectors formulation for gene delivery in cancer therapy exploring design of

Ângela Sousa1, Ana M Almeida1, Rúben Faria1

  • 1CICS-UBI - Centro de Investigação em Ciências da Saúde, Universidade da Beira Interior, Av. Infante D. Henrique, 6200-506 Covilhã, Portugal.

Insights

Peptide-based vectors like RALA and WRAP5 show promise for cancer gene therapy. Design of Experiments optimized their formulation with plasmid DNA (pDNA), yielding efficient gene delivery systems.

Area of Science:

  • Biotechnology
  • Nanomedicine
  • Molecular Biology

Background:

  • Gene therapy holds significant potential for treating diseases like cancer.
  • Effective gene delivery systems are crucial for clinical gene therapy applications.
  • Peptide-based vectors offer a promising approach for therapeutic gene delivery.

Purpose of the Study:

  • To optimize the formulation of peptide/plasmid DNA (pDNA) complexes for gene delivery using two peptides: RALA and WRAP5.
  • To identify optimal conditions that minimize vector size, maximize positive surface charge (zeta potential), and enhance pDNA complexation capacity (CC).

Main Methods:

  • Utilized a Design of Experiments (DoE) approach to systematically optimize peptide/pDNA formulations.
  • Investigated the impact of buffer pH and nitrogen to phosphate (N/P) ratio on vector characteristics.
  • Monitored vector size, zeta potential, and pDNA complexation capacity (CC) as key outputs.

Main Results:

  • Identified optimal RALA/pDNA and WRAP5/pDNA formulations through DoE.
  • Demonstrated that optimal conditions significantly influence vector size, zeta potential, and CC.
  • Revealed distinct formulation characteristics related to peptide structure and pDNA complexation ability.

Conclusions:

  • Design of Experiments (DoE) is a highly effective tool for optimizing peptide/pDNA vector formulations efficiently.
  • The optimized peptide/pDNA nanosystems exhibit promising features for enhanced gene delivery.
  • This research provides valuable insights for developing improved gene delivery systems for cancer gene therapy.

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