Trap and kill strategy for non-BRCA mutant pancreatic cancer by co-delivery of olaparib and JQ1 with plectin-1 targeting peptide nanoparticles
Source abstract
Abstract
Abstract The poly (ADP-ribose) polymerase (PARP) inhibitor olaparib (Ola), which inhibits the repair of DNA single-strand breaks, has been approved recently by the Food and Drug Administration (FDA) of U.S. for treatment of advanced pancreatic cancer patients with BRCA (Breast Cancer) mutations. However, the response of the pancreatic cancer patients with non-BRCA mutant to Ola treatment remains suboptimal. There is an urgent need to develop effective therapeutic solutions for the majority pancreatic patients. Recently, the drug combination of Ola and the homologous recombination inhibitor JQ1 to treat non-BRCA mutant pancreatic cancers has showed promising outcomes. Herein, we took the advantage of peptide nanoparticle platform, which possesses high drug loading capacity, desirable pharmacokinetic profiles and integration of peptide targeting motif, and developed a tailor-designed plectin-1 targeting peptide nanoparticles (PTNPs) for co-delivery of Ola and JQ1 to treat non-BRCA mutant pancreatic cancers. We confirmed that the majority pancreatic tumor cells are plectin-1 positive. The PTNPs efficiently targeted plectin-1 positive pancreatic tumor cells in vitro and significantly accumulated in tumor site in vivo. The targeted co-delivery of Ola and JQ1 induced much more pancreatic tumor cell apoptosis and significantly enhanced the synergistic effect of combination treatment of Ola and JQ1 in both orthotopic and patient-derived xenograft (PDX) models. Furthermore, this precise delivery of highly coordinated drugs to tumor cells distinctly reduced adverse effects caused by combination of Ola and JQ1.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: PARP inhibition in cancer therapy · Cell death mechanisms and regulation · RNA Interference and Gene Delivery
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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