Evidence map›Paper›PMID 42280526›Full record

ArticlePolymers2026

Synthesis and Characterization of Dual Natural Quercetin/Fucoidan Gene Delivery Nanoplatform for Synthetic Lethality in BRCA-Deficient Tumors.

Jih-Hao Yeh, Shih-Yu Huang, Ching-Chun Chu, Chun-Tao Su, Hung-Wei Cheng, San-Yuan Chen

Abstract read
In one paragraph

Article in Polymers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Jih-Hao YehDepartment of Materials Science and Engineering, National Yang Ming Chiao Tung University, Hsinchu 300093, Taiwan.
Shih-Yu HuangDepartment of Materials Science and Engineering, National Yang Ming Chiao Tung University, Hsinchu 300093, Taiwan.
Ching-Chun ChuDepartment of Materials Science and Engineering, National Yang Ming Chiao Tung University, Hsinchu 300093, Taiwan.
Chun-Tao SuDepartment of Materials Science and Engineering, National Yang Ming Chiao Tung University, Hsinchu 300093, Taiwan.
Hung-Wei ChengDepartment of Biological Science and Technology, China Medical University, Taichung 406040, Taiwan.
San-Yuan ChenDepartment of Materials Science and Engineering, National Yang Ming Chiao Tung University, Hsinchu 300093, Taiwan.ORCID 0000-0002-6500-2993

Funding

National Science and Technology Council NSTC 114-2223-E-A49-005
6 · The paper itself

Abstract

Cancer is a complex and evolutionary disease, with the development of different types of cancers leading to various different defective gene mutations. Synthetic lethality is a genetic-level precision medical strategy. Currently, treating BRCA (BReast CAncer)-mutated breast or ovarian cancer cells with a chemical inhibitor (Poly(ADP-ribose) polymerase, PARPi) is a typical synthetic lethal application in clinical practice. However, PARPi therapy has been found to cause off-target effects and therapy-induced immune escape driven by PD-L1 upregulation, allowing for cancer cells to escape attack from the immune response. To overcome these challenges, we developed a core-shell structure comprising a hydrophobic core of quercetin (Q)-mediated PARP inhibition and iron oxide nanoparticles (IONPs), enveloped by a hydrophilic fucoidan (Fu) shell to encapsulate short hairpin RNA targeting Programmed Death Ligand 1 (shPD-L1) for efficient gene transfection (shPD-L1@QIO@Fu). Structurally, the incorporation of quercetin into the intermediate hydrophobic layer enables modulate of the PARP effect, while the inner aqueous core with shPD-L1 gene silencing can inhibit the expression of PD-L1 protein. In this study, we proved that shPD-L1@QIO@Fu demonstrated a dual therapeutic mechanism against BRCA-mutant cancer cells by inducing extensive DNA double-strand breaks and promoting apoptosis. Furthermore, the combined action of quercetin-mediated DNA damage and shPD-L1-driven PD-L1 suppression led to a significant reduction in PD-L1 mRNA to approximately 5% at 72 h and decreased surface PD-L1 below baseline by 96 h. This effectively suppresses PARPi-induced PD-L1 upregulation and enhances antitumor immunity. These findings demonstrate the therapeutic efficacy of shPD-L1@QIO@Fu nanomedicine, providing a promising foundation for advanced co-delivery strategies to synergize PARP inhibition mediated synthetic lethality with immune checkpoint blockade in next-generation precision medicine.

Indexed as

BRCA1/2-mutant tumorsnanomedicinePD-L1 blockadePoly(ADP-ribose) polymerase inhibitionquercetinsynthetic lethality

Identifiers

PMID42280526
PMCPMC13259162

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.