Evidence map›Paper›PMID 38907991›Full record

ArticleACS nano2024

Enhanced Prostate-specific Membrane Antigen Targeting by Precision Control of DNA Scaffolded Nanoparticle Ligand Presentation.

Deblin Jana, Zhiyuan Han, Xiao Huang, Anju Wadhwa, Athira Raveendran, Kareem Ebeid, Niranjan Meher, Robert R Flavell, Tejal Desai

Abstract read
In one paragraph

Article in ACS nano, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Deblin JanaSchool of Engineering, Institute for Biology, Engineering and Medicine, Brown University, Providence, Rhode Island 02912, United States.ORCID 0000-0003-2157-724X
Zhiyuan HanDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California 94158, United States.
Xiao HuangDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California 94158, United States.
Anju WadhwaDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, California 94143, United States.
Athira RaveendranDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, California 94143, United States.
Kareem EbeidSchool of Engineering, Institute for Biology, Engineering and Medicine, Brown University, Providence, Rhode Island 02912, United States.
Niranjan MeherDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, California 94143, United States.
Robert R FlavellDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, California 94143, United States.ORCID 0000-0002-8694-1199
Tejal DesaiSchool of Engineering, Institute for Biology, Engineering and Medicine, Brown University, Providence, Rhode Island 02912, United States.ORCID 0000-0003-3409-9208

Funding

Translational InformaticsP30CA082103 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Jennifer Leigh Clarke · 1999 to 2026
$209.7M
ACE2-targeted PET radiotracers for investigating spatiotemporal distribution of SARS-CoV-2 organ injury and therapy response.R01AI161829 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI DESAI, TEJAL A., FLAVELL, ROBERT RICHARD · 2021 to 2023
$2.4M
NCI NIH HHS P30 CA082103NIAID NIH HHS R01 AI161829
6 · The paper itself

Abstract

Targeted nanoparticles have been extensively explored for their ability to deliver their payload to a selective cell population while reducing off-target side effects. The design of actively targeted nanoparticles requires the grafting of a ligand that specifically binds to a highly expressed receptor on the surface of the targeted cell population. Optimizing the interactions between the targeting ligand and the receptor can maximize the cellular uptake of the nanoparticles and subsequently improve their activity. Here, we evaluated how the density and presentation of the targeting ligands dictate the cellular uptake of nanoparticles. To do so, we used a DNA-scaffolded PLGA nanoparticle system to achieve efficient and tunable ligand conjugation. A prostate-specific membrane antigen (PSMA) expressing a prostate cancer cell line was used as a model. The density and presentation of PSMA targeting ligand ACUPA were precisely tuned on the DNA-scaffolded nanoparticle surface, and their impact on cellular uptake was evaluated. It was found that matching the ligand density with the cell receptor density achieved the maximum cellular uptake and specificity. Furthermore, DNA hybridization-mediated targeting chain rigidity of the DNA-scaffolded nanoparticle offered ∼3 times higher cellular uptake compared to the ACUPA-terminated PLGA nanoparticle. Our findings also indicated a ∼ 3.7-fold reduction in the cellular uptake for the DNA hybridization of the non-targeting chain. We showed that nanoparticle uptake is energy-dependent and follows a clathrin-mediated pathway. Finally, we validated the preferential tumor targeting of the nanoparticles in a bilateral tumor xenograft model. Our results provide a rational guideline for designing actively targeted nanoparticles and highlight the application of DNA-scaffolded nanoparticles as an efficient active targeting platform.

Indexed as

DNAGlutamate Carboxypeptidase IINanoparticlesProstatic NeoplasmsAnimalsAntigens, SurfaceCell Line, TumorHumansLigandsMaleMicePolylactic Acid-Polyglycolic Acid CopolymerAntigens, SurfaceDNAFOLH1 protein, humanGlutamate Carboxypeptidase IILigandsPolylactic Acid-Polyglycolic Acid Copolymercell uptakeDNAligand densitynanoparticlessurface chemistry

Identifiers

PMID38907991
PMCPMC11223598

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.