Evidence map›Paper›PMID 41630161›Full record

ReviewAdvanced healthcare materials2026

From RNA to DNA: How Cargo Identity Reprograms Lipid Nanoparticle Architecture and Function.

Erica Quagliarini, Daniela Pozzi, Giulio Caracciolo

Abstract readReview
In one paragraph

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

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Erica QuagliariniNanoDelivery Lab, Department of Molecular Medicine, Sapienza University of Rome, Rome, Italy.
Daniela PozziNanoDelivery Lab, Department of Molecular Medicine, Sapienza University of Rome, Rome, Italy.
Giulio CaraccioloNanoDelivery Lab, Department of Molecular Medicine, Sapienza University of Rome, Rome, Italy.ORCID https://orcid.org/0000-0002-8636-4475

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lipid nanoparticles (LNPs) have become the leading platform for delivering genetic material, gaining global recognition through the success of mRNA-based COVID-19 vaccines such as mRNA-1273 (SpikeVax, Moderna) and BNT162b2 (Comirnaty, BioNTech/Pfizer). Yet, while RNA-LNPs have reached clinical maturity, their DNA counterparts remain comparatively underexplored, despite holding great promise for gene replacement and genome-editing therapies. In this review, we turn the spotlight on DNA-loaded LNPs, examining how their structure, composition, and biological behavior differ from RNA-LNPs, their natural point of reference, and from earlier lipid-based systems such as cationic liposome/DNA complexes (lipoplexes). DNA-LNPs tend to form larger, more heterogeneous, and often multilamellar particles due to the intrinsic stiffness and high charge density of DNA. These distinctive features call for dedicated design strategies, including the use of cationic lipids, pre-condensation agents, and optimized PEGylation schemes. Moreover, DNA profoundly influences the biomolecular corona that forms in biological fluids, which in turn shapes immune recognition, circulation, and tissue targeting. By highlighting these unique physical and biological challenges, this review underscores the need to move beyond simply adapting RNA-based formulations. Instead, a cargo-informed design approach will be key to unlocking the full therapeutic potential of DNA-LNPs in next-generation gene delivery.

Indexed as

DNALipidsNanoparticlesRNAAnimalsCOVID-19 VaccinesGene Transfer TechniquesHumansLiposomesSARS-CoV-2COVID-19 VaccinesDNALipid NanoparticlesLipidsLiposomesRNADNAgene deliverylipid nanoparticlesprotein coronaRNA

Identifiers

PMID41630161
PMCPMC13107920

What OpenQuestion holds

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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.