Evidence map›Paper›PMID 35173043›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2022

Lung-selective mRNA delivery of synthetic lipid nanoparticles for the treatment of pulmonary lymphangioleiomyomatosis.

Min Qiu, Yan Tang, Jinjin Chen, Rachel Muriph, Zhongfeng Ye, Changfeng Huang, Jason Evans, Elizabeth P Henske, Qiaobing Xu

Open access · hybridAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 230 papers.

0numbers the graph read from it
0cells of the map it votes in
230citing papers in PubMed
49.6field-weighted citation impact, top 1% of its field
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

230 citing papers in PubMed, 456 citations in OpenAlex.

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  6. Bioactive lipid-derived nanoparticles for RNA delivery.Materials today (Kidlington, England) · 2026
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  11. Dual pKa Lipid Nanoparticles for Lung-tropic mRNA Delivery and pH-Programmed Endosomal Escape.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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170 more citing papers are in PubMed but not listed here.

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 at 3 institutions in 1 country.

Min QiuDepartment of Biomedical Engineering, Tufts University, Medford, MA 02155.ORCID 0000-0002-7373-2355
Yan TangDivision of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115; Qiaobing.Xu@tufts.edu ytang11@bwh.harvard.edu ehenske@bwh.harvard.edu.ORCID 0000-0002-6223-8423
Jinjin ChenDepartment of Biomedical Engineering, Tufts University, Medford, MA 02155.ORCID 0000-0002-3386-5321
Rachel MuriphDepartment of Chemistry, University of Massachusetts Boston, Boston, MA 02125.
Zhongfeng YeDepartment of Biomedical Engineering, Tufts University, Medford, MA 02155.ORCID 0000-0003-0383-7247
Changfeng HuangDepartment of Biomedical Engineering, Tufts University, Medford, MA 02155.
Jason EvansDepartment of Chemistry, University of Massachusetts Boston, Boston, MA 02125.
Elizabeth P HenskeDivision of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115; Qiaobing.Xu@tufts.edu ytang11@bwh.harvard.edu ehenske@bwh.harvard.edu.ORCID 0000-0001-7978-6699
Qiaobing XuDepartment of Biomedical Engineering, Tufts University, Medford, MA 02155; Qiaobing.Xu@tufts.edu ytang11@bwh.harvard.edu ehenske@bwh.harvard.edu.
Tufts University · USBrigham and Women's Hospital · USUniversity of Massachusetts Boston · US

Funding

SCGE Disease Models Studies Supplement: Development of LNP-mediated based editing to treat Leber Congenital Amaurosis (LCA) for vision restoration in mouse modelUH3TR002636 · NCATS · MASSACHUSETTS EYE AND EAR INFIRMARY · PI CHEN, ZHENG-YI, LIU, DAVID R · 2021 to 2022
$3.8M
Efficient in Vivo RNP-based Gene Editing in the Sensory Organ Inner Ear Using Bioreducible Lipid NanoparticlesUG3TR002636 · NCATS · MASSACHUSETTS EYE AND EAR INFIRMARY · PI CHEN, ZHENG-YI, LIU, DAVID R · 2018 to 2020
$2.4M
NCATS NIH HHS UG3 TR002636NCATS NIH HHS UH3 TR002636
6 · The paper itself

Abstract

Safe and efficacious systemic delivery of messenger RNA (mRNA) to specific organs and cells in vivo remains the major challenge in the development of mRNA-based therapeutics. Targeting of systemically administered lipid nanoparticles (LNPs) coformulated with mRNA has largely been confined to the liver and spleen. Using a library screening approach, we identified that N-series LNPs (containing an amide bond in the tail) are capable of selectively delivering mRNA to the mouse lung, in contrast to our previous discovery that O-series LNPs (containing an ester bond in the tail) that tend to deliver mRNA to the liver. We analyzed the protein corona on the liver- and lung-targeted LNPs using liquid chromatography-mass spectrometry and identified a group of unique plasma proteins specifically absorbed onto the surface that may contribute to the targetability of these LNPs. Different pulmonary cell types can also be targeted by simply tuning the headgroup structure of N-series LNPs. Importantly, we demonstrate here the success of LNP-based RNA therapy in a preclinical model of lymphangioleiomyomatosis (LAM), a destructive lung disease caused by loss-of-function mutations in the

Indexed as

AnimalsDrug Delivery SystemsFemaleGenetic EngineeringGene Transfer TechniquesLiposomesLungLung DiseasesLymphangioleiomyomatosisMiceMice, Inbred BALB CMice, Inbred C57BLNanoparticlesProtein CoronaRNA, MessengerRNA, Small InterferingLipid NanoparticlesLiposomesProtein CoronaRNA, MessengerRNA, Small Interferinglipid nanoparticleslung-targeted deliverylymphangioleiomyomatosismRNAtuberous sclerosis complex

Identifiers

PMID35173043
PMCPMC8872770
OpenAlexW4212774448

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.