Evidence map›Paper›PMID 36282941›Full record

ArticleBioconjugate chemistry2022

Surface Presentation of Hyaluronic Acid Modulates Nanoparticle-Cell Association.

Elad Deiss-Yehiely, Spencer D Brucks, Natalie Boehnke, Andrew J Pickering, Laura L Kiessling, Paula T Hammond

Open access · greenAbstract read
In one paragraph

Article in Bioconjugate chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.6field-weighted citation impact, top 37% 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

9 citing papers in PubMed, 9 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Elad Deiss-YehielyDepartment of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.ORCID 0000-0002-4345-7903
Spencer D BrucksDepartment of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.ORCID 0000-0002-6409-0709
Natalie BoehnkeKoch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.ORCID 0000-0002-3468-2033
Andrew J PickeringKoch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.
Laura L KiesslingDepartment of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.ORCID 0000-0001-6829-1500
Paula T HammondKoch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.ORCID 0000-0002-9835-192X
Massachusetts Institute of Technology · USInstitute for Soldier Nanotechnologies · US

Funding

VIRUS PRODUCTION COREP30CA014051 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI Angela Nicole Koehler · 1985 to 2026
$93.9M
Synthetic Ligands for Modulating Immune Cell ResponsesR01AI055258 · NIAID · UNIVERSITY OF WISCONSIN-MADISON · PI KIESSLING, LAURA L · 2003 to 2024
$7.8M
Understanding drug delivery through an integrated barcoding approachK99CA255844 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BOEHNKE, NATALIE · 2021 to 2022
$308k
NCI NIH HHS K99 CA255844NCI NIH HHS P30 CA014051NIAID NIH HHS R01 AI055258
6 · The paper itself

Abstract

Nanoparticle (NP) drug carriers have revolutionized medicine and increased patient quality of life. Clinically approved formulations typically succeed because of reduced off-target toxicity of the cargo. However, increasing carrier accumulation at disease sites through precise targeting remains one of the biggest challenges in the field. Novel multivalent ligand presentations and self-assembled constructs can enhance cell association, but an inability to draw direct comparisons across formulations has hindered progress. Furthermore, how nanoparticle structure influences function often is unclear. In this report, we leverage the well-characterized hyaluronic acid (HA)-CD44 binding pair to investigate how the surface architecture of modified NPs impacts their association with ovarian cancer cells that overexpress CD44. We functionalized anionic liposomes with 5 kDa HA by either covalent conjugation via surface coupling or electrostatic self-assembly using the layer-by-layer (LbL) adsorption method. Comparing these two methods, we observed a consistent enhancement of NP-cell association with the self-assembly LbL technique, particularly with higher molecular weight (≥10 kDa) HA. To further optimize association, we increased the surface-available HA. We synthesized a bottlebrush glycopolymer composed of a polynorbornene backbone and pendant 5 kDa HA and layered this macromolecule onto NPs. Flow cytometry revealed that the LbL HA bottlebrush NP outperformed the LbL linear display of HA. Cellular visualization by deconvolution optical microscopy corroborated results from all three constructs. Using exogenous HA to block NP-CD44 interactions, we found the LbL HA bottlebrush NP had a 4-fold higher binding avidity than the best-performing LbL linear HA NP. We further observed that decreasing the density of HA bottlebrush side chains to 75% had minimal impact on LbL NP stability or cell association, though we did see a reduction in binding avidity with this side-chain-modified NP. Our studies indicate that LbL surfaces are highly effective for multivalent displays, and the mode in which they present a targeting ligand can be optimized for NP cell targeting.

Indexed as

Hyaluronic AcidNanoparticlesCell Line, TumorDrug CarriersHumansHyaluronan ReceptorsLigandsQuality of LifeDrug CarriersHyaluronan ReceptorsHyaluronic AcidLigands

Identifiers

PMID36282941
PMCPMC9942780
OpenAlexW4307342899

What OpenQuestion holds

Textmetadata
LicenceTDM
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.