Evidence map›Paper›PMID 32699280›Full record

Observational studyNature communications2020

Rapid, deep and precise profiling of the plasma proteome with multi-nanoparticle protein corona.

John E Blume, William C Manning, Gregory Troiano, Daniel Hornburg, Michael Figa, Lyndal Hesterberg, Theodore L Platt, Xiaoyan Zhao, Rea A Cuaresma, Patrick A Everley and 15 more

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 216 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
216citing papers in PubMed, 1 pooled it
18.5field-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

216 citing papers in PubMed, 1 synthesis or guideline pooled it, 439 citations in OpenAlex.

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156 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

25 authors at 4 institutions in 1 country.

John E Blume *Seer, Inc., Redwood City, CA, 94065, USA. jblume@seer.bio.ORCID http://orcid.org/0000-0003-3026-953X
William C Manning *Seer, Inc., Redwood City, CA, 94065, USA.
Gregory Troiano *Seer, Inc., Redwood City, CA, 94065, USA.
Daniel Hornburg *Seer, Inc., Redwood City, CA, 94065, USA.
Michael FigaSeer, Inc., Redwood City, CA, 94065, USA.
Lyndal HesterbergSeer, Inc., Redwood City, CA, 94065, USA.
Theodore L PlattSeer, Inc., Redwood City, CA, 94065, USA.
Xiaoyan ZhaoSeer, Inc., Redwood City, CA, 94065, USA.
Rea A CuaresmaSeer, Inc., Redwood City, CA, 94065, USA.
Patrick A EverleySeer, Inc., Redwood City, CA, 94065, USA.
Marwin KoSeer, Inc., Redwood City, CA, 94065, USA.
Hope LiouSeer, Inc., Redwood City, CA, 94065, USA.
Max MahoneySeer, Inc., Redwood City, CA, 94065, USA.
Shadi FerdosiSeer, Inc., Redwood City, CA, 94065, USA.ORCID http://orcid.org/0000-0003-2933-8809
Eltaher M ElgierariSeer, Inc., Redwood City, CA, 94065, USA.
Craig StolarczykSeer, Inc., Redwood City, CA, 94065, USA.
Behzad TangeyshSeer, Inc., Redwood City, CA, 94065, USA.
Hongwei XiaSeer, Inc., Redwood City, CA, 94065, USA.
Ryan BenzSeer, Inc., Redwood City, CA, 94065, USA.
Asim SiddiquiSeer, Inc., Redwood City, CA, 94065, USA.
Steven A CarrBroad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.
Philip MaSeer, Inc., Redwood City, CA, 94065, USA.
Robert LangerDavid H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.ORCID http://orcid.org/0000-0003-4255-0492
Vivek FariasSloan School and Operations Research Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA. vivekf@mit.edu.ORCID http://orcid.org/0000-0002-5856-9246
Omid C FarokhzadSeer, Inc., Redwood City, CA, 94065, USA. ofarokhzad@bwh.harvard.edu.ORCID http://orcid.org/0000-0003-2009-270X
Codexis (United States) · USMassachusetts Institute of Technology · USBrigham and Women's Hospital · USBroad Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Large-scale, unbiased proteomics studies are constrained by the complexity of the plasma proteome. Here we report a highly parallel protein quantitation platform integrating nanoparticle (NP) protein coronas with liquid chromatography-mass spectrometry for efficient proteomic profiling. A protein corona is a protein layer adsorbed onto NPs upon contact with biofluids. Varying the physicochemical properties of engineered NPs translates to distinct protein corona patterns enabling differential and reproducible interrogation of biological samples, including deep sampling of the plasma proteome. Spike experiments confirm a linear signal response. The median coefficient of variation was 22%. We screened 43 NPs and selected a panel of 5, which detect more than 2,000 proteins from 141 plasma samples using a 96-well automated workflow in a pilot non-small cell lung cancer classification study. Our streamlined workflow combines depth of coverage and throughput with precise quantification based on unique interactions between proteins and NPs engineered for deep and scalable quantitative proteomic studies.

Indexed as

AdultAgedAged, 80 and overBlood ProteinsCarcinoma, Non-Small-Cell LungChromatography, High Pressure LiquidDiagnosis, DifferentialFemaleHealthy VolunteersHumansLung NeoplasmsMaleMiddle AgedNanoparticlesPilot ProjectsProtein CoronaBlood ProteinsProtein Corona

Identifiers

PMID32699280
PMCPMC7376165
OpenAlexW3043870236

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.