Evidence map›Paper›PMID 39814365›Full record

ArticleJournal of proteome research2025

IP-to-MS: An Unbiased Workflow for Antigen Profiling.

Stephanie Biedka, Svitlana Yablonska, Xi Peng, Duah Alkam, Mara Hartoyo, Hannah VanEvery, Daniel J Kass, Stephanie D Byrum, Kunhong Xiao, Yingze Zhang and 4 more

Abstract read
In one paragraph

Article in Journal of proteome research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Trial
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

14 authors.

Stephanie BiedkaImpact Proteomics, LLC., Pittsburgh, Pennsylvania 15206, United States.ORCID 0000-0001-8167-037X
Svitlana YablonskaImpact Proteomics, LLC., Pittsburgh, Pennsylvania 15206, United States.
Xi PengCenter for Proteomics & Artificial Intelligence, Allegheny Health Network Cancer Institute, Pittsburgh, Pennsylvania 15205, United States.
Duah AlkamDepartment of Biochemistry and Molecular Biology, University of Arkansas for Medical Sciences, Little Rock, Arkansas 72205, United States.
Mara HartoyoUniversity of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15261, United States.
Hannah VanEveryUniversity of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15261, United States.
Daniel J KassDivision of Pulmonary and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15261, United States.
Stephanie D ByrumDepartment of Biochemistry and Molecular Biology, University of Arkansas for Medical Sciences, Little Rock, Arkansas 72205, United States.ORCID 0000-0002-1783-3610
Kunhong XiaoCenter for Proteomics & Artificial Intelligence, Allegheny Health Network Cancer Institute, Pittsburgh, Pennsylvania 15205, United States.
Yingze ZhangDivision of Pulmonary and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15261, United States.
Robyn T DomsicDivision of Rheumatology and Clinical Immunology, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15261, United States.
Robert LafyatisDivision of Rheumatology and Clinical Immunology, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15261, United States.
Dana P AschermanDivision of Rheumatology and Clinical Immunology, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15261, United States.
Jonathan S MindenImpact Proteomics, LLC., Pittsburgh, Pennsylvania 15206, United States.

Funding

Translational Regulation in Normal Erythropoiesis and Diamond Blackfan AnemiaP20GM121293 · NIGMS · ARKANSAS CHILDREN'S HOSPITAL RES INST · PI Alan Tackett · 2017 to 2026
$27.6M
Supplement for Google cloud build-outR24GM137786 · NIGMS · UNIV OF ARKANSAS FOR MED SCIS · PI Alan Tackett · 2020 to 2026
$15.4M
Systems Biology CoreP50AR080612 · NIAMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Stephen Y Chan · 2022 to 2026
$9.5M
NIAMS NIH HHS P50 AR080612NIGMS NIH HHS P20 GM121293NIGMS NIH HHS R24 GM137786
6 · The paper itself

Abstract

Immunoprecipitation is among the most widely utilized methods in biomedical research, with applications that include the identification of antibody targets and associated proteins. The path to identifying these targets is not straightforward, however, and often requires the use of chemical cross-linking and/or gel electrophoresis to separate targets from an overabundance of immunoglobulin protein. Such experiments are labor intensive and often yield long lists of candidate antibody targets. Here, we describe an unbiased immunoprecipitation-to-mass spectrometry (IP-to-MS) method that relies on a novel protein tag to separate low abundance immunoprecipitated proteins from overwhelmingly abundant immunoglobulins. We demonstrate that the IP-to-MS serotyping workflow is highly reproducible and can be used for the identification of novel, patient-specific antigen targets in multiple disease states. Furthermore, we show that IP-to-MS may outperform conventional methods of antibody detection, including enzyme-linked immunosorbent assay, while also enabling patient stratification beyond what is possible with traditional approaches.

Indexed as

AntigensImmunoprecipitationMass SpectrometryProteomicsEnzyme-Linked Immunosorbent AssayHumansImmunoglobulinsWorkflowAntigensImmunoglobulinsautoimmune diseaseimmunoprecipitationmass spectrometryunbiased antigen identification

Identifiers

PMID39814365
PMCPMC11812086

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.