Evidence map›Paper›PMID 29741879›Full record

ArticleAnalytical chemistry2018

Reanalysis of Global Proteomic and Phosphoproteomic Data Identified a Large Number of Glycopeptides.

Yingwei Hu, Punit Shah, David J Clark, Minghui Ao, Hui Zhang

Abstract read
In one paragraph

Article in Analytical chemistry, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 1 pooled it
4.6field-weighted citation impact, top 4% 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

48 citing papers in PubMed, 1 synthesis or guideline pooled it, 83 citations in OpenAlex.

  1. Pooled it
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  13. Plasma/Serum Proteomics based on Mass Spectrometry.Protein and peptide letters · 2024
    Review
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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

5 authors at 1 institution in 1 country.

Yingwei HuDepartment of Pathology , Johns Hopkins University , Baltimore , Maryland 21287 , United States.ORCID 0000-0002-4629-0985
Punit ShahDepartment of Pathology , Johns Hopkins University , Baltimore , Maryland 21287 , United States.
David J ClarkDepartment of Pathology , Johns Hopkins University , Baltimore , Maryland 21287 , United States.ORCID 0000-0003-0527-8469
Minghui AoDepartment of Pathology , Johns Hopkins University , Baltimore , Maryland 21287 , United States.
Hui ZhangDepartment of Pathology , Johns Hopkins University , Baltimore , Maryland 21287 , United States.ORCID 0000-0001-8726-7098
Johns Hopkins University · US

Funding

Shared Resource CoresP01HL107153 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI HART, GERALD WARREN · 2011 to 2017
$16.8M
Glycoprotein biomarkers for the early detection of aggressive prostate cancerU01CA152813 · NCI · JOHNS HOPKINS UNIVERSITY · PI ZHANG, HUI · 2010 to 2021
$6.2M
The Comprehensive Proteome Characterization Center at Johns Hopkins: High Precision Discovery and Confirmation of Genoproteomic TargetsU24CA210985 · NCI · JOHNS HOPKINS UNIVERSITY · PI CHAN, DANIEL WANYUI, ZHANG, HUI · 2016 to 2020
$5.3M
NCI NIH HHS U01 CA152813NCI NIH HHS U24 CA210985NHLBI NIH HHS P01 HL107153
6 · The paper itself

Abstract

Protein glycosylation plays fundamental roles in many cellular processes, and previous reports have shown dysregulation to be associated with several human diseases, including diabetes, cancer, and neurodegenerative disorders. Despite the vital role of glycosylation for proper protein function, the analysis of glycoproteins has been lagged behind to other protein modifications. In this study, we describe the reanalysis of global proteomic data from breast cancer xenograft tissues using recently developed software package GPQuest 2.0, revealing a large number of previously unidentified N-linked glycopeptides. More importantly, we found that using immobilized metal affinity chromatography (IMAC) technology for the enrichment of phosphopeptides had coenriched a substantial number of sialoglycopeptides, allowing for a large-scale analysis of sialoglycopeptides in conjunction with the analysis of phosphopeptides. Collectively, combined tandem mass spectrometry (MS/MS) analyses of global proteomic and phosphoproteomic data sets resulted in the identification of 6 724 N-linked glycopeptides from 617 glycoproteins derived from two breast cancer xenograft tissues. Next, we utilized GPQuest 2.0 for the reanalysis of global and phosphoproteomic data generated from 108 human breast cancer tissues that were previously analyzed by Clinical Proteomic Analysis Consortium (CPTAC). Reanalysis of the CPTAC data set resulted in the identification of 2 683 glycopeptides from the global proteomic data set and 4 554 glycopeptides from phosphoproteomic data set, respectively. Together, 11 292 N-linked glycopeptides corresponding to 1 731 N-linked glycosites from 883 human glycoproteins were identified from the two data sets. This analysis revealed an extensive number of glycopeptides hidden in the global and enriched in IMAC-based phosphopeptide-enriched proteomic data, information which would have remained unknown from the original study otherwise. The reanalysis described herein can be readily applied to identify glycopeptides from already existing data sets, providing insight into many important facets of protein glycosylation in different biological, physiological, and pathological processes.

Indexed as

AnimalsCell Line, TumorCell Transformation, NeoplasticChromatography, AffinityFemaleGlycopeptidesHumansMammary Neoplasms, ExperimentalMicePhosphopeptidesProteomicsGlycopeptidesPhosphopeptides

Identifiers

PMID29741879
PMCPMC6440470
OpenAlexW2786070559

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.