Evidence map›Paper›PMID 35982648›Full record

ArticlebioRxiv : the preprint server for biology2022

LC-MS/MS-PRM Quantification of IgG glycoforms using stable isotope labeled IgG1 Fc glycopeptide standard.

Miloslav Sanda, Qiang Yang, Guanghui Zong, He Chen, Zhihao Zheng, Harmeet Dhani, Khalid Khan, Alexander Kroemer, Lai-Xi Wang, Radoslav Goldman

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 2 countries.

Miloslav Sanda
Qiang Yang
Guanghui Zong
He Chen
Zhihao Zheng
Harmeet Dhani
Khalid Khan
Alexander Kroemer
Lai-Xi Wang
Radoslav Goldman
Georgetown University · USUniversity of Maryland, College Park · US

Funding

Glycans in Hepatocellular CarcinomaR01CA135069 · NCI · GEORGETOWN UNIVERSITY · PI GOLDMAN, RADOSLAV · 2009 to 2019
$4.1M
Proteomic Analysis of Serum in Liver CancerR01CA115625 · NCI · GEORGETOWN UNIVERSITY · PI GOLDMAN, RADOSLAV · 2007 to 2010
$1.4M
Orbitrap Fusion Lumos ETDS10OD023557 · OD · GEORGETOWN UNIVERSITY · PI GOLDMAN, RADOSLAV · 2017 to 2017
$1.1M
NCI NIH HHS R01 CA115625NCI NIH HHS R01 CA135069NIH HHS S10 OD023557
6 · The paper itself

Abstract

Targeted quantification of proteins is a standard methodology with broad utility, but targeted quantification of glycoproteins has not reached its full potential. The lack of optimized workflows and isotopically labeled standards limits the acceptance of glycoproteomics quantification. In this paper, we introduce an efficient and streamlined chemoenzymatic synthesis of a library of isotopically labeled glycopeptides of IgG1 which we use for quantification in an energy optimized LC-MS/MS-PRM workflow. Incorporation of the stable isotope labeled N-acetylglucosamine enables an efficient monitoring of all major fragment ions of the glycopeptides generated under the soft collision induced dissociation (CID) conditions which reduces the CVs of the quantification to 0.7-2.8%. Our results document, for the first time, that the workflow using a combination of stable isotope labeled standards with intra-scan normalization enables quantification of the glycopeptides by an electron transfer dissociation (ETD) workflow as well as the CID workflow with the highest sensitivity compared to traditional workflows., This was exemplified by a rapid quantification (13-minute) of IgG1 Fc glycoforms from COVID-19 patients. Graphic Abstract:

Identifiers

PMID35982648
PMCPMC9387126
OpenAlexW4289755317

What OpenQuestion holds

Textmetadata
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.