Evidence map›Paper›PMID 32758705›Full record

ArticleJournal of proteomics2020

An input-controlled model system for identification of MHC bound peptides enabling laboratory comparisons of immunopeptidome experiments.

Martin G Klatt, Zita E H Aretz, Michael Curcio, Ron S Gejman, Heather F Jones, David A Scheinberg

Open access · greenAbstract read
In one paragraph

Article in Journal of proteomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 50% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
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 3 institutions in 1 country.

Martin G KlattMolecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York 10065, USA.
Zita E H AretzMolecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York 10065, USA; Physiology Biophysics and Systems Biology Program, Weill Cornell Medicine, New York 10065, USA.
Michael CurcioMolecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York 10065, USA.
Ron S GejmanMolecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York 10065, USA; Tri-Institutional MD-PhD Program, Sloan Kettering Institute, Weill Cornell Medicine and Rockefeller University, New York 10065, USA.
Heather F JonesMolecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York 10065, USA; Pharmacology Department, Weill Cornell Medicine, New York 10065, USA.
David A ScheinbergMolecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York 10065, USA; Pharmacology Department, Weill Cornell Medicine, New York 10065, USA. Electronic address: scheinbd@mskcc.org.
Memorial Sloan Kettering Cancer Center · USWeill Cornell Medicine · USRockefeller University · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
T LYMPHOCYTE SUBSET FUNCTION POST-TRANSPLANTATIONP01CA023766 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI PAMER, ERIC G. · 1985 to 2023
$59.0M
Weill Cornell/Rockefeller/Sloan-Kettering MST ProgramT32GM007739 · NIGMS · WEILL MEDICAL COLL OF CORNELL UNIV · PI HSU, KATHARINE C · 1985 to 2023
$51.1M
CANCER PHARMACOLOGYT32CA062948 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI LORRAINE J GUDAS · 1994 to 2026
$12.1M
Understanding and Mimicking TCR Recognition with Therapeutic Monoclonal Antibodies.R35CA241894 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI DAVID A SCHEINBERG · 2020 to 2026
$7.2M
RECOMBINANT ANTICD33 ANTIBODY FOR AMLR01CA055349 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI SCHEINBERG, DAVID A · 1991 to 2020
$6.8M
Immunoediting in Human CancerF30CA200327 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI GEJMAN, RON S · 2015 to 2018
$187k
NCI NIH HHS F30 CA200327NCI NIH HHS P01 CA023766NCI NIH HHS P30 CA008748NCI NIH HHS R01 CA055349NCI NIH HHS R35 CA241894NCI NIH HHS T32 CA062948NIGMS NIH HHS T32 GM007739
6 · The paper itself

Abstract

Characterization of MHC-bound peptides by mass spectrometry (MS) is an essential technique for immunologic studies. Many efforts have been made to quantify the number of MHC-presented ligands by MS and to define the limits of detection of a specific MHC ligand. However, these experiments are often complex and comparisons across different laboratories are challenging. Therefore, we compared and orthogonally validated quantitation of peptide:MHC complexes by radioimmunoassay and flow cytometry using TCR mimic antibodies in three model systems to establish a method to control the experimental input of peptide MHC:complexes for MS analysis. Following isolation of MHC-bound peptides we identified and quantified an MHC ligand of interest with high correlation to the initial input. We found that the diversity of the presented ligandome, as well as the peptide sequence itself affected the detection of the target peptide. Furthermore, results were applicable from these model systems to unmodified cell lines with a tight correlation between HLA-A*02 complex input and the number of identified HLA-A*02 ligands. Overall, this framework provides an easily accessible experimental setup that offers the opportunity to control the peptide:MHC input and in this way compare immunopeptidome experiments not only within but also between laboratories, independent of their experimental approach. SIGNIFICANCE: Although immunopeptidomics is an essential tool for the characterization of MHCbound peptides on the cell surface, there are no easily applicable established protocols available that allow comparison of immunopeptidome experiments across laboratories. Here, we demonstrate that controlling the peptide:MHC input for immunopurification and LC-MS/MS experiments by flow cytometry in pre-defined model systems allows the generation of qualitative and quantitative data that can easily be compared between investigators, independently of their methods for MHC ligand isolation for MS.

Indexed as

LaboratoriesTandem Mass SpectrometryChromatography, LiquidLigandsPeptidesLigandsPeptides

Identifiers

PMID32758705
PMCPMC7484941
OpenAlexW3047039657

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.