Evidence map›Paper›PMID 28228285›Full record

ArticleImmunity2017

Mass Spectrometry Profiling of HLA-Associated Peptidomes in Mono-allelic Cells Enables More Accurate Epitope Prediction.

Jennifer G Abelin, Derin B Keskin, Siranush Sarkizova, Christina R Hartigan, Wandi Zhang, John Sidney, Jonathan Stevens, William Lane, Guang Lan Zhang, Thomas M Eisenhaure and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Immunity, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 384 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
384citing papers in PubMed, 1 pooled it
–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

384 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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324 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

15 authors.

Jennifer G AbelinBroad Institute of MIT and Harvard, Cambridge, MA, USA.
Derin B KeskinBroad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA; Department of Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA; Harvard Medical School, Boston, MA, 02115, USA; Department of Computer Science, Metropolitan College, Boston University, Boston, MA, 02215, USA.
Siranush SarkizovaBroad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02142, USA.
Christina R HartiganBroad Institute of MIT and Harvard, Cambridge, MA, USA.
Wandi ZhangDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.
John SidneyLa Jolla Institute for Allergy and Immunology, 92037, La Jolla, CA.
Jonathan StevensTissue Typing Laboratory, Brigham and Women's Hospital, Boston, MA, 02115, USA.
William LaneTissue Typing Laboratory, Brigham and Women's Hospital, Boston, MA, 02115, USA.
Guang Lan ZhangDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA; Harvard Medical School, Boston, MA, 02115, USA; Department of Computer Science, Metropolitan College, Boston University, Boston, MA, 02215, USA.
Thomas M EisenhaureBroad Institute of MIT and Harvard, Cambridge, MA, USA.
Karl R ClauserBroad Institute of MIT and Harvard, Cambridge, MA, USA.
Nir HacohenBroad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA; Center for Cancer Immunology, Massachusetts General Hospital, Boston, MA, 02114, USA. Electronic address: nhacohen@mgh.harvard.edu.
Michael S RooneyBroad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard/MIT Division of Health Sciences and Technology, Cambridge, Massachusetts, 02139 USA; Neon Therapeutics, Cambridge, MA, 02139, USA. Electronic address: mrooney@neontherapeutics.com.
Steven A CarrBroad Institute of MIT and Harvard, Cambridge, MA, USA. Electronic address: scarr@broad.mit.edu.
Catherine J WuBroad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA; Department of Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA; Harvard Medical School, Boston, MA, 02115, USA. Electronic address: cwu@partners.org.

Funding

Treating the P13-Kinase/AKTP50CA101942 · NCI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI David McDermott · 2003 to 2026
$53.4M
Proteo-genomic Discovery, Prioritization and Verification of Cancer BiomarkersU24CA160034 · NCI · BROAD INSTITUTE, INC. · PI CARR, STEVEN A, PAULOVICH, AMANDA G · 2011 to 2016
$16.2M
Training Program in Bioinformatics and Integrative GenomicsT32HG002295 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI Peter J Park · 2001 to 2026
$15.8M
Personal tumor neoantigens for immunity against chronic lymphocytic leukemiaR01CA155010 · NCI · DANA-FARBER CANCER INST · PI Catherine Ju-Ying Wu · 2011 to 2026
$9.6M
NCI NIH HHS P50 CA101942NCI NIH HHS R01 CA155010NCI NIH HHS U24 CA160034NHGRI NIH HHS T32 HG002295
6 · The paper itself

Abstract

Identification of human leukocyte antigen (HLA)-bound peptides by liquid chromatography-tandem mass spectrometry (LC-MS/MS) is poised to provide a deep understanding of rules underlying antigen presentation. However, a key obstacle is the ambiguity that arises from the co-expression of multiple HLA alleles. Here, we have implemented a scalable mono-allelic strategy for profiling the HLA peptidome. By using cell lines expressing a single HLA allele, optimizing immunopurifications, and developing an application-specific spectral search algorithm, we identified thousands of peptides bound to 16 different HLA class I alleles. These data enabled the discovery of subdominant binding motifs and an integrative analysis quantifying the contribution of factors critical to epitope presentation, such as protein cleavage and gene expression. We trained neural-network prediction algorithms with our large dataset (>24,000 peptides) and outperformed algorithms trained on datasets of peptides with measured affinities. We thus demonstrate a strategy for systematically learning the rules of endogenous antigen presentation.

Indexed as

AlgorithmsAllelesAntigen PresentationCell LineChromatography, LiquidEpitopesGene Expression ProfilingHistocompatibility Antigens Class IHumansNeural Networks, ComputerPeptidesProtein Interaction Domains and MotifsTandem Mass SpectrometryEpitopesHistocompatibility Antigens Class IPeptides

Identifiers

PMID28228285
PMCPMC5405381

What OpenQuestion holds

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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.