Evidence map›Paper›PMID 29786170›Full record

ArticleProteomics2018

Immunopeptidomic Profiling of HLA-A2-Positive Triple Negative Breast Cancer Identifies Potential Immunotherapy Target Antigens.

Nicola Ternette, Marloes J M Olde Nordkamp, Julius Müller, Amanda P Anderson, Annalisa Nicastri, Adrian V S Hill, Benedikt M Kessler, Demin Li

Open access · hybridAbstract read
In one paragraph

Article in Proteomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

30 citing papers in PubMed, 48 citations in OpenAlex.

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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

8 authors at 3 institutions in 1 country.

Nicola TernetteThe Jenner Institute, University of Oxford, Oxford, OX3 7FZ, UK.ORCID 0000-0002-9283-0743
Marloes J M Olde NordkampNuffield Division of Clinical Laboratory Sciences, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 9DU, UK.
Julius MüllerThe Jenner Institute, University of Oxford, Oxford, OX3 7FZ, UK.
Amanda P AndersonNuffield Division of Clinical Laboratory Sciences, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 9DU, UK.
Annalisa NicastriTarget Discovery Institute, Nuffield Department of Medicine, Oxford, OX3 7FZ, UK.
Adrian V S HillThe Jenner Institute, University of Oxford, Oxford, OX3 7FZ, UK.
Benedikt M KesslerTarget Discovery Institute, Nuffield Department of Medicine, Oxford, OX3 7FZ, UK.
Demin LiNuffield Division of Clinical Laboratory Sciences, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 9DU, UK.ORCID 0000-0002-7118-3401
John Radcliffe Hospital · GBNuffield Orthopaedic Centre · GBUniversity of Oxford · GB

Funding

Cancer Research UK C10396/A21667
6 · The paper itself

Abstract

The recent development in immune checkpoint inhibitors and chimeric antigen receptor (CAR) T-cells in the treatment of cancer has not only demonstrated the potency of utilizing T-cell reactivity for cancer therapy, but has also highlighted the need for developing new approaches to discover targets suitable for such novel therapeutics. Here we analyzed the immunopeptidomes of six HLA-A2-positive triple negative breast cancer (TNBC) samples by nano-ultra performance liquid chromatography tandem mass spectrometry (nUPLC-MS

Indexed as

ImmunotherapyAdultAgedAged, 80 and overAntigens, NeoplasmFemaleHLA-A2 AntigenHumansMiddle AgedPeptide FragmentsTriple Negative Breast NeoplasmsAntigens, NeoplasmHLA-A2 AntigenPeptide FragmentsaTaCCbreast cancerHLA-A2immunopeptidomemass spectrometry

Identifiers

PMID29786170
PMCPMC6032843
OpenAlexW2803894013

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.