Evidence map›Paper›PMID 29658117›Full record

ReviewImmunology2018

Mapping the tumour human leukocyte antigen (HLA) ligandome by mass spectrometry.

Lena Katharina Freudenmann, Ana Marcu, Stefan Stevanović

Abstract readReview
In one paragraph

Review in Immunology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
68citing 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

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

  1. Pooled it
  2. Trial
  3. Trial
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Review
  12. Review
  13. Article
  14. Review
  15. Review
  16. Review
  17. Review
  18. Article
  19. TOFNature communications · 2023
    Article
  20. Article

8 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

3 authors.

Lena Katharina FreudenmannInterfaculty Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany.ORCID 0000-0002-9827-4979
Ana MarcuInterfaculty Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany.ORCID 0000-0003-0808-8097
Stefan StevanovićInterfaculty Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany.ORCID 0000-0003-1954-7762

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The entirety of human leukocyte antigen (HLA)-presented peptides is referred to as the HLA ligandome of a cell or tissue, in tumours often termed immunopeptidome. Mapping the tumour immunopeptidome by mass spectrometry (MS) comprehensively views the pathophysiologically relevant antigenic signature of human malignancies. MS is an unbiased approach stringently filtering the candidates to be tested as opposed to epitope prediction algorithms. In the setting of peptide-specific immunotherapies, MS-based strategies significantly diminish the risk of lacking clinical benefit, as they yield highly enriched amounts of truly presented peptides. Early immunopeptidomic efforts were severely limited by technical sensitivity and manual spectra interpretation. The technological progress with development of orbitrap mass analysers and enhanced chromatographic performance led to vast improvements in mass accuracy, sensitivity, resolution, and speed. Concomitantly, bioinformatic tools were developed to process MS data, integrate sequencing results, and deconvolute multi-allelic datasets. This enabled the immense advancement of tumour immunopeptidomics. Studying the HLA-presented peptide repertoire bears high potential for both answering basic scientific questions and translational application. Mapping the tumour HLA ligandome has started to significantly contribute to target identification for the design of peptide-specific cancer immunotherapies in clinical trials and compassionate need treatments. In contrast to prediction algorithms, rare HLA allotypes and HLA class II can be adequately addressed when choosing MS-guided target identification platforms. Herein, we review the identification of tumour HLA ligands focusing on sources, methods, bioinformatic data analysis, translational application, and provide an outlook on future developments.

Indexed as

Epitope MappingLigandsMass SpectrometryAnimalsAntigens, NeoplasmComputational BiologyEpitopesHLA AntigensHumansImmunotherapyNeoplasmsPeptidesPrecision MedicineProtein Processing, Post-TranslationalTranslational Research, BiomedicalAntigens, NeoplasmEpitopesHLA AntigensLigandsPeptidescancer immunotherapyHLA ligandimmunopeptidomemass spectrometryTAAtumour-associated antigen

Identifiers

PMID29658117
PMCPMC6002237

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.