Evidence map›Paper›PMID 38857186›Full record

ArticleDatabase : the journal of biological databases and curation2024

The Immunopeptidomics Ontology (ImPO).

Daniel Faria, Patrícia Eugénio, Marta Contreiras Silva, Laura Balbi, Georges Bedran, Ashwin Adrian Kallor, Susana Nunes, Aleksander Palkowski, Michal Waleron, Javier A Alfaro and 1 more

Abstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Daniel FariaINESC-ID, Instituto Superior Técnico, Universidade de Lisboa, Rua Alves Redol, 9, Lisboa 1000-029, Portugal.
Patrícia EugénioLASIGE, Faculdade de Ciências da Universidade de Lisboa, Campo Grande, Lisboa 1749-016, Portugal.ORCID 0000-0002-2329-3753
Marta Contreiras SilvaLASIGE, Faculdade de Ciências da Universidade de Lisboa, Campo Grande, Lisboa 1749-016, Portugal.
Laura BalbiLASIGE, Faculdade de Ciências da Universidade de Lisboa, Campo Grande, Lisboa 1749-016, Portugal.
Georges BedranInternational Centre for Cancer Vaccine Science, University of Gdansk, ul. Kładki 24, Gdańsk 80-822, Poland.
Ashwin Adrian KallorInternational Centre for Cancer Vaccine Science, University of Gdansk, ul. Kładki 24, Gdańsk 80-822, Poland.
Susana NunesLASIGE, Faculdade de Ciências da Universidade de Lisboa, Campo Grande, Lisboa 1749-016, Portugal.
Aleksander PalkowskiInternational Centre for Cancer Vaccine Science, University of Gdansk, ul. Kładki 24, Gdańsk 80-822, Poland.
Michal WaleronInternational Centre for Cancer Vaccine Science, University of Gdansk, ul. Kładki 24, Gdańsk 80-822, Poland.
Javier A AlfaroInternational Centre for Cancer Vaccine Science, University of Gdansk, ul. Kładki 24, Gdańsk 80-822, Poland.
Catia PesquitaLASIGE, Faculdade de Ciências da Universidade de Lisboa, Campo Grande, Lisboa 1749-016, Portugal.

Funding

European Union's Horizon 2020 101017453Fundação para a Ciência e a Tecnologia UIDB/00408/2020 UIDP/00408/2020Fundacja na rzecz Nauki Polskiej
6 · The paper itself

Abstract

The adaptive immune response plays a vital role in eliminating infected and aberrant cells from the body. This process hinges on the presentation of short peptides by major histocompatibility complex Class I molecules on the cell surface. Immunopeptidomics, the study of peptides displayed on cells, delves into the wide variety of these peptides. Understanding the mechanisms behind antigen processing and presentation is crucial for effectively evaluating cancer immunotherapies. As an emerging domain, immunopeptidomics currently lacks standardization-there is neither an established terminology nor formally defined semantics-a critical concern considering the complexity, heterogeneity, and growing volume of data involved in immunopeptidomics studies. Additionally, there is a disconnection between how the proteomics community delivers the information about antigen presentation and its uptake by the clinical genomics community. Considering the significant relevance of immunopeptidomics in cancer, this shortcoming must be addressed to bridge the gap between research and clinical practice. In this work, we detail the development of the ImmunoPeptidomics Ontology, ImPO, the first effort at standardizing the terminology and semantics in the domain. ImPO aims to encapsulate and systematize data generated by immunopeptidomics experimental processes and bioinformatics analysis. ImPO establishes cross-references to 24 relevant ontologies, including the National Cancer Institute Thesaurus, Mondo Disease Ontology, Logical Observation Identifier Names and Codes and Experimental Factor Ontology. Although ImPO was developed using expert knowledge to characterize a large and representative data collection, it may be readily used to encode other datasets within the domain. Ultimately, ImPO facilitates data integration and analysis, enabling querying, inference and knowledge generation and importantly bridging the gap between the clinical proteomics and genomics communities. As the field of immunogenomics uses protein-level immunopeptidomics data, we expect ImPO to play a key role in supporting a rich and standardized description of the large-scale data that emerging high-throughput technologies are expected to bring in the near future. Ontology URL: https://zenodo.org/record/10237571 Project GitHub: https://github.com/liseda-lab/ImPO/blob/main/ImPO.owl.

Indexed as

Biological OntologiesDatabases, ProteinHumansPeptidesProteomicsPeptides

Identifiers

PMID38857186
PMCPMC11164101

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.