Evidence map›Paper›PMID 37211046›Full record

ArticleMolecular & cellular proteomics : MCP2023

Large-Scale Plasma Proteome Epitome Profiling is an Efficient Tool for the Discovery of Cancer Biomarkers.

Jozsef Lazar, Peter Antal-Szalmas, Istvan Kurucz, Annamaria Ferenczi, Mihaly Jozsi, Ilona Tornyi, Monika Muller, Janos Tibor Fekete, John Lamont, Peter FitzGerald and 23 more

Abstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Proteomics and Its Applications in Cancers 2.0.International journal of molecular sciences · 2024
    Article
  6. Article
  7. Review
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

33 authors.

Jozsef LazarBiosystems International Kft., Debrecen, Hungary; Biosystems Immunolab Zrt., Debrecen, Hungary. Electronic address: jozsef.lazar@biosys-ilab.com.
Peter Antal-SzalmasBiosystems Immunolab Zrt., Debrecen, Hungary; Department of Laboratory Medicine, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
Istvan KuruczBiosystems International Kft., Debrecen, Hungary; Biosystems Immunolab Zrt., Debrecen, Hungary.
Annamaria FerencziBiosystems International Kft., Debrecen, Hungary.
Mihaly JozsiDepartment of Immunology, ELTE Eötvös Loránd University, Budapest, Hungary; MTA-ELTE Complement Research Group, Eötvös Loránd Research Network (ELKH), Budapest, Hungary.
Ilona TornyiBiosystems Immunolab Zrt., Debrecen, Hungary; Department of Human Genetics, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
Monika MullerAdware Research Kft., Balatonfüred, Hungary.
Janos Tibor FeketeDepartment of Bioinformatics, Semmelweis University, Budapest, Hungary.
John LamontRandox Laboratories Ltd, Crumlin, United Kingdom.
Peter FitzGeraldRandox Laboratories Ltd, Crumlin, United Kingdom.
Anna Gall-DebreceniBiosystems International Kft., Debrecen, Hungary.
Janos KadasBiosystems International Kft., Debrecen, Hungary.
Andras VidaDepartment of Laboratory Medicine, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
Nadege TardieuBiosystems International SAS, Evry, France.
Yann KiefferBiosystems International SAS, Evry, France.
Anne JullienBiosystems International SAS, Evry, France.
Mariana Guergova-KurasBiosystems International SAS, Evry, France.
William HempelBiosystems International SAS, Evry, France.
Andras KovacsBiosystems Immunolab Zrt., Debrecen, Hungary.
Tamas KardosDepartment of Pulmonology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
Nora BittnerDepartment of Pulmonology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
Eszter CsankyDepartment of Pulmonology, Miskolc Semmelweis Hospital and University Hospital, Miskolc, Hungary.
Maria SzilasiDepartment of Pulmonology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
Gyorgy LosonczyDepartment of Pulmonology, Faculty of Medicine, Semmelweis University, Budapest, Hungary.
Klara SzondyDepartment of Pulmonology, Faculty of Medicine, Semmelweis University, Budapest, Hungary.
Gabriella GalffyDepartment of Pulmonology, Faculty of Medicine, Semmelweis University, Budapest, Hungary.
Edit CsadaCsongrád County Hospital of Chest Diseases, Deszk, Hungary.
Klara SzalontaiCsongrád County Hospital of Chest Diseases, Deszk, Hungary.
Attila SomfayDepartment of Pulmonology, Faculty of Medicine, University of Szeged, Deszk, Hungary.
David MalkaDepartment of Medical Oncology, Gustave Roussy, Villejuif, France.
Paul CottuDepartment of Medical Oncology, Institut Curie, Paris, France.
Krisztina BogosNational Koranyi Institute for Pulmonology, Budapest, Hungary.
Laszlo TakacsBiosystems International Kft., Debrecen, Hungary; Biosystems Immunolab Zrt., Debrecen, Hungary; Department of Human Genetics, Faculty of Medicine, University of Debrecen, Debrecen, Hungary; Biosystems International SAS, Evry, France. Electronic address: laszlo.takacs@biosys-ilab.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current proteomic technologies focus on the quantification of protein levels, while little effort is dedicated to the development of system approaches to simultaneously monitor proteome variability and abundance. Protein variants may display different immunogenic epitopes detectable by monoclonal antibodies. Epitope variability results from alternative splicing, posttranslational modifications, processing, degradation, and complex formation and possesses dynamically changing availability of interacting surface structures that frequently serve as reachable epitopes and often carry different functions. Thus, it is highly likely that the presence of some of the accessible epitopes correlates with function under physiological and pathological conditions. To enable the exploration of the impact of protein variation on the immunogenic epitome first, here, we present a robust and analytically validated PEP technology for characterizing immunogenic epitopes of the plasma. To this end, we prepared mAb libraries directed against the normalized human plasma proteome as a complex natural immunogen. Antibody producing hybridomas were selected and cloned. Monoclonal antibodies react with single epitopes, thus profiling with the libraries is expected to profile many epitopes which we define by the mimotopes, as we present here. Screening blood plasma samples from control subjects (n = 558) and cancer patients (n = 598) for merely 69 native epitopes displayed by 20 abundant plasma proteins resulted in distinct cancer-specific epitope panels that showed high accuracy (AUC 0.826-0.966) and specificity for lung, breast, and colon cancer. Deeper profiling (≈290 epitopes of approximately 100 proteins) showed unexpected granularity of the epitope-level expression data and detected neutral and lung cancer-associated epitopes of individual proteins. Biomarker epitope panels selected from a pool of 21 epitopes of 12 proteins were validated in independent clinical cohorts. The results demonstrate the value of PEP as a rich and thus far unexplored source of protein biomarkers with diagnostic potential.

Indexed as

Biomarkers, TumorNeoplasmsAntibodies, MonoclonalEpitopesHumansProteomeProteomicsAntibodies, MonoclonalBiomarkers, TumorEpitopesProteomebiomarkercancerepitopelung cancerplasma epitom profilingprotein variantsproteoform

Identifiers

PMID37211046
PMCPMC10319867

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Registered trials

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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.