Evidence map›Paper›PMID 34944842›Full record

ArticleCancers2021

Mapping the Melanoma Plasma Proteome (MPP) Using Single-Shot Proteomics Interfaced with the WiMT Database.

Natália Almeida, Jimmy Rodriguez, Indira Pla Parada, Yasset Perez-Riverol, Nicole Woldmar, Yonghyo Kim, Henriett Oskolas, Lazaro Betancourt, Jeovanis Gil Valdés, K Barbara Sahlin and 9 more

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 33% 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

5 citing papers in PubMed, 10 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

19 authors at 6 institutions in 6 countries.

Natália AlmeidaLaboratory of Proteomics/LADETEC, Universidade Federal Do Rio de Janeiro, Rio de Janeiro 21941-598, Brazil.
Jimmy RodriguezDivision of Chemistry I, Department of Biochemistry and Biophysics, Karolinska Institute, 17165 Stockholm, Sweden.
Indira Pla ParadaSection for Clinical Chemistry, Department of Translational Medicine, Lund University, Skåne University Hospital Malmö, 20502 Malmö, Sweden.ORCID 0000-0002-0839-7829
Yasset Perez-RiverolEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.ORCID 0000-0001-6579-6941
Nicole WoldmarClinical Protein Science & Imaging, Biomedical Center, Department of Biomedical Engineering, Lund University, BMC D13, 22184 Lund, Sweden.
Yonghyo KimData Convergence Drug Research Center, Therapeutics and Biotechnology Division, Korea Research Institute of Chemical Technology (KRICT), Daejeon 34114, Korea.ORCID 0000-0002-4447-9864
Henriett OskolasDivision of Oncology, Department of Clinical Sciences Lund, Lund University, 22185 Lund, Sweden.
Lazaro BetancourtDivision of Oncology, Department of Clinical Sciences Lund, Lund University, 22185 Lund, Sweden.
Jeovanis Gil ValdésDivision of Oncology, Department of Clinical Sciences Lund, Lund University, 22185 Lund, Sweden.
K Barbara SahlinClinical Protein Science & Imaging, Biomedical Center, Department of Biomedical Engineering, Lund University, BMC D13, 22184 Lund, Sweden.ORCID 0000-0003-3035-3256
Luciana PizzattiLaboratory of Molecular Biology and Blood Proteomics-LADETEC, Institute of Chemistry, Federal University of Rio de Janeiro, Rio de Janeiro 21941-598, Brazil.ORCID 0000-0001-5513-782X
A Marcell SzaszOncology Center, Semmelweis University, 1083 Budapest, Hungary.
Sarolta KárpátiDepartment of Dermatology, Venereology and Dermatooncology, Semmelweis University, 1085 Budapest, Hungary.
Roger AppelqvistDivision of Oncology, Department of Clinical Sciences Lund, Lund University, 22185 Lund, Sweden.ORCID 0000-0001-7450-7216
Johan MalmSection for Clinical Chemistry, Department of Translational Medicine, Lund University, Skåne University Hospital Malmö, 20502 Malmö, Sweden.ORCID 0000-0002-9365-7313
Gilberto B DomontProteomics Unit, Institute of Chemistry, Universidade Federal Do Rio de Janeiro, Rio de Janeiro 21941-909, Brazil.
Fábio C S NogueiraLaboratory of Proteomics/LADETEC, Universidade Federal Do Rio de Janeiro, Rio de Janeiro 21941-598, Brazil.
György Marko-VargaClinical Protein Science & Imaging, Biomedical Center, Department of Biomedical Engineering, Lund University, BMC D13, 22184 Lund, Sweden.
Aniel SanchezSection for Clinical Chemistry, Department of Translational Medicine, Lund University, Skåne University Hospital Malmö, 20502 Malmö, Sweden.ORCID 0000-0002-0278-8802
Lund University · SEUniversidade Federal do Rio de Janeiro · BRSemmelweis University · HUEuropean Bioinformatics Institute · GBKarolinska Institutet · SETokyo Medical University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plasma analysis by mass spectrometry-based proteomics remains a challenge due to its large dynamic range of 10 orders in magnitude. We created a methodology for protein identification known as Wise MS Transfer (WiMT). Melanoma plasma samples from biobank archives were directly analyzed using simple sample preparation. WiMT is based on MS1 features between several MS runs together with custom protein databases for ID generation. This entails a multi-level dynamic protein database with different immunodepletion strategies by applying single-shot proteomics. The highest number of melanoma plasma proteins from undepleted and unfractionated plasma was reported, mapping >1200 proteins from >10,000 protein sequences with confirmed significance scoring. Of these, more than 660 proteins were annotated by WiMT from the resulting ~5800 protein sequences. We could verify 4000 proteins by MS1t analysis from HeLA extracts. The WiMT platform provided an output in which 12 previously well-known candidate markers were identified. We also identified low-abundant proteins with functions related to (i) cell signaling, (ii) immune system regulators, and (iii) proteins regulating folding, sorting, and degradation, as well as (iv) vesicular transport proteins. WiMT holds the potential for use in large-scale screening studies with simple sample preparation, and can lead to the discovery of novel proteins with key melanoma disease functions.

Indexed as

biomarkersmalignant melanomaplasmaproteomeproteomicsWiMT

Identifiers

PMID34944842
PMCPMC8699267
OpenAlexW4200424585

What OpenQuestion holds

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LicenceCC BY
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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.