Evidence map›Paper›PMID 30532160›Full record

ArticlePloS one2018

Automated phosphopeptide enrichment from minute quantities of frozen malignant melanoma tissue.

Jimmy Rodriguez Murillo, Magdalena Kuras, Melinda Rezeli, Tasso Miliotis, Lazaro Betancourt, Gyorgy Marko-Varga

Erratum issuedAbstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Leveraging HILIC/ERLIC separations for online nanoscale LC-MS/MS analysis of phosphopeptide isoforms from RNA polymerase II C-terminal domain.Journal of chromatography. B, Analytical technologies in the biomedical and life sciences · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Jimmy Rodriguez MurilloClinical Protein Science & Imaging, Department of Clinical Sciences (Lund), Department of Biomedical Engineering, Lund University, Lund, Sweden.
Magdalena KurasClinical Protein Science & Imaging, Department of Clinical Sciences (Lund), Department of Biomedical Engineering, Lund University, Lund, Sweden.
Melinda RezeliClinical Protein Science & Imaging, Department of Clinical Sciences (Lund), Department of Biomedical Engineering, Lund University, Lund, Sweden.
Tasso MiliotisClinical Protein Science & Imaging, Department of Clinical Sciences (Lund), Department of Biomedical Engineering, Lund University, Lund, Sweden.
Lazaro BetancourtClinical Protein Science & Imaging, Department of Clinical Sciences (Lund), Department of Biomedical Engineering, Lund University, Lund, Sweden.ORCID 0000-0001-8207-7041
Gyorgy Marko-VargaClinical Protein Science & Imaging, Department of Clinical Sciences (Lund), Department of Biomedical Engineering, Lund University, Lund, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To acquire a deeper understanding of malignant melanoma (MM), it is essential to study the proteome of patient tissues. In particular, phosphoproteomics of MM has become of significant importance because of the central role that phosphorylation plays in the development of MM. Investigating clinical samples, however, is an extremely challenging task as there is usually only very limited quantities of material available to perform targeted enrichment approaches. Here, an automated phosphopeptide enrichment protocol using the AssayMap Bravo platform was applied to MM tissues and assessed for performance. The strategy proved to be highly-sensitive, less prone to variability, less laborious than existing techniques and adequate for starting quantities at the microgram level. An Fe(III)-NTA-IMAC-based enrichment workflow was applied to a dilution series of MM tissue lysates. The workflow was efficient in terms of sensitivity, reproducibility and phosphosite localization; and from only 12.5 μg of sample, more than 1,000 phosphopeptides were identified. In addition, from 60 μg of protein material the number of identified phosphoproteins from individual MM samples was comparable to previous reports that used extensive fractionation methods. Our data set included key pathways that are involved in MM progression; such as MAPK, melanocyte development and integrin signaling. Moreover, tissue-specific immunological proteins were identified, that have not been previously observed in the proteome of MM-derived cell lines. In conclusion, this workflow is suitable to study large cohorts of clinical samples that demand automatic and careful handling.

Indexed as

AutomationChromatography, AffinityChromatography, High Pressure LiquidCluster AnalysisFerric CompoundsFrozen SectionsHumansIntegrinsMelanomaMitogen-Activated Protein KinasesPhosphopeptidesProteomeSignal TransductionTandem Mass SpectrometryFerric CompoundsIntegrinsMitogen-Activated Protein KinasesPhosphopeptidesProteome

Identifiers

PMID30532160
PMCPMC6287822

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.