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Mapping the Melanoma Plasma Proteome (MPP) Using Single-Shot Proteomics Interfaced with the WiMT Database.
Almeida, Natália; Rodriguez, Jimmy; Pla Parada, Indira; Perez-Riverol, Yasset; Woldmar, Nicole; Kim, Yonghyo; Oskolas, Henriett; Betancourt, Lazaro; Valdés, Jeovanis Gil; Sahlin, K Barbara; Pizzatti, Luciana; Szasz, A Marcell; Kárpáti, Sarolta; Appelqvist, Roger; Malm, Johan; B Domont, Gilberto; C S Nogueira, Fábio; Marko-Varga, György; Sanchez, Aniel.
Afiliación
  • Almeida N; Laboratory of Proteomics/LADETEC, Universidade Federal Do Rio de Janeiro, Rio de Janeiro 21941-598, Brazil.
  • Rodriguez J; Proteomics Unit, Institute of Chemistry, Universidade Federal Do Rio de Janeiro, Rio de Janeiro 21941-909, Brazil.
  • Pla Parada I; Clinical Protein Science & Imaging, Biomedical Center, Department of Biomedical Engineering, Lund University, BMC D13, 22184 Lund, Sweden.
  • Perez-Riverol Y; Division of Chemistry I, Department of Biochemistry and Biophysics, Karolinska Institute, 17165 Stockholm, Sweden.
  • Woldmar N; Section for Clinical Chemistry, Department of Translational Medicine, Lund University, Skåne University Hospital Malmö, 20502 Malmö, Sweden.
  • Kim Y; European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
  • Oskolas H; Clinical Protein Science & Imaging, Biomedical Center, Department of Biomedical Engineering, Lund University, BMC D13, 22184 Lund, Sweden.
  • Betancourt L; Laboratory of Molecular Biology and Blood Proteomics-LADETEC, Institute of Chemistry, Federal University of Rio de Janeiro, Rio de Janeiro 21941-598, Brazil.
  • Valdés JG; Data Convergence Drug Research Center, Therapeutics and Biotechnology Division, Korea Research Institute of Chemical Technology (KRICT), Daejeon 34114, Korea.
  • Sahlin KB; Division of Oncology, Department of Clinical Sciences Lund, Lund University, 22185 Lund, Sweden.
  • Pizzatti L; Division of Oncology, Department of Clinical Sciences Lund, Lund University, 22185 Lund, Sweden.
  • Szasz AM; Division of Oncology, Department of Clinical Sciences Lund, Lund University, 22185 Lund, Sweden.
  • Kárpáti S; Division of Oncology, Department of Clinical Sciences Lund, Lund University, 22185 Lund, Sweden.
  • Appelqvist R; Clinical Protein Science & Imaging, Biomedical Center, Department of Biomedical Engineering, Lund University, BMC D13, 22184 Lund, Sweden.
  • Malm J; Section for Clinical Chemistry, Department of Translational Medicine, Lund University, Skåne University Hospital Malmö, 20502 Malmö, Sweden.
  • B Domont G; Laboratory of Molecular Biology and Blood Proteomics-LADETEC, Institute of Chemistry, Federal University of Rio de Janeiro, Rio de Janeiro 21941-598, Brazil.
  • C S Nogueira F; Oncology Center, Semmelweis University, 1083 Budapest, Hungary.
  • Marko-Varga G; Department of Dermatology, Venereology and Dermatooncology, Semmelweis University, 1085 Budapest, Hungary.
  • Sanchez A; Division of Oncology, Department of Clinical Sciences Lund, Lund University, 22185 Lund, Sweden.
Cancers (Basel) ; 13(24)2021 Dec 10.
Article en En | MEDLINE | ID: mdl-34944842
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.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Cancers (Basel) Año: 2021 Tipo del documento: Article País de afiliación: Brasil

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Cancers (Basel) Año: 2021 Tipo del documento: Article País de afiliación: Brasil