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Mapping the melanoma plasma proteome (MPP) using single-shot proteomics interfaced with the WiMT database

Almeida, Natália LU ; Rodriguez, Jimmy ; Parada, Indira Pla LU orcid ; Perez-Riverol, Yasset ; Woldmar, Nicole LU ; Kim, Yonghyo LU ; Oskolas, Henriett LU ; Betancourt, Lazaro LU ; Valdés, Jeovanis Gil LU and Sahlin, K. Barbara LU , et al. (2021) In Cancers 13(24).
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... (More)

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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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Biomarkers, Malignant melanoma, Plasma, Proteome, Proteomics, WiMT
in
Cancers
volume
13
issue
24
article number
6224
publisher
MDPI AG
external identifiers
  • scopus:85120796871
  • pmid:34944842
ISSN
2072-6694
DOI
10.3390/cancers13246224
language
English
LU publication?
yes
id
36717e82-57e3-4179-8148-120a73590d57
date added to LUP
2022-01-31 10:03:06
date last changed
2024-06-16 00:43:24
@article{36717e82-57e3-4179-8148-120a73590d57,
  abstract     = {{<p>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 &gt;1200 proteins from &gt;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.</p>}},
  author       = {{Almeida, Natália and Rodriguez, Jimmy and Parada, Indira Pla and Perez-Riverol, Yasset and Woldmar, Nicole and Kim, Yonghyo and Oskolas, Henriett and Betancourt, Lazaro and Valdés, Jeovanis Gil and Sahlin, K. Barbara and Pizzatti, Luciana and Szasz, A. Marcell and Kárpáti, Sarolta and Appelqvist, Roger and Malm, Johan and Domont, Gilberto B. and Nogueira, Fábio C.S. and Marko-Varga, György and Sanchez, Aniel}},
  issn         = {{2072-6694}},
  keywords     = {{Biomarkers; Malignant melanoma; Plasma; Proteome; Proteomics; WiMT}},
  language     = {{eng}},
  month        = {{12}},
  number       = {{24}},
  publisher    = {{MDPI AG}},
  series       = {{Cancers}},
  title        = {{Mapping the melanoma plasma proteome (MPP) using single-shot proteomics interfaced with the WiMT database}},
  url          = {{http://dx.doi.org/10.3390/cancers13246224}},
  doi          = {{10.3390/cancers13246224}},
  volume       = {{13}},
  year         = {{2021}},
}