Improvement of untargeted proteomics workflow for surfaceome profiling and its evaluation through the implementation of quality controls: Application to multiple myeloma.
Multiple myeloma
Quality control
Sample preparation
Surfaceome
Untargeted proteomics
Journal
Analytica chimica acta
ISSN: 1873-4324
Titre abrégé: Anal Chim Acta
Pays: Netherlands
ID NLM: 0370534
Informations de publication
Date de publication:
23 Oct 2023
23 Oct 2023
Historique:
received:
27
06
2023
revised:
28
08
2023
accepted:
29
08
2023
medline:
23
10
2023
pubmed:
13
10
2023
entrez:
12
10
2023
Statut:
ppublish
Résumé
Comprehensive surfaceome profiling of cancer cells using mass spectrometry (MS)-based technologies is a valuable approach to identify new antigens that could be targeted by immunotherapies. Multiple myeloma (MM) is an incurable hematological malignancy in which patients suffer from multiple relapses associated with drug resistance. Nevertheless, only three MM-specific antigens are currently targeted by approved immunotherapies which restrain the availability of efficient treatments for severe refractory patients affected by aggressive forms of the disease. Therefore, the discovery of new antigens in this context could open new perspectives for those patients. In this study, the first objective was to improve a MS-based untargeted proteomics workflow in order to handle limited patient samples. For this purpose, a highly sensitive and robust miniaturized separation system (LC-Chip) coupled with drift tube ion mobility spectrometry and high-resolution MS was integrated in our workflow to maximize protein identification. As sample preparation can strongly influence the detectability of membrane-associated proteins, the critical steps in sample preparation were carefully optimized. As a result, 4.5 times more membrane-associated proteins were identified and experimental throughput was also drastically improved. In addition to workflow performance, particular attention was paid to assess the quality of the generated data. Indeed, several quality controls (QC) were implemented to assess data quality. Finally, the optimized workflow as well as selected QCs were evaluated in the analysis of samples containing limited number of cells. This work allowed the improvement of an untargeted proteomics workflow for surfaceome profiling in terms of performance. Besides, the reliability of the obtained data was evaluated through the introduction of QCs in the workflow. The applicability of the improved workflow as well as the implemented QCs for the analysis of MM primary cells obtained from patients was confirmed.
Sections du résumé
BACKGROUND
BACKGROUND
Comprehensive surfaceome profiling of cancer cells using mass spectrometry (MS)-based technologies is a valuable approach to identify new antigens that could be targeted by immunotherapies. Multiple myeloma (MM) is an incurable hematological malignancy in which patients suffer from multiple relapses associated with drug resistance. Nevertheless, only three MM-specific antigens are currently targeted by approved immunotherapies which restrain the availability of efficient treatments for severe refractory patients affected by aggressive forms of the disease. Therefore, the discovery of new antigens in this context could open new perspectives for those patients.
RESULTS
RESULTS
In this study, the first objective was to improve a MS-based untargeted proteomics workflow in order to handle limited patient samples. For this purpose, a highly sensitive and robust miniaturized separation system (LC-Chip) coupled with drift tube ion mobility spectrometry and high-resolution MS was integrated in our workflow to maximize protein identification. As sample preparation can strongly influence the detectability of membrane-associated proteins, the critical steps in sample preparation were carefully optimized. As a result, 4.5 times more membrane-associated proteins were identified and experimental throughput was also drastically improved. In addition to workflow performance, particular attention was paid to assess the quality of the generated data. Indeed, several quality controls (QC) were implemented to assess data quality. Finally, the optimized workflow as well as selected QCs were evaluated in the analysis of samples containing limited number of cells.
SIGNIFICANCE
CONCLUSIONS
This work allowed the improvement of an untargeted proteomics workflow for surfaceome profiling in terms of performance. Besides, the reliability of the obtained data was evaluated through the introduction of QCs in the workflow. The applicability of the improved workflow as well as the implemented QCs for the analysis of MM primary cells obtained from patients was confirmed.
Identifiants
pubmed: 37827665
pii: S0003-2670(23)00985-6
doi: 10.1016/j.aca.2023.341764
pii:
doi:
Substances chimiques
Membrane Proteins
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
341764Informations de copyright
Copyright © 2023 Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.