ArticleJournal of proteome research2022
A Sensitive and Controlled Data-Independent Acquisition Method for Proteomic Analysis of Cell Therapies.
Article in Journal of proteome research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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.
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Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- Review
- Blood proteome profiling for biomarker discovery in broilers with necrotic enteritis.Scientific reports · 2025Article
- Quantitative Proteomics for the Development and Manufacturing of Human-Induced Pluripotent Stem Cell-Derived Neural Stem Cells Using Data-Independent Acquisition Mass Spectrometry.Journal of proteome research · 2023Article
- Identification markers of goat milk adulterated with bovine milk based on proteomics and metabolomics.Food chemistry: X · 2023Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mass spectrometry (MS)-based proteomic measurements are uniquely poised to impact the development of cell and gene therapies. With the adoption of rigorous instrumental performance qualifications (PQs), large-scale proteomics can move from a research to a manufacturing control tool. Especially suited, data-independent acquisition (DIA) approaches have distinctive qualities to extend multiattribute method (MAM) principles to characterize the proteome of cell therapies. Here, we describe the development of a DIA method for the sensitive identification and quantification of proteins on a Q-TOF instrument. Using the improved acquisition parameters, we defined a control strategy and highlighted some metrics to improve the reproducibility of SWATH acquisition-based proteomic measurements. Finally, we applied the method to analyze the proteome of Jurkat cells that here serves as a model for human T-cells. Raw and processed data were deposited in PRIDE (PXD029780).
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Registered trials
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