Chem. J. Chinese Universities ›› 2024, Vol. 45 ›› Issue (11): 20240311.doi: 10.7503/cjcu20240311

• Article • Previous Articles     Next Articles

Quantitative Accuracy Evaluation of Mass Spectrometry Based Proteomics Methods Commonly Used in Biomarker Research

ZHANG Lei, SHEN Huali()   

  1. Institute of Biomedical Science,Fudan University,Shanghai 200032,China
  • Received:2024-06-26 Online:2024-11-10 Published:2024-08-07
  • Contact: SHEN Huali E-mail:shenhuali@fudan.edu.cn
  • Supported by:
    the National Natural Science Foundation of China(82272174);the Science and Technology Innovation Action Plan of STCSM, China(22S31901900)

Abstract:

In the progression of diseases, changes in protein expression levels, modification states, or interaction patterns may reflect pathological conditions or disease advancement, making proteins commonly used as disease biomarkers. Mass spectrometry-based proteomics has identified numerous potential disease biomarkers. However, these biomarkers and their mass spectrometry detection methods need to have high quantitative accuracy and stability for further clinical application. This study synthesized 32 standard peptides and evaluated three quantitative methods data independent acquisition(DIA), multiple reaction monitoring(MRM), and parallel reaction monitoring(PRM), for their potential in large-scale clinical applications in mass spectrometry. We simulated actual samples at four different concentrations to assess peptide discovery rates, standard curve linearity, inter-day and intra-day precision, and retention time shift using the aforementioned three mass spectrometry methods. The results indicate that MRM quantification is most suitable for clinical applications due to its good stability, sensitivity, and quantitative accuracy. PRM is suitable for targeted quantification in research settings, which can offer high sensitivity and stability. Finally, despite its high throughput nature, DIA demonstrates inferior quantitative accuracy for specific peptides compared to PRM and MRM.

Key words: Clinical mass spectrometry, Proteomics, Parallel reaction monitoring, Multiple reaction monitoring, Data independent acquisition

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