Abstract
Quantitative determination of endogenous compounds in biological samples has still been challenged by the absence of authentic blank matrix. Alternative strategy of surrogate matrix for preparing reference samples are prevalent due to its low cost and high availability. However, the evaluation system of surrogate matrix is not perfect. Herein, a novel multifunctional isotopic standards based steroidomics strategy was developed. Isotope-labeled standards were used not only as internal standards but also for the evaluation the feasibility of surrogate matrix, which improved the accuracy of assessment and could provide a new prospect for the quantitative analysis of endogenous compounds. Based on this approach, a detailed optimization from LC separation, MS detection to extraction conditions for global steroids in the steroidogenesis was firstly carried out. Characteristics and regularities of steroids in LC–MS were summarized to make references for further targeted or untargeted steroidomics study. Then eighteen steroids were quantified with high accuracy and high sensitivity in plasma from four types of cancer patients and healthy subjects using 1% BSA in PBS as surrogate matrix. And multi-steroids indexes with the best discriminating ability for lung, colorectal, breast and gastric cancer in different genders were identified successfully with Student's t-test, PLS-DA and logistic regression- ROC curve analysis. Finally, efficient cancer screening workflow was established by integrating the amine submetabolomics and lipidomics data of our previous studies. Taken together, the integrated steroidomics strategy could shed a light on the guidance for further steroidome as well as other endogenous compounds analysis and may provide a powerful tool for cancer diagnosis.
Original language | English (US) |
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Article number | 460723 |
Journal | Journal of Chromatography A |
Volume | 1614 |
DOIs | |
State | Published - Mar 15 2020 |
Funding
This work was supported by the National Natural Science Foundation of China (Grant Nos. 81473324 , 81372329 , 81603277/H2803 and 81703463/H3010 ) and Liaoning Distinguished Professor Project for Qing Li (2017). This work was supported by the National Natural Science Foundation of China (Grant Nos. 81473324, 81372329, 81603277/H2803 and 81703463/H3010) and Liaoning Distinguished Professor Projectfor Qing Li (2017).
Keywords
- Cancer biomarkers
- Multifunctional isotopic standards
- Steroidomics
- Surrogate matrix
ASJC Scopus subject areas
- Analytical Chemistry
- Biochemistry
- Organic Chemistry