Biofluids Metabolic Profiling Based on PS@Fe 3 O 4 -NH 2 Magnetic Beads-Assisted LDI-MS for Liver Cancer Screening.
Liuying HeXiao WangJunyu ChenYuze LiLiping WangCaiqiao XiongZongxiu NiePublished in: Analytical chemistry (2022)
Liver cancer (LC) is the third frequent cause of death worldwide, so early diagnosis of liver cancer patients is crucial for disease management. Herein, we applied NH 2 -coated polystyrene@Fe 3 O 4 magnetic beads (PS@Fe 3 O 4 -NH 2 MBs) as a matrix material in laser desorption/ionization mass spectrometry (LDI-MS). Rapid, sensitive, and selective metabolic profiling of the native biofluids was achieved without any inconvenient enrichment or purification. Then, based on the selected m / z features, LC patients were discriminated from healthy controls (HCs) by machine learning, with the high area under the curve (AUC) values for urine and serum assessments (0.962 and 0.935). Moreover, initial-diagnosed and subsequent-visited LC patients were also differentiated, which indicates potential applications of this method in early diagnosis. Furthermore, among these identified compounds by FT-ICR MS, the expression level of some metabolites changed from HCs to LCs, including 29 and 12 characteristic metabolites in human urine and serum samples, respectively. These results suggest that PS@Fe 3 O 4 -NH 2 MBs-assisted LDI-MS coupled with machine learning is feasible for LC clinical diagnosis.
Keyphrases
- mass spectrometry
- ms ms
- machine learning
- liquid chromatography
- end stage renal disease
- multiple sclerosis
- chronic kidney disease
- ejection fraction
- newly diagnosed
- peritoneal dialysis
- simultaneous determination
- prognostic factors
- room temperature
- high resolution
- endothelial cells
- high performance liquid chromatography
- single cell
- gas chromatography
- capillary electrophoresis
- poor prognosis
- deep learning
- molecularly imprinted
- solid phase extraction
- climate change
- patient reported
- big data