Biofluid Metabolic Profiling for Lung Cancer Screening via Reactive Matrix-Assisted Laser Desorption Ionization Mass Spectrometry.
Zhengzhou LiChen SunKe JiaXiao WangJing HanJunyu ChenJiyun WangHuihui LiuZongxiu NiePublished in: Analytical chemistry (2023)
Lung cancer (LC) has the highest mortality rate among various cancer diseases. Developing an early screening method for LC with high classification accuracy is essential. Herein, 2-hydrazinoquinoline (2-HQ) is utilized as a dual-mode reactive matrix for metabolic fingerprint analysis and LC screening via matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS). Metabolites in both positive mode and negative mode can be detected using 2-HQ as the matrix, and derivative analysis of aldehyde and ketone compounds can be achieved simultaneously. Hundreds of serum and urine samples from LC patients and healthy volunteers were analyzed. Combined with machine learning, LC patients and healthy volunteers were successfully distinguished with a high area under the curve value (0.996 for blind serum samples and 0.938 for urine). The MS signal was identified for metabolic profiling, and dysregulated metabolites of the LC group were analyzed. The above results showed that this method has great potential for rapid screening of LC.
Keyphrases
- mass spectrometry
- liquid chromatography
- simultaneous determination
- machine learning
- end stage renal disease
- ms ms
- newly diagnosed
- high performance liquid chromatography
- ejection fraction
- chronic kidney disease
- gas chromatography
- high resolution
- capillary electrophoresis
- tandem mass spectrometry
- multiple sclerosis
- prognostic factors
- high resolution mass spectrometry
- patient reported outcomes
- single cell
- peritoneal dialysis
- squamous cell carcinoma
- young adults
- cardiovascular disease
- risk assessment
- cardiovascular events
- sensitive detection
- risk factors
- big data
- squamous cell
- water soluble