Combining MALDI-MS with machine learning for metabolomic characterization of lung cancer patient sera
Xiaopin Lai, Kunbin Guo, Wei Huang, Yang Su, Siyu Chen, Qiongdan Li, Kaiqing Liang, Wenhua Gao, Xin Wang, Yuping Chen, Hongbiao Wang, Wen Lin, Xiaolong Wei, Wen‐Xiu Ni, Yan Lin, Dazhi Jiang, Yu-Hong Cheng, Chi‐Ming Che, Kwan‐Ming Ng
Abstract
< 0.001) between 34 lung cancer patients and 26 healthy controls were selected as significant potential biomarkers of lung cancer. 6 out of the 13 distinctive features were identified as intact metabolites. Our results demonstrate the potential for clinical application of MALDI-MS in serum metabolomics for biomarker screening in lung cancer.
Topics & Concepts
MetabolomicsMetaboliteLung cancerBiomarker discoveryBiomarkerMass spectrometryCancerMatrix-assisted laser desorption/ionizationDiagnostic biomarkerChromatographyChemistryMedicineInternal medicineProteomicsDesorptionBiochemistryAdsorptionGeneOrganic chemistryMetabolomics and Mass Spectrometry StudiesMass Spectrometry Techniques and ApplicationsAnalytical Chemistry and Chromatography