Urine Proteome Profiling Predicts Lung Cancer from Control Cases and Other Tumors.

ABSTRACT: Development of noninvasive, reliable biomarkers for lung cancer diagnosis has many clinical benefits knowing that most of lung cancer patients are diagnosed at the late stage. For this purpose, we conducted proteomic analyses of 231 human urine samples in healthy individuals (n=33), benign pulmonary diseases (n=40), lung cancer (n=33), bladder cancer (n=17), cervical cancer (n=25), colorectal cancer (n=22), esophageal cancer (n=14), and gastric cancer (n=47) patients collected from multiple medical centers. By random forest modeling, we nominated a list of urine proteins that could separate lung cancers from other cases. With a feature selection algorithm, we selected a panel of five urinary biomarkers (FTL: Ferritin light chain; MAPK1IP1L: Mitogen-Activated Protein Kinase 1 Interacting Pr

SUBMITTER: Zhang C 

PROVIDER: S-EPMC5952250 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature