Research and Applications of Non-target and Targeted Metabolomics in Urine Samples

Lung cancer mortality ranks first among all malignancies worldwide, and the survival rate is quite low. Currently, there are two methods for diagnosis, low-dose spiral CT (LDCT) (high false positive rate and radiation damage) and tumor tissue testing (gene mutation screening). There is no non-invasive clinical diagnosis mark to guide the treatment for now. The research paper (Non-invasive urinary metabolomic profiling identifies diagnostic and prognostic markers in lung cancer, Cancer Research IF=9.3215) introduced today aims to find biomarkers for lung cancer diagnosis by performing metabolomics tests on urine.

There are three main reasons why this paper can get a good score, great samples, techniques and data analysis.

Samples Used in the Experiment

Prescreening samples (1005 cases): samples collected in 10 years(1998~2007) from 469 patients (urine collected before the treatment) and 536 healthy people.

Samples for later validation (158 cases): Samples collected in 2008-2010 from 80 patients (urine collected before the treatment) and 78 healthy people.

Tissue samples: 48 tumor tissue samples and its surrounding non-tumor tissue samples

Technical Workflow: initial non-targeted screening and post targeted MRM validation

Research results

Initial screening

Untargeted metabolomics analysis of pre-screened samples detected 1807 new numbers in positive ion mode and 1359 in negative ions. Through the detection of smoking-related metabolites (cotinine, nicotine-N'-oxide and trans-3'-hydroxycotinine), it was found that the smoking population was well separated from the non-smokers, and the feasibility of the analytical method was verified.

Data Analysis

Diagnostic and typing study: After applying statistical analysis to exclude human and gender interference, the authors identified four differential metabolites: NANA, cortisol sulfate, creatine riboside and 561+ (unidentified material). ROC analysis found that four differential metabolites had an AUC value between 0.63 and 0.76 in all populations and between 0.59 and 0.70 in stage I-II lung cancer patients. Among them, creatine riboside or all four metabolites were predicted to be more accurate (P

Prime Jones is a senior researcher from MtoZ Biolabs. She is specialized in the field of proteomics study.