Candidate urine biomarker discovery from only five pairs of samples before and after tumor resection in glioma patients

Without the control of homeostatic mechanisms, urine accumulates systemic body changes and thus serves as an excellent biomarker source. However, urine is affected by many factors other than disease. Although many candidate biomarkers have been discovered in animal models, a large number of clinical samples might still be required for successful biomarker discovery. A self-controlled study should account for individual differences between patients. Gliomas are the most common primary malignant brain tumors and have a very poor prognosis. Early diagnosis of gliomas and the monitoring of tumor recurrence are crucial to improve glioma patient outcomes. However, it is unknown whether promising biomarkers can be identified from a relatively small number of glioma patient urine samples. In this study, urine samples from five glioma patients were collected at the time of tumor diagnosis and after total surgical removal of the brain tumor. A comparative proteomic analysis of urine samples before and after tumor resection was performed using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Using label-free proteome quantification, twenty-seven urinary proteins were significantly changed after tumor resection, many of which have been previously associated with gliomas, such as CEACAM1, ANXA7, CALR, CRYAB, CD276, pIgR, cathepsin D, beta-glucuronidase, and acid ceramidase. After functional annotation of these proteins, significant enrichment was identified for the regulation of tissue remodeling, autophagy, the inhibition of gene expression, the positive regulation of natural killer cell-mediated cytotoxicity and angiogenesis. In this study, candidate urinary biomarkers with the potential to detect disease and monitor tumor recurrence after treatment were identified in glioma patients. Our results suggested that using the self-control of before and after tumor resection is an effective method to identify differently expressed tumor proteins, even in a small number of urine samples. Our findings will help direct future biomarker studies involving brain cancer.