title: The discovery of putative urine markers for the specific detection of prostate tumor by integrative mining of public genomic profiles.
abstract: Urine has emerged as an attractive biofluid for the noninvasive detection of prostate cancer (PCa). There is a strong imperative to discover candidate urinary markers for the clinical diagnosis and prognosis of PCa. The rising flood of various omics profiles presents immense opportunities for the identification of prospective biomarkers. Here we present a simple and efficient strategy to derive candidate urine markers for prostate tumor by mining cancer genomic profiles from public databases. Prostate, bladder and kidney are three major tissues from which cellular matters could be released into urine. To identify urinary markers specific for PCa, upregulated entities that might be shed in exosomes of bladder cancer and kidney cancer are first excluded. Through the ontology-based filtering and further assessment, a reduced list of 19 entities encoding urinary proteins was derived as putative PCa markers. Among them, we have found 10 entities closely associated with the process of tumor cell growth and development by pathway enrichment analysis. Further, using the 10 entities as seeds, we have constructed a protein-protein interaction (PPI) subnetwork and suggested a few urine markers as preferred prognostic markers to monitor the invasion and progression of PCa. Our approach is amenable to discover and prioritize potential markers present in a variety of body fluids for a spectrum of human diseases.
authors.affiliation: Center for Molecular Medicine, School of Life Science and Biotechnology, Dalian University of Technology, Dalian, People's Republic of China.
authors.forename: Min
authors.initials: M
authors.lastname: Chen
authors.forename: Kai
authors.initials: K
authors.lastname: Wang
authors.forename: Liang
authors.initials: L
authors.lastname: Zhang
authors.forename: Cheng
authors.initials: C
authors.lastname: Li
authors.forename: Yongliang
authors.initials: Y
authors.lastname: Yang
mesh_terms: D014408:Biomarkers, Tumor / Q000652:urine*; D057225:Data Mining; D030541:Databases, Genetic; D018450:Disease Progression; D053263:Gene Regulatory Networks / Q000235:genetics; D023281:Genomics; D006801:Humans; D008297:Male; D009362:Neoplasm Metastasis; D009363:Neoplasm Proteins / Q000235:genetics / Q000378:metabolism; D011471:Prostatic Neoplasms / Q000235:genetics* / Q000652:urine*; D025941:Protein Interaction Mapping; D012680:Sensitivity and Specificity
chemical_list: D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins