title: Link test--A statistical method for finding prostate cancer biomarkers.
abstract: We present a new method, link-test, to select prostate cancer biomarkers from SELDI mass spectrometry and microarray data sets. Biomarkers selected by link-test are supported by data sets from both mRNA and protein levels, and therefore results in improved robustness. Link-test determines the level of significance of the association between a microarray marker and a specific mass spectrum marker by constructing background mass spectra distributions estimated by all human protein sequences in the SWISS-PROT database. The data set consist of both microarray and mass spectrometry data from prostate cancer patients and healthy controls. A list of statistically justified prostate cancer biomarkers is reported by link-test. Cross-validation results show high prediction accuracy using the identified biomarker panel. We also employ a text-mining approach with OMIM database to validate the cancer biomarkers. The study with link-test represents one of the first cross-platform studies of cancer biomarkers.
authors.affiliation: College of Information Science and Technology, University of Nebraska at Omaha, Omaha, NE 68182, USA. xdeng@mail.unomaha.edu
authors.forename: Xutao
authors.initials: X
authors.lastname: Deng
authors.forename: Huimin
authors.initials: H
authors.lastname: Geng
authors.forename: Dhundy R
authors.initials: DR
authors.lastname: Bastola
authors.forename: Hesham H
authors.initials: HH
authors.lastname: Ali
mesh_terms: D000465:Algorithms; D014408:Biomarkers, Tumor / Q000378:metabolism*; D003627:Data Interpretation, Statistical; D030562:Databases, Protein; D006801:Humans; D008297:Male; D011471:Prostatic Neoplasms / Q000175:diagnosis* / Q000378:metabolism; D040901:Proteomics; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
chemical_list: D014408:Biomarkers, Tumor