You have accessJournal of UrologyKidney Cancer: Basic Research II1 Apr 2010204 A SPECIFIC PROTEIN SIGNATURE CHARACTERIZES THE METASTATIC POTENTIAL OF CLEAR CELL RENAL CELL CARCINOMAS Christian Heinze, Rico Pilchowski, Ferdinand von Eggeling, Mieczyslaw Gajda, Heiko Wunderlich, and Kerstin Junker Christian HeinzeChristian Heinze More articles by this author , Rico PilchowskiRico Pilchowski More articles by this author , Ferdinand von EggelingFerdinand von Eggeling More articles by this author , Mieczyslaw GajdaMieczyslaw Gajda More articles by this author , Heiko WunderlichHeiko Wunderlich More articles by this author , and Kerstin JunkerKerstin Junker More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2010.02.261AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Presently the prognosis of patients with metastatic renal cell carcinoma (RCC) is still poor although in spite of new therapies. Therefore it is necessary to identify prognostic parameters for an early detection of patients at high risk for metastasis. The aim of our study is to identify specific protein patterns in tumor tissue of patients distinguish between metastatic and non metastatic tumors to define the metastatic potential of primary tumors METHODS To establish specific protein patterns in tumor tissue we analyzed a pool of 45 patient samples including 25 metastatic and 20 non metastatic tumor samples. Protein lysates from tumor tissues were investigated by the Surface-Enhanced Laser desorption/Ionization Time-of-Flight Mass Spectrometry (SELDI-TOF-MS). The ProteinChip-Array Q10 (a strong anion exchanger) was used. The detected spectra were analyzed by the computer software XL-Miner 3.5 (Biocontrol Jena GmbH) with the Fuzzy c-means method for clustering followed by establishing rules and evaluation using the relevance index by Kiendl. This tool automatically generates rules with best prediction. Further more we analyse early and late metastasized tumor samples by the same techniques to establish significant proteomic pattern to define a tumor at high risk for aggressive metastasis. RESULTS The generated rule base for the Q10 surface at a significance level of α=0.90 showed a sensitivity of 95% and a specificity of 92%. This rule base permitted the classification of the groups metastatic / non matastatic tumors with a total reliability of 93%. This rule base contains 12 relevant protein peaks including highly significant peaks at 10348 Da, 10506 Da and 44565 Da. CONCLUSIONS The ProteinChip Technology including bioinformatic evaluation software XL-Miner 3.5 is suitable to predict the potential of a primary tumor to metastasize and to characterize highly aggressive tumors based on specific protein profiles. In the next step, the relevant proteins have to be identified. Based on these data it seems possible to select patients for an early adjuvant therapy. Jena, Germany© 2010 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 183Issue 4SApril 2010Page: e81 Advertisement Copyright & Permissions© 2010 by American Urological Association Education and Research, Inc.MetricsAuthor Information Christian Heinze More articles by this author Rico Pilchowski More articles by this author Ferdinand von Eggeling More articles by this author Mieczyslaw Gajda More articles by this author Heiko Wunderlich More articles by this author Kerstin Junker More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...