Repository: Freie Universit├Ąt Berlin, Math Department

Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry: serum protein profiling in seminoma patients.

Strenziok, R. and Hinz, S. and Wolf, C. and Conrad, T. O. F. and Krause, H. and Miller, K. and Schrader, M. (2009) Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry: serum protein profiling in seminoma patients. World J of Urology, 28 (2). pp. 193-197.

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Official URL: http://dx.doi.org/10.1007/s00345-009-0434-9

Abstract

PURPOSE: Surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF MS) allows rapid protein profiling of complex biological mixtures. We analyzed testicular germ cell cancer serum samples to differentiate between cancer and controls with a special focus on beta-hCG-negative seminomas. METHODS: Proteomic spectra were generated by the ProteinChip system and analyzed by the proteomic platform "proteomic.net". For statistical analysis, an artificial intelligence learning algorithm was used. RESULTS: The classification algorithm correctly identified the pattern in 90.4% of the patients. Decision trees predicted seminomas with 91.5% sensitivity and 89.4% specificity. Seminoma patients with normal beta-hCG serum level were correctly predicted with 80% sensitivity and 70% specificity. CONCLUSIONS: Our study demonstrates protein profiles of testicular germ cell cancer patients that differ in a highly significant degree from normal controls. Validation of these findings may enable proteomic profiling to become a valuable tool, especially for aftercare.

Item Type:Article
Subjects:Mathematical and Computer Sciences > Statistics > Mathematical Statistics
Medicine and Dentistry > Clinical Medicine
Mathematical and Computer Sciences > Artificial Intelligence > Machine Learning
Divisions:Department of Mathematics and Computer Science > Institute of Mathematics > Comp. Proteomics Group
Department of Mathematics and Computer Science > Institute of Mathematics
Department of Mathematics and Computer Science > Institute of Mathematics > BioComputing Group
ID Code:156
Deposited By: Tim Conrad
Deposited On:14 Jan 2009 12:01
Last Modified:18 Jan 2011 16:16

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