Identification of protein pattern in kidney cancer using ProteinChip arrays and bioinformatics.
Tumor biology of renal cell carcinoma (RCC) is not very well understood, although many studies on molecular and cellular biology have been performed. It is accepted now that cancer research has to be performed also with proteomic tools, because proteins are the real actors in the genesis and progression of cancer. Therefore, we used a ProteinChip System(R) (SELDI) which is able to detect minute amounts of protein and moreover to analyze a complex protein pattern. We analyzed 37 cases of clear cell RCC as a training set including corresponding normal tissue. From all samples protein lysates were made and spotted directly on different chip surfaces (SAX2, WCX). After a washing procedure the arrays were analyzed in the ProteinChip Reader. All profiles were subjected to a bioinformatical analysis including normalization, clustering, rule extraction and rating. Defined rules (markers) were evaluated using a test set of 24 samples (13 tumor tissues and 11 normal kidney tissues). The generated rule base for the SAX2 surface showed a sensitivity of 100% and a specificity of 97.3%. For the WCX arrays the optimal rule base showed worse results. A combined rule base for SAX2 and WCX did not result in a higher sensitivity or specificity. Using the optimal rule base for the SAX2 chip in the test set, sensitivity and specificity reached 76.9% and 100%, respectively. The ProteinChip System represents a key technology for the rapid detection of cancer specific proteomic patterns. It is possible to identify clear cell renal cancer with high sensitivity and specificity from minimal amounts of cells.
Junker
Kerstin
K
Department of Urology, Friedrich-Schiller-University, D-07743 Jena, Germany. kerstin.junker@med.uni-jena.de
Gneist
Jana
J
Melle
Christian
C
Driesch
Dominik
D
Schubert
Joerg
J
Claussen
Uwe
U
Von Eggeling
Ferdinand
F
D045744:Cell Line, Tumor; D016000:Cluster Analysis; D019295:Computational Biology; D006801:Humans; D017403:In Situ Hybridization; D007668:Kidney / Q000378:metabolism; D007680:Kidney Neoplasms / Q000378:metabolism*; D005810:Multigene Family; D040081:Protein Array Analysis / Q000379:methods*; D012680:Sensitivity and Specificity; D012984:Software