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home :: proscar :: Mass_spectrometric_identification_of.txt

Wed, 24 May 2006


Mass spectrometric identification of human prostate cancer-derived proteins in serum of xenograft-bearing mice.

van den Bemd GJ, Krijgsveld J, Luider TM, van Rijswijk AL, Demmers JA, Jenster G

Lack of sensitivity and specificity of current tumor markers has intensified research efforts to find new biomarkers. The identification of potential tumor markers in human body fluids is hampered by large variability and complexity of both control and patient samples, laborious biochemical analyses, and the fact that the identified proteins are unlikely produced by the diseased cells, but are due to secondary body defense mechanisms. In a new approach presented here, we eliminate these problems by performing proteomic analysis in a prostate cancer xenograft model in which human prostate cancer cells form a tumor in an immune-incompetent nude mouse. Using this concept, proteins present in mouse serum that can be identified as human, will by definition, originate from the human prostate cancer xenograft and might have potential diagnostic and prognostic value. Using one-dimensional gel electrophoresis, liquid chromatography, and mass spectrometry, we identified tumor-derived human nm23/nucleoside diphosphate kinase (NME) in the serum of a nude mouse bearing the androgen-independent human prostate cancer xenograft PC339. NME is known to be involved in the metastatic potential of several tumor cells, including prostate cancer cells. Furthermore, we identified six human enzymes involved in glycolysis (fructose-bisphosphate aldolase A, triosephosphate isomerase, glyceraldehyde-3-phosphate dehydrogenase, alpha enolase, and lactate dehydrogenase A and B) in the serum of the tumor-bearing mice. The presence of human NME and GAPD in the serum of PC339-bearing mice was confirmed by Western blotting. Although the putative usefulness of these proteins in predicting prognosis of prostate cancer remains to be determined, the present data illustrate that our approach is a promising tool for the focused discovery of new prostate cancer biomarkers.

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