A gene signature of primary tumor identifies metastasized seminoma

Background m of this study was the prediction of metastatic status in seminoma based on examination of the primary tumor. s RNA was isolated from metastasized seminoma (n = 10, T1N1-2M0), non-metastasized seminoma (n = 21, T1-3N0M0), and corresponding normal tissues. Pooled RNA from 10 biopsies of each tissue type was hybridized on whole genome microarrays for screening purposes. Ninety-two selected gene candidates were quantitatively examined using real-time quantitative polymerase chain reaction (RTQ-PCR). s ent in gene expression was 88% between the whole genome microarrays and RTQ-PCR. Metastasized seminoma showed 1,912 up-regulated and 2,179 down-regulated genes with ≥2-fold differences in gene expression compared non-metastasized seminoma. RTQ-PCR of selected genes showed that mean gene expression values were significantly reduced in metastasized compared with non-metastasized seminoma. The presence of metastases could be predicted based on an 85-gene expression signature by using logistic regression. Sensitivity and accuracy of the 10-fold cross-validation model were 77.8% and 84.2%, respectively. sion stic regression model using an 85 gene expression signature allowed identification of metastasized seminoma from the primary tumor with a sensitivity of 77.8%.